In closing, I would like to thank my entire family for their emotional support and for their continued encouragement, which helped me persevere and complete my PhD. vapor" conditions, (b) "high vapor" conditions, (c) from toluene under "no vapor" conditions and (d) from mesitylene under "no vapor" conditions. [START_REF] Nilsson | Morphology and Phase Segregation of Spin-Casted Films of Polyfluorene/PCBM Blends[END_REF] ............................. Table 2.1 The list of processing solvents and additives used in this thesis. 6. 3 The candidates provided for PF2:PC71BM by IBSS®CAMD with a GloPerf > 0.6. ........... Table 6.4 The candidates provided for PF2:EH-IDTBR by IBSS®CAMD with a GloPerf > 0.6. ........ Table 6.5 List of the best solvent candidates selected from the results of molecular design provided by IBSS®CAMD for PF2:PC71BM blends. [6,6]-phenyl-C61-butyric acid methyl ester PC71BM [6,6]-phenyl-C71-butyric acid methyl ester PCE/Ƞ Power conversion efficiency PEDOT:PSS Poly (3,4-ethylenedioxythiophene)

Figures

Tables

List of variables and abbreviations

General Introduction

While for the past sixty years, inorganic semiconductors (such as silicon or gallium arsenide) and metals have formed the backbone of the semiconductor industry, today organic semiconductors are increasingly being used in various electronic devices, such as organic light emitting diodes (OLEDs), radio-frequency identification (RFID), organic field-effect transistors (OFET) and organic photovoltaics (OPVs). In 1977, Chiang et al.

reported a chemically doped polyacetylene, the first highly conductive polymer that could be used as an electrically active material. 1 Since then, conjugated organic materials have been the focus of significant research efforts. While initially the development of organic semiconductor devices has been hampered by the poor performance and stability of early organic semiconductors, significant improvements in the synthesis and processing of new molecular materials, such as conjugated polythiophenes 2 , have increased the prospects for commercialization of organic semiconductor. [3][4][5][6] For example, OLEDs are now being used in many flat panel displays for smartphones. 7 Simplicity and lower costs of organic semiconductor device manufacturing have been the primary reasons driving these devices towards commercialization.

The development of functional organic materials that can be processed from solution has inspired many research groups to explore the potential of applying printing technologies to the large-scale manufacturing of organic electronic devices. 8- 10 Solution-based printing technologies achieve the integration of advanced functions onto large-area substrates, such as flexible paper, plastic sheets, or large-area rigid glass, at a lower manufacturing cost than traditional manufacturing techniques. [11][12][13] For these technologies, the processing solvents play a critical role both in the performance of the organic devices and in their environmental impact. Therefore, the development and application of green solvents in the organic semiconductor field has attracted a lot of interest. [14][15][START_REF] Li | Biodegradable Materials and Green Processing for Green Electronics[END_REF][START_REF] Ribeiro | Green and Stable Processing of Organic Light-Emitting Diodes from Aqueous Nanodispersions[END_REF] The industrial revolution has caused a serious transformation of the human standard of living, leading to major advances that have contributed to improvements in life expectancy, quality of life and comfort. These developments have been accompanied by a dramatic increase in the world's population and, with it, a dramatic rise in energy demand. Today, the energy supply issue, more than ever, is a global problem, with a wide audience, from politicians to the scientific community. To date, energy demand has mostly been met by conventional hydrocarbons (oil, gas, coal).

However, the greenhouse gases emitted into the Earth's atmosphere from the burning of fossil fuels are causing enormous environmental damage and have a significant impact on global climate change. Moreover, fossil fuels are a finite source of energy, leading to a shortage of these resources as societies develop, with political and social crises ensuing at the different places of today's world. In this case, solar energy offers many privileges as a clean and renewable energy source. The primary motivation for further development of solar energy research is the enormous amount of energy that the sun delivers to the Earth's surface every day. Considering simple assumptions and rough estimates, it has been reported that solar power plants could provide up to 67 TW of electricity by 2050, more than twice the world's energy demand, provided they cover 2% of the land area with an average power conversion efficiency (PCE) of about 12%. [START_REF] Darling | The Case for Organic Photovoltaics[END_REF] Solar cells, also known as photovoltaic cells, are devices that convert sunlight directly into electricity. They can be fabricated from a variety of materials (organic, inorganic, etc.) and their PCE over time is shown in the National Renewable Energy Laboratory chart 19 (Figure 1.1). By far, silicon solar cells (mono-and multicrystalline silicon) have controlled the commercial solar cells market, reaching a PCE of 22.9% for mono-crystalline and 18.5% for multicrystalline silicon in commercial modules in 2016. [START_REF] Nathan | Research Opportunities to Advance Solar Energy Utilization[END_REF] However, silicon-based solar cells have obvious drawbacks that reduce their competitiveness with fossil fuels, including high production costs, heavy weight, high energy payback time (EPBT) (of the order of 3 years). In order to reduce the production costs and the EPBT, different thin film technologies are being developed intensively.

Organic Photovoltaics (OPV) is seen as a promising alternative to conventional photovoltaic systems, due to the possibility of producing light weight and flexible modules at low cost. Also, the recently reported significant increase in power conversion efficiency (PCE) of OPV devices strengthen the potential for this technology to contribute to large-scale renewable energy production. The history of organic electronics began with the discovery of conductive πconjugated polymers by Shirakawa, MacDiarmid and Heeger in the late 1970s. [START_REF] Shirakawa | Synthesis of Electrically Conducting Organic Polymers: Halogen Derivatives of Polyacetylene, (CH)X[END_REF] Traditionally, polymers are regarded as insulating materials; however, the presence of delocalized π electrons can attribute semi-conductive properties to polymers. In 1986, Tang et al. reported the first organic solar cell with a PCE of 0.95%. [START_REF] Tang | Two-Layer Organic Photovoltaic Cell[END_REF] In 1995, Yu et al.

made an important breakthrough in PCE of OPVs by introducing the concept of donoracceptor heterogeneous junction. [START_REF] Yu | Polymer Photovoltaic Cells: Enhanced Efficiencies via a Network of Internal Donor-Acceptor Heterojunctions[END_REF] Until the early 2000s, the PCEs of solutionprocessed bulk heterogeneous junction solar cells remained around 3%. [START_REF] Shaheen | 2.5% Efficient Organic Plastic Solar Cells[END_REF][START_REF] Padinger | Effects of Postproduction Treatment on Plastic Solar Cells[END_REF] However, despite low cost and simple manufacturing methods, these low efficiency values remain a major impediment to the industrial development of organic technologies. As a result, many efforts have been made to improve their optoelectronic properties. To date, at the lab scale, a PCE of 18.22% has been reported for a single-junction OPV device based on a new electron donor copolymer "D18" and a new acceptor molecule "Y6" [START_REF] Liu | 18% Efficiency Organic Solar Cells[END_REF] . These achievements demonstrate the potential of OPVs in becoming a market reality. In addition, OPV devices can be processed from solutions, suggesting that it is easier to fabricate large-area, low-cost photovoltaic modules. Some innovative devices, such as flexible, transparent and lightweight solar cells (Figure 1.2) have already been reported [START_REF] Koo | Flexible Organic Solar Cells Over 15% Efficiency with Polyimide-Integrated Graphene Electrodes[END_REF][START_REF] Qu | Biomimetic Electrodes for Flexible Organic Solar Cells with Efficiencies over 16%[END_REF][START_REF] Anctil | Net Energy and Cost Benefit of Transparent Organic Solar Cells in Building-Integrated Applications[END_REF][START_REF] Lee | Toward Visibly Transparent Organic Photovoltaic Cells Based on a Near-Infrared Harvesting Bulk Heterojunction Blend[END_REF] . At last, OPV modules have a much lower energy payback time (around 0.4 -1 year) [START_REF] Anctil | Net Energy and Cost Benefit of Transparent Organic Solar Cells in Building-Integrated Applications[END_REF][START_REF] Zhou | Assessing the Photovoltaic Technology Landscape: Efficiency and Energy Return on Investment (EROI)[END_REF] and an excellent power/weight ratio than silicon-based devices. "Green" processing of OPV devices involves the use of non-toxic solvents, ecofriendly functional layers that are compatible with large-scale, low-cost fabrication methods. Essentially, green processing should suppress the emission of toxic substances into the environment while, simultaneously, leading to high-performance devices (in comparison with the performances of devices manufactured by conventional methods). Therefore, balancing low environmental impact with device performance is the key for successful green fabrication.

Over the past decades, great efforts were made to increase the PCE of organic solar cells up to 18% and to reach the threshold value required for industrialization and commercialization. [START_REF] Liu | 18% Efficiency Organic Solar Cells[END_REF][START_REF] Koo | Flexible Organic Solar Cells Over 15% Efficiency with Polyimide-Integrated Graphene Electrodes[END_REF][START_REF] Qu | Biomimetic Electrodes for Flexible Organic Solar Cells with Efficiencies over 16%[END_REF] However, when it comes to the industrial development of OPV modules, safe, eco-friendly and economical manufacturing is of paramount importance and will depend on the availability of non-toxic solvents for roll-to-roll production of organic modules. Historically, OPV devices were typically manufactured by standard solution printing techniques using laboratory equipment, and halogenated and/or aromatic solvents were chosen as processing solvents to meet thin film quality requirements. [START_REF] Huang | Efficient Ternary Bulk Heterojunction Solar Cells Based on Small Molecules Only[END_REF][START_REF] Diao | Morphology Control Strategies for Solution-Processed Organic Semiconductor Thin Films[END_REF] However, since such solvents are harmful to human health of humans and to the environment, they impede sustainable development and are therefore not suitable for mass production and commercialization of OPV modules.

It is thus urgent that environment-friendly or "green" solvents are found, which allow to reach power conversion efficiencies similar to those obtained from halogenated solutions.

Current research results on less/non-toxic processing solvents for OPV devices are rather limited. Up to now, the selection of alternative solvents was mostly the result of tedious experimental trial and error approaches, which may have left out suitable candidate solvents. Importantly, no solvent can be considered as a "universal" one for all organic semiconductors, because solubility depends both on the molecular structure of the solute and on the solvent. The search for new solvents is indeed a complex problem, requiring the simultaneous consideration of many properties, which may compete with each other in the sense that an increase in one property's performance may reduce the performance in another. Hence finding a suitable solvent is often the compromise of a multi-objective problem. Properties such as solubility, viscosity, safety, durability, toxicity..., are altogether important for the final application and all have an impact on the performance of the device. In addition, as donor and acceptor materials are continually being modified to achieve OPV devices with still higher performance, the development of a more effective method for identifying nontoxic solvents that allow processing of these new materials is a critical issue. It should also be noted that the demand for non-toxic solvents is likewise important for other organic devices processed from solution, such as OLEDs, OFETs, or photodiodes. [START_REF] Zheng | Green Solvent Processed Tetramethyl-Substituted Aluminum Phthalocyanine Thin Films as Anode Buffer Layers in Organic Light-Emitting Diodes[END_REF][START_REF] Wang | Flexible RFID Tag Metal Antenna on Paper-Based Substrate by Inkjet Printing Technology[END_REF][START_REF] Hong | Morphology Driven by Molecular Structure of Thiazole-Based Polymers for Use in Field-Effect Transistors and Solar Cells[END_REF] As sustainability is equally desirable, solvents based on agricultural resources, or socalled "biosolvents", are initiating a growing interest as they usually exhibit low health and environmental impacts. However, regarding primary functions such as solubility, biosolvents are less versatile than most chlorinated or hydrocarbon solvents that need to be replaced. Therefore, new methodologies based on a reverse engineering approach have been developed to make the screening and selection of biosolvents less empirical.

In this thesis, we explore the effectiveness of reverse engineering based on a computer assisted molecular design (CAMD) tool to find alternative biosolvents for organic photovoltaic materials. The method is applied to blends of reference organic photovoltaic materials as well as to synthesized high-performance donor polymers.

The reference materials were studied in order to understand the relationship between OPV performance and alternative solvent properties. The method is then applied to synthetic polymers to achieve high performance of "green-processed" OPVs in an efficient way. ORGANIC PHOTOVOLTAICS CHAPTER 2

Organic Photovoltaics

This chapter presents the current knowledge of the physical mechanisms of organic solar cell operation and the main parameters that determine the energy conversion efficiency. First, a brief introduction is provided to the physical properties of organic semiconductors. Then, the key physical steps that occur during the photon energy conversion are described in detail. After that, the main parameters of the solar cells are presented.

Organic Semiconducting Materials

Organic semiconductors are carbon-based materials, composed of organic molecules which include a π-conjugated system as molecular backbone. Within a πconjugated carbon chain, the carbon atoms adopt a "sp 2 " configuration: three out of four valence electrons of each C atom occupy sp 2 hybridized orbitals, with the fourth valence electron being in a pz orbital. The sp 2 electrons form strong σ-bonds with neighboring atoms and are responsible for most of the molecular binding energy, while the pz electrons form weaker π-bond with neighboring C atoms. The bond-length between neighboring carbon atoms forming a conjugated π-electron system undergoes a slight periodic variation. The molecular backbone is therefore represented symbolically by an alternation of single and double bonds. Figure 2.1 illustrates a simple example of polyacetylene, which consists of repeating ethylene units. Within the conjugated π-electron system, the π-electrons are highly delocalized, allowing electrons to move freely along the conjugated carbon backbone. The spatial extension of electron delocalization is referred to as conjugation length. The overlap of the pz orbitals of neighboring C atoms results in the formation of bonding and antibonding orbitals. The bonding orbital is filled with electrons and is lower in energy. It contributes to the Highest Occupied Molecular Orbital (HOMO). The antibonding orbital is unoccupied and at higher energy and involved in the Lowest Unoccupied Molecular Orbital (LUMO). In organic semiconductors, the distribution of HOMO and LUMO levels are the analogs of respectively the valence and conduction bands of conventional inorganic semiconductors. The difference between the HOMO and LUMO levels is called energy bandgap. Organic materials are expected to behave as semiconductors when the energy bandgap is below ~3eV. In organic solar cells, the active layer is generally composed of two organic semiconductors. If the HOMO and LUMO levels of one semiconductor are higher than those of the second component (i.e., lower in absolute terms), this semiconductor behaves as an electron-donor.

Accordingly, the semiconductor with the deeper lying HOMO and LUMO levels is referred to as an electron-acceptor material.

Working Principle of OPV

The overall working principle of OPV devices can be summarized in four steps as follows: (4) collection of the free carriers at the electrodes.

Light absorption and exciton generation

In a conventional inorganic semiconductor, the Coulomb interaction of holes and electrons are efficiently reduced due to the large dielectric constant (~10).

Correspondingly, the exciton binding energy is in the range of a few meV, and therefore excitons can be dissociated by thermal energy at room temperature. On the contrary, the dielectric constant of organic semiconductors is around 3, much smaller than that of inorganic semiconductors, and the electron and hole wavefunctions are generally delocalized over only a few molecular segments, causing a strong Coulomb interaction between electron-hole pairs. Hence, the consequently high exciton binding energy (100 ~ 1400 meV) prevents excitons from being dissociated into free charges directly by thermal energy at ambient temperature. [START_REF] Knupfer | Exciton Binding Energies in Organic Semiconductors[END_REF][START_REF] Hummer | Oligoacene Exciton Binding Energies: Their Dependence on Molecular Size[END_REF][START_REF] Van Der Horst | Calculation of Excitonic Properties of Conjugated Polymers Using the Bethe-Salpeter Equation[END_REF][START_REF] Clarke | Charge Photogeneration in Organic Solar Cells[END_REF] For example, P3HT (poly(3hexylthiophene)), a common donor material for OPV devices, an exciton binding energy of 300~700 meV has been reported. [START_REF] Deibel | Energetics of Excited States in the Conjugated Polymer Poly(3-Hexylthiophene)[END_REF] Since excitons have generally a lifetime of the order of nanoseconds

Exciton diffusion and dissociation at the D/A Interface

Excitons generated by photon absorption need to be dissociated to generate free charges. Because of the high exciton binding energy, an additional driving force is required to promote exciton dissociation. This driving force is provided by the energy offset between the frontier orbital energy levels of the donor and acceptor materials that compose the organic heterojunction. When the excitons are separated on a heterojunction, electrons will be transferred and dominate the acceptor material, which has deeper levels of HOMO and LUMO, while the holes remain on the donor material. In 2007, Derouiche and Djara have reported that energy differences in HOMO and LUMO levels of donor/acceptor organic materials could be proven to be responsible for the improvement of all photovoltaic properties of organic solar cells. [START_REF] Derouiche | Impact of the Energy Difference in LUMO and HOMO of the Bulk Heterojunctions Components on the Efficiency of Organic Solar Cells[END_REF] Figure 2.2 illustrates the exciton dissociation into free charges in the case the exciton is generated in the donor material. The energy difference in the LUMO levels of the donor/acceptor materials (ΔLUMO) will drive the exciton dissociation, which has to be greater than the binding energy of the excitons. [START_REF] Athanasopoulos | What Is the Binding Energy of a Charge Transfer State in an Organic Solar Cell?[END_REF] For many donor/acceptor systems using a fullerene derivative as electron acceptor a ΔLUMO greater than 0.3 eV has been found to be sufficient. [START_REF] Scharber | Design Rules for Donors in Bulk-Heterojunction Solar Cells -Towards 10 % Energy-Conversion Efficiency[END_REF][START_REF] Bre´das | Charge-Transfer and Energy-Transfer Processes in π-Conjugated Oligomers and Polymers: A Molecular Picture[END_REF] Koen Vandewal has reported that a ΔLUMO as low as 0.1 eV is sufficient to achieve exciton dissociation in the active layer. [START_REF] Vandewal | Interfacial Charge Transfer States in Condensed Phase Systems[END_REF] After exciton generation, the excitons need to reach the donor/acceptor interface by diffusion to be dissociated. If ΔLUMO is large enough, a charge transfer from the donor to the acceptor occurs, giving rise to a charge transfer (CT) state. The CT process occurs at a very short timescale (around 45~100 fs), [START_REF] Sariciftci | Photoinduced Electron Transfer from a Conducting Polymer to Buckminsterfullerene Author[END_REF][START_REF] Brabec | Tracing Photoinduced Electron Transfer Process in Conjugated Polymer/Fullerene Bulk Heterojunctions in Real Time[END_REF] which is roughly 10 000 times smaller than the exciton lifetime (around 1ns). After CT, the electron-hole pairs, although still influenced by coulomb interactions, are able to dissociate into a charge separated (CS) state corresponding to a free electron in the acceptor domain and a free hole in the donor domain. The CT is hence an intermediate state between the Coulomb bounded exciton and free charges.

It is currently believed that the delocalized nature of holes and electrons on their respective materials could weaken the coulomb interactions enough to allow the formation of the CS state. [START_REF] Han | From Molecular Packing Structures to Electronic Processes: Theoretical Simulations for Organic Solar Cells[END_REF] In some cases, the presence of an electric field may also contribute to the CS formation. The average distance covered by excitons before recombination (in the absence of a D/A interface) corresponds to the exciton diffusion length (Lex), which is generally of the order of a few nanometers. Excitons generated at a distance from the heterojunction longer than Lex will recombine before reaching the heterojunction, reducing the energy conversion efficiency. Therefore, the concept of D/A bulk heterojunction, consisting of a mixture of donor and acceptor domains, has been introduced (Figure 2.3).

Charge carrier transport

Once excitons are dissociated into free charge-carriers, the latter have to travel towards their respective electrodes for collection within their lifetimes. The main driving forces for the transport of free charge-carriers are drift and diffusion currents.

The charge-carriers may drift along the build-in electric field lines, with the electric field being generated by dissymmetric electrodes. In a planar heterojunction, the recombination probability of free carrier is very low because they are spatially separated. On the other hand, in a bulk heterojunction, electrons and holes are more likely to meet at the D/A interface and recombine before charge extraction may occur.

The mobilities of free charges in the active layer is a major limitation for charge collection. [START_REF] Sariciftci | Photoinduced Electron Transfer from a Conducting Polymer to Buckminsterfullerene Author[END_REF] Balanced hole and electron mobilities are required to avoid accumulation of electrons or holes in the active layer and the formation of space charge that may impact the internal electric field. If for instance the electron mobility in organic semiconductors is higher than hole mobility, the electrons are transported more efficiently to the electrode. That is, the rate of electrons reaching the cathode is higher than that of holes to the anode, resulting in that the electrons tend to gather near the cathode interface, generating space charge in the active layer. This effect modifies the electric field distribution in the active layer and limit the current output of a solar cell.

As a consequence, organic semiconductors with high and similar hole and electron mobilities are being developed to overcome this weakness. 52-56

Charge-carrier extraction at electrodes

Free charge-carriers can be collected by electrodes when they reach the active layer/electrode interface. The potential barrier for the given charge carrier type (electrons at the anode or holes at the cathode) at the interface needs to be minimized to avoid charge accumulation and recombination, and achieve efficient charge-carrier extraction. Moreover, carrier accumulation causes the misalignment of active layer/electrode energy level, and strongly influences the VOC (open-circuit voltage) and fill factor (FF) of the solar cells. [START_REF] Wagenpfahl | S-Shaped Current-Voltage Characteristics of Organic Solar Devices[END_REF] The ideal situation corresponds to the work function of the anode matching well the donor HOMO level, and the work function of the cathode matching the acceptor LUMO level. In this case, the contacts are ohmic and VOC correlates with the difference between the donor HOMO and acceptor LUMO. In addition, charge collection at the wrong electrodes, i.e., electrons at the anode or holes at the cathode, can be another factor that reduces device performance.

Therefore, electrical and hole transport layer (ETL and HTL) are often implemented between the active layer and the electrode. For example, the low valence band and large band gap of ZnO (Ev ~4.4 eV, Eg ~7.8 eV) prevent holes from reaching the cathode while allowing efficient electron extraction. [START_REF] Wang | Solution-Processable Metal Oxides/Chelates as Electrode Buffer Layers for Efficient and Stable Polymer Solar Cells[END_REF][START_REF] Liang | Cathode Buffer Layers for Inverted Polymer Solar Cells[END_REF] 2

.3 Functionality of the active Layer

As discussed in Section 2.2, excitons diffuse towards the D/A interface before their dissociation (Figure 2.3 b). Ideally, the phase separation between donor and acceptor materials in bulk heterojunctions should lead to domain sizes of the order of the exciton diffusion length, thereby minimizing exciton recombination and allowing excitons to be dissociated into a charge transfer state at the D/A interface (Figure 2.3 b). Phase separation between both materials is therefore critical to the electronic processes underlying the operation of the device. Importantly, the intermolecular interactions between both organic components and the means of manufacturing the OPV devices can influence the thin film morphology considerably. In general, phase separation of the active layer can be manipulated by designing the molecular structure and optimizing the device processing, e.g., by using different solvents, additives, co-solvents, thermal annealing or solvent vapor annealing.

Selecting an appropriate solvent is a simple and common way to optimize the active layer morphology and to achieve high performance devices. [START_REF] Diao | Morphology Control Strategies for Solution-Processed Organic Semiconductor Thin Films[END_REF][START_REF] Han | From Molecular Packing Structures to Electronic Processes: Theoretical Simulations for Organic Solar Cells[END_REF][START_REF] Nilsson | Morphology and Phase Segregation of Spin-Casted Films of Polyfluorene/PCBM Blends[END_REF] On the other hand, phase separation can be addressed, to some extent, by molecular engineering of the D and A molecules. For instance, fluorine substitution (see Chapter 6), which has been introduced to adjust frontier orbital energy levels and to improve charge carrier transport, also influences the phase separation and molecular assembly by enhancing intermolecular interactions. In general, controlling and optimizing the morphology of the active layer is necessary to achieve high photovoltaic performances. and "inverted", respectively. For the "standard" structure, holes are extracted at the transparent bottom electrode and electrons at the top metal electrode. On the contrast, in the "inverted" structure, electrons are collected at the transparent bottom electrode and holes at the top metal electrode. In the "standard" structure, a low work [START_REF] Mcdowell | Organic Solar Cells Processed from Green Solvents[END_REF][START_REF] Kong | Top-down Approach for Nanophase Reconstruction in Bulk Heterojunction Solar Cells[END_REF][START_REF] Jagadamma | Polymer Solar Cells with Efficiency >10% Enabled via a Facile Solution-Processed Al-Doped ZnO Electron Transporting Layer[END_REF][START_REF] Liao | Single Junction Inverted Polymer Solar Cell Reaching Power Conversion Efficiency 10.31% by Employing Dual-Doped Zinc Oxide Nano-Film as Cathode Interlayer[END_REF] or titanium oxides (TiOx) [START_REF] Steim | Interface Modification for Highly Efficient Organic Photovoltaics[END_REF][START_REF] Hadipour | Room Temperature Solution-Processed Electron Transport Layer for Organic Solar Cells[END_REF][START_REF] Litzov | Development of Efficient and Stable Inverted Bulk Heterojunction (BHJ) Solar Cells Using Different Metal Oxide Interfaces[END_REF][START_REF] Kuwabara | Inverted Type Bulk-Heterojunction Organic Solar Cell Using Electrodeposited Titanium Oxide Thin Films as Electron Collector Electrode[END_REF] . Taking this into account, "inverted" device structures are accepted to be more stable than "standard" ones and they were shown to perform better. [START_REF] Yuan | Structure, Band Gap and Energy Level Modulations for Obtaining Efficient Materials in Inverted Polymer Solar Cells[END_REF][START_REF] Zhang | Non-Conjugated Polymers as Thickness-Insensitive Electron Transport Materials in High-Performance Inverted Organic Solar Cells[END_REF][START_REF] Thambidurai | Solution-Processed Ga-TiO2 Electron Transport Layer for Efficient Inverted Organic Solar Cells[END_REF][START_REF] Abdallaoui | Comparative Study of Conventional and Inverted P3HT: PCBM Organic Solar Cell[END_REF] More details on device architecture differences can be found in Ref 73. The inverted device structure was used throughout this work.

Device Structures and working principle

Current -Voltage Characteristics

The main parameter that describes the performance of a solar cell is its power conversion efficiency (η or PCE), defined by:

η(%) = P max P in × 100% (1)
where Pmax is the highest electrical power per unit area delivered by the solar cell, and Pin the incident light intensity.

The values of η is generally measured by exposing the solar cell to a 1000W m -2 light source characterized by a AM 1.5 solar spectrum. The current density J as a function of an applied DC voltage (V) is recorded subsequently under darkness and under illumination. Figure 2.5 reports the illustrative dark and illuminated J-V curves.

The maximum power point (MPP) represents the device operational point at which

Standard Structure Inverted Structure (a) (b)
the product of JxV is maximum and corresponds to the highest power delivered by the solar cell under AM1.5 illumination conditions.

Short Circuit Current Density (JSC)

As shown in Figure 2.5, the short circuit current density (JSC) is obtained from the solar cell under short circuit conditions (V = 0 V). JSC represents the number of chargecarriers that are collected under illumination when the build-in electric field is at its maximum. JSC is generally proportional to the number of absorbed photons in the active layer. It is often considered that enhanced optical/electrical parameters such as a high photon absorption coefficient and high carrier mobilities improve JSC. Besides, phase separation plays a significant role in charge carrier generation. For domain sizes of the order of the exciton diffusion length (typically less then 10 nm), most photons are absorbed at a sufficiently short distance from the donor/acceptor interface to allow excitons to reach the donor/acceptor interface and to be dissociated into free charge carriers before recombination. [START_REF] Ma | Structure-Property Relationships of Oligothiophene-Isoindigo Polymers for Efficient Bulk-Heterojunction Solar Cells[END_REF][START_REF] Bloking | Comparing the Device Physics and Morphology of Polymer Solar Cells Employing Fullerenes and Non-Fullerene Acceptors[END_REF][START_REF] Sharenko | The Effect of Solvent Additive on the Charge Generation and Photovoltaic Performance of a Solution-Processed Small Molecule: Perylene Diimide Bulk Heterojunction Solar Cell[END_REF] During the free charge carrier extraction process, the free charges have to cross the active layer to reach the respective electrodes. Hence, interconnected donor and acceptor pathways must be present within the active layer. 1,[START_REF] Proctor | Understanding Charge Transport in Molecular Blend Films in Terms of Structural Order and Connectivity of Conductive Pathways[END_REF] Moreover, the domain purity should be as high as possible to avoid charge carrier trapping or recombination at bulk defect sites.

V oc = E Fn -E Fp q (2)
Due to the energetic disorder of organic semiconductors, the energy level distributions of the HOMO and LUMO bands of an organic semiconductor are approximately gaussian shaped, causing the quasi-Fermi levels to be pinned to the tail energy states. These tail states lead to a downshift of the electron and an upshift of the hole quasi-Fermi levels and thereby reduce the VOC. In general, the factors that play a crucial importance in determining the VOC are therefore energetic disorder, CT states distribution, carrier density and the quality of the semiconductor/electrode interfaces. A more detailed information about the origin of VOC can be found in the Refs 80,81.

Fill Factor (FF)

The FF can be considered as a measure of how efficiently photo-generated charge carriers can be extracted under the maximum power point operating conditions. It is defined as the ratio of the maximum power delivered by the device over the product of the open circuit voltage and short circuit current:

FF = J MPP ×V MPP J SC ×V OC (3)
where JMPP and VMPP correspond to the maximum power (MPP) point of the cell (Figure 2.5).

FF reflects the competition between recombination and extraction rates of free charges and is influenced, among others, by the series resistance (RS) and shunt resistance (RSH) of the OPV device. RS depends on the conductivity of the electrodes (especially ITO), the active layer and the interfacial layers. RSH may be caused by different types of leakage currents, e.g. imperfect active layer quality, aggregates etc. [START_REF] Yu | Polymer Photovoltaic Cells: Enhanced Efficiencies via a Network of Internal Donor-Acceptor Heterojunctions[END_REF] Finally, the power conversion efficiency of the solar cell can be written as:

η(%) = V OC ×J SC ×FF P in × 100% (4)

Fabrication of OPVs

An inverted structure is used throughout this thesis due to its advantages mentioned above. Firstly, a brief description of the materials and substrates used is given. Next the elaboration procedures of "inverted" photovoltaic device structures and the device characterization methods are presented.

Materials and Substrates

P3HT, PC71BM and EH-IDTBR were purchased from Solaris Chem Inc., Solenne BV and 1-Material Inc, respectively. A ZnO nanoparticle dispersion (N-10) was purchased from Avantama. The properties of standard processing solvents and additives used for the active layer deposition and purchased at Sigma Aldrich are shown in

Experimental details

First, ITO-coated glass substrates were systematically cleaned in ultrasonic bath of deionized water, acetone and 2-propanol at 45°C for 15 minutes for each step. They were then dried under nitrogen flow and treated in a UV/Ozone oven to remove residual organic contaminants.

Before depositing the active layer, a 7-10 nm thin layer of ZnO nanoparticles was deposited by spin-coating, using the following steps: Then, the active layer was spin-coated under nitrogen ambient (glove box). The organic semiconductors were weighted with the desired proportion in vials. Solvents were introduced to the vials to solubilize the organic semiconductors. These vials were put on a hotplate and stirred overnight at 60ᵒC. For each polymer used in this thesis, the spin-coating conditions of the active layer were optimized to obtain homogeneous films. The corresponding thin film deposition parameters will be presented in the related chapters. For the inverted photovoltaic structure, thin layers of MoO3 (~7 nm)

and silver (120 nm) were thermally evaporated sequentially under vacuum (Pressure ≈ 1x10 -6 mbar) and used as top electrodes. The OPV sample and shadow mask used for JV measurements are shown in Figure 2.

Characterization of OPV devices 2.6.1 JV characteristics

The JV curves of OPV devices were measured under a BET Technologies Sun 3000 AM 1.5G-100 mW/cm 2 solar simulator, using a LabView-controlled Keithley 2400 SMU device parameter analyzer. JV characterizations were carried out at room temperature in a glove box filled with N2. All the photovoltaic parameters (VOC, JSC, FF and PCE) were extracted using a LabView program. The JV measurements shown in this thesis (chapter 5 and 6) are averaged over 24 cells (6 samples).

Thickness measurement

The thickness of the active layer was measured by a DektakXT stylus profiler. In our study, the average thickness was obtained from 6 measurement points on two samples.

Ultraviolet-visible spectroscopy

The absorption a material either in solution or in thin films can be measured by ultraviolet-visible (UV/Vis) spectroscopy by a UV/Vis spectrophotometer. In this thesis, all the absorption profiles of pure polymers in solid state were characterized using a Shimadzu 082395 spectrophotometer at ICPEES with the assistance of Dr. Nicolas Leclerc. In-situ temperature dependent UV/Vis measurements in solutions were carried out with the help of Dr. Laure Biniek at ICS on the Agilent Cary 60 UV-VIS spectrophotometer.

Strategies for Controlling the Active Layer Morphology and

Methods for Solvents Selection

Active Layer Morphology

A key property that controls the solar cell performances is the morphology of the photoactive layer, which consists of intimately mixed electron donor and electron acceptor domains. Large donor and acceptor domains provide a percolating pathway for efficient charge transport and collection, but lead to a loss of interfacial area, low exciton dissociation rates and thus low free charge generation rates. [START_REF] Oosterhout | Absence of Mixed Phase in Organic Photovoltaic Active Layers Facilitates Use of Green Solvent Processing[END_REF] On the other hand, strong intermixing results in a large donor/acceptor interface, but hinder charge transport and increase the charge recombination rate. Consequently, the morphology of the active layer composed of a given donor/acceptor blend needs generally to be optimized in order to provide simultaneously a high exciton dissociation rate, minimum charge recombination and efficient charge transport and extraction. For solution-processed OPV devices, processing solvents and additives play a crucial role in this optimization process.

Role of Processing Solvents

For solution-processed devices, the BHJ morphology is strongly dependent on the thermodynamic properties and drying kinetics of the solution used to elaborate the organic layers. [START_REF] Cho | Solution Phase Exciton Diffusion Dynamics of a Charge-Transfer Copolymer PTB7 and a Homopolymer P3HT[END_REF][START_REF] Yang | Crystalline Organization of a Methanofullerene as Used for Plastic Solar-Cell Applications[END_REF] The thermodynamic properties of the system are related to various physicochemical properties of the donor and acceptor materials and the processing solvents, such as intermolecular interactions, miscibility, and solid state phases (crystallization). [START_REF] Hleli | Improvement of Polymer:Fullerene Bulk Heterojunction Morphology via Temperature and Anti-Solvent Effect[END_REF] The film-drying kinetics are related mostly to the properties of solvents such as boiling point and vapor pressure. [START_REF] Gurney | Morphology and Efficiency Enhancements of PTB7-Th:ITIC Nonfullerene Organic Solar Cells Processed via Solvent Vapor Annealing[END_REF] Currently, the choice of a processing solvent for OPV devices is mainly determined by its capacity to solubilize the organic semiconductors and its boiling point.

Solubility

The solubility properties of the donor and acceptor materials in a processing solvent affect the aggregation and the phase separation in the thin film. The work of Duc T. Duong et al. highlights the relationship between the quality of solvents and the morphology of a BHJ (MDMO-PPV: PC61BM system). [START_REF] Duong | Molecular Solubility and Hansen Solubility Parameters for the Analysis of Phase Separation in Bulk Heterojunctions[END_REF] Figure 3.1 depicts the AFM topography images of MDMO-PPV: PC61BM system, showing that the size of phasedseparated PC61BM domains is dependent on the maximum solubility of PC61BM in the solvent. Large sized aggregates of PC61BM can be found in the active layer when using a poor solubility solvent for PC61BM (such as toluene) to prepare the film. While the PC61BM is dispersed homogeneously and no over-sized aggregates are formed in the BHJ film when it is processed from a good solvent. The solubilities of PC61BM for some common solvents such as chloroform (CF), chlorobenzene (CB), orthodichlorobenzene (o-DCB) are summarized in Table 3.1. Similarly, the study of Camilla Lindqvist et al. on a blend film with different ratios of quinoxaline-based co-polymer (TQ1) and a fullerene acceptor PC71BM illustrates the relationship between solubility limits of PC71BM and the morphology of a BHJ. [START_REF] Lindqvist | Fullerene Aggregation in Thin Films of Polymer Blends for Solar Cell Applications[END_REF] The AFM images (Figure 3.2) show that phase-separated, PC71BM-rich domains become larger when the films are processed from a solvent with a poorer solubility for PC71BM.

In the series of decreasing PC71BM solubility, i.e., CF (34 mg/mL), CB (56 mg/mL), and o-DCB (66 mg/mL), this phenomenon is more pronounced for the 1:3 donor:acceptor blend ratio than for the 1:1 ratio. Thus, the PC71BM solubility significantly affects the aggregation of fullerene derivatives in polymer:fullerene blends. Surface roughness (RMS), as well as the corresponding height sca le, is added to each image. [START_REF] Lindqvist | Fullerene Aggregation in Thin Films of Polymer Blends for Solar Cell Applications[END_REF] Likewise, the donor domains are influenced by the donor solubility limit in the processing solvent. A study by Jie Guo et al. [START_REF] Guo | End Group Tuning in Small Molecule Donors for Non-Fullerene Organic Solar Cells[END_REF] on two new small molecules: BDT-2T-DCV-Me and BDT-2T-CNAB illustrates the dependency between the solubility of donor molecules and the morphology of the active layer. These two small molecules were modified by end groups, dicyanovinyl (DCVMe) and n-butyl cyanoester (CNAB), to increase the charge transport rate. Table 3.2 displays the solubilities of both molecules in CF and the power conversion efficiency of related OPV devices. The AFM images (Figure 3.3) reveal a more homogeneous interpenetrating donor/acceptor network for BDT-2T-DCV-Me: IDIC blend films than for BDT-2T-CNAB: IDIC blend films. The BDT-2T-CNAB:IDIC films do have indeed a rougher surface than BDT-2T-DCV-Me:IDIC films, with RMS values of 0.843 nm and 2.927 nm respectively [START_REF] Duong | Molecular Solubility and Hansen Solubility Parameters for the Analysis of Phase Separation in Bulk Heterojunctions[END_REF] . Note that the solubility of BDT-2T-CNAB (7.9 mg/mL) in CF is higher than that of BDT-2T-DCV-Me (1.7 mg/mL).

The results reported by Jie Guo are thus in contrast with those reported on fullerene acceptors by Ca. Lindqvist, where a higher solubility led to smaller domains. This discrepancy points out the complexity of the processes underlying the morphology of BHJ films, which is influenced by a range of properties other than solubility, and illustrates the difficulty to anticipate the optimum processing conditions. BDT-2T-CNAB CF 7.9 6.17

Boiling Point of Processing Solvents

The organization of donor and acceptor domains are in particular impacted by the drying kinetics. The solvent evaporation and crystallization of the organic materials well as "high vapor" conditions, i.e. using solvent vapor to reduce the evaporation rate.

A more homogenous BHJ film was observed under high vapor conditions, when the rate of solvent evaporation is lower. Similar changes in the morphology of BHJ films occurred when using different processing solvents with different boiling points.

Comparing Figure 3.4 a and d, the films spin-coated from mesitylene (boiling point=166 °C) are flatter and more homogenous than those spin-coated from either toluene or o-xylene with boiling points of 110°C and 138°C respectively.

A similar behavior was also observed in other blends such as P3HT:PC61BM. For example, Yu prepared P3HT:PC61BM OPV devices by using 4 processing solvents (CF, CB, o-DCB, and 1,2,4-trichlorobenzene). [START_REF] Huangzhong | Different Solvents Effect on the Performance of the Solar Cells Based on Poly(3-Hexylthiophene):Methanofullerenes[END_REF] It was observed that P3HT crystallinity is improved when the processing solvent boiling point is increased. This result was ascribed to the fact that a high boiling point solvent provides a low drying speed, offering more time for self-assembly of polymer chains during solvent evaporation.

Thus, P3HT can adopt a low energy state (higher crystallinity) when the films are prepared from a high boiling point solvent. The OPVs achieved a PCE of 3.69% when using 1,2,4-trichlorobenzene compared to 0.94% for CF processed devices. mesitylene under "no vapor" conditions. [START_REF] Nilsson | Morphology and Phase Segregation of Spin-Casted Films of Polyfluorene/PCBM Blends[END_REF] However, the solvents with high boiling points are difficult to remove and can lead to solvent residues after the devices processing. Zhang et al. has reported the study about the relationship between the solvent residues and the performance of devices, indicating that 1,8-diiodooctane (DIO), a solvent additive with a high boiling point (363.3 o C), is difficult to completely remove from the blend films, and results in an unstable state of the acceptor phase even though the films appear dry. [START_REF] Zhang | Efficient Large Area Organic Solar Cells Processed by Blade-Coating With Single-Component Green Solvent[END_REF] DIO residuals allow the acceptor domains to grow further in size, leading to excessively large domain sizes.

Solvent mixtures

Films cast from single solvents often have nonideal morphologies with either insufficient or excessive phase separation between the donor and acceptor materials, and/or disordered domains, resulting in poor device performances. The utilization of cosolvents or additives provide a simple and fast way to optimize the morphology of the active layer.

-Use of additives. This method requires that a processing solvent is introduced in very small proportions (commonly a few volume ~%) into the host solvent. Generally, the additives should have a high boiling point and provide a good solubility for both the donor and the acceptor. Under these conditions, additives can optimize the active layer morphology of various of donor and acceptor BHJs. They may for instance, promote the polymer crystallization after evaporation of the main solvent (the polymer chains have more time to self-organize themselves), and increase the purity of the domains, thereby improving the performance of OPV devices. Common additives include 1,8-diiodooctane (DIO) [START_REF] Sharenko | The Effect of Solvent Additive on the Charge Generation and Photovoltaic Performance of a Solution-Processed Small Molecule: Perylene Diimide Bulk Heterojunction Solar Cell[END_REF][START_REF] Zheng | Binary Solvent Additives Treatment Boosts the Efficiency of PTB7:PCBM Polymer Solar Cells to Over 9.5%[END_REF][START_REF] Zhao | A Universal Halogen-Free Solvent System for Highly Efficient Polymer Solar Cells[END_REF][START_REF] Xu | Thiophene: An Eco-Friendly Solvent for Organic Solar Cells[END_REF][START_REF] Liu | Rational Selection of Solvents and Fine Tuning of Morphologies toward Highly Efficient Polymer Solar Cells Fabricated Using Green Solvents[END_REF][100][101] , 1,8-octanedithiol (OT) 102-105 , 1chloronaphthalene (CN) 106,107 , nitrobenzene (NB) 108 , N-methyl-2-pyrrolidone (NMP) 109 , 1-Methylnaphthalene (1-MN) 110 , and diphenyl ether (DPE) [START_REF] Hong | Morphology Driven by Molecular Structure of Thiazole-Based Polymers for Use in Field-Effect Transistors and Solar Cells[END_REF][START_REF] Zheng | Binary Solvent Additives Treatment Boosts the Efficiency of PTB7:PCBM Polymer Solar Cells to Over 9.5%[END_REF][START_REF] Xu | Thiophene: An Eco-Friendly Solvent for Organic Solar Cells[END_REF]111,112 . Figure 3.5 depicts the chemical structures of some of the processing additives found in the literature. impacts the morphology of a P3HT:PC61BM system. [START_REF] Yao | Effects of Solvent Mixtures on the Nanoscale Phase Separation in Polymer Solar Cells[END_REF] The different boiling points between the processing additive OT (270 o C) and the host solvent o-DCB (178 °C), lead to different evaporation rates. A fast evaporation rate for the host solvent causes an increase in the additive concentration in the solvent mixture during film formation.

The redistribution of PC61BM and P3HT in blend films is due to the residual OT. Due to the presence of OT, PC61BM is finely dispersed between P3HT chains on a molecular basis, leading to the redistribution of PC61BM and P3HT in the blend films, and optimizing the morphology of active layer. Experimental results demonstrate that the PCE of OT-processed OPVs is 5-6 times higher than that of OPVs without additive.

Based on these examples, it is obvious that the use of processing additives represents a widely applicable and effective way to optimize the morphology of a wide range of donor/acceptor systems and, consequently, to improve the performance of organic solar cells. Table 3.3 displays examples of some donor/acceptor systems along with the PCEs with and without processing additives.

-Use of cosolvents. Cosolvents generally constitute a larger proportion of the solvent mixtures, and cosolvents and host solvents have close evaporation rates, e.g.

vapor pressure, melting point, etc. The "new solvent" made from the mixture of cosolvent and host solvent needs to provide high solubility for both donor and acceptor. Since the chlorinated solvents cannot be used for large-area OPV products because of their high toxicity and large environmental impact, nontoxic or less toxic alternative solvents are required for OPV up-scaling. If no single less toxic solvents that lead to an ideal morphology can be identified, the utilization of cosolvents can be an interesting alternative, as it broadens the choice of solvents.

As an example, carbon disulphide (CS2) and acetone were chosen to replace CB for processing PCDTBT: PC71BM blends. A higher solubility of PCDTBT: PC71BM blends was achieved in the solvent mixture by optimizing the CS2 /acetone ratio. 118 CS2 and acetone are mutually miscible and have similar boiling points (46 o C and 56 o C respectively). This close boiling point of both solvents ensures that the solvents in the blend evaporate at a similar rate during the drying process. Besides, the CS2 /acetone mixtures provide a higher solubility for PCDTBT (20 mg/ml) than CB (10 mg/ml). The OPV devices that were processed by CS2/acetone (80:20 by volume) mixtures obtained a comparable PCE of 6.62% to the PCE of devices processed by pure CB (5.52%). The results from Jung et al. suggest that the use of cosolvents represents an efficient approach to optimize the morphology of BHJ films and the OPV fabrication from less toxic processing solvents. 118

Methods for Solvent Selection

There are two main reasons for selecting alternative solvents: to improve the performance of organic materials for OPV (for instance due to a better morphology), and to replace toxic solvents to make OPV module fabrication more environmentally friendly. Currently, most active layers of state-of-the-art OPV systems are still processed with toxic solvents such as CF, CB, and o-DCB at the laboratory scale. It should be noted that the quantity of solvents used during processing increases dramatically with large-scale production, making environmental damage and impact on human health critical issues. Also, toxic solvents are expensive and energy-intensive to remove as waste. Therefore, the usage of toxic solvents to process both well-known and new organic materials is a major bottleneck for the development of the OPV industry. It is thus urgent to develop "greener" alternative solvents to process efficient OPV devices. Many efforts have already been made for a safe, eco-friendly and economical OPV fabrication and were based on two methodologies: a trial and error approach and the Hansen solubility parameters theory (HSPs).

Trial and Error Approach

The trial and error approach is a basic experimental problem-solving method built on practical experiments. For a conventional (generally toxic) solvent to be replaced, one or several alternative solvents are empirically selected and tested. If these candidates do not match the requirements, they are removed from the candidate list and others are proposed and tested, until achieving the target properties. The efficacy of the alternative solvent generally takes into account application-relevant properties, such as solubility power, toxicity and energy consumption. For determining the final choice, a compromise between different selection criteria is often ineluctable. This method is widely used in the OPV field for the selection of alternative solvents and processing additives. For instance, Liao et al. added ethylenedioxythiophene (EDOT) side chains to the benzo [1,2-b:4,5-b']dithiophene (BDT) donor units to improve the solubility of the PTB7 donor material in nonhalogenated solvents. 106 Yet, the final halogen-free solvent 2-methyltetrahydrofuran (MeTHF) that was used to prepare the OPV devices and led to a maximum PCE of 10.18%, was selected by a trial and error method. Another recent example is 2-methyl anisole (2-MA) which has been considered as alternative solvent in many studies, because of its low toxicity and widespread use as food additive. [START_REF] Zhang | Efficient Large Area Organic Solar Cells Processed by Blade-Coating With Single-Component Green Solvent[END_REF] 2-MA was selected by a trial and error method to replace the toxic halogenated solvent CB and processing additive DIO during the device manufacturing. Highly efficient PTB7: PC71BM-based OPV devices with a highest PCE of 9.6%. were prepared with 2-MA. Table 3.4 represents some examples of alternative solvents for different donor/acceptor systems.

Hansen Solubility Parameters Theory (HSPs)

As noted in section 3.2, processing solvents and additives can improve the morphology of BHJ by modifying the miscibility between solvents and photovoltaic materials. The solubility of photovoltaic materials in various solvents can be predicted by the Hansen solubility parameters methodology (HSPs). Hildebrand and Scott were first to propose the term solubility parameter. The Hildebrand solubility parameter is defined as the square root of the cohesive energy density ( 𝐸 𝐶 ) (or energy of evaporation per unit volume) over the molar volume of the pure solution:

𝛿 = √( 𝐸 𝐶 𝑉 ) (5)
Hansen extended this preliminary work by proposing the so-called Hansen solubility theory that decomposes the cohesive energy into three major types of intermolecular interactions 125 , namely: (1) dispersion interactions 𝐸 𝐷 , (2) permanent dipole molecular interactions 𝐸 𝑃 , and (3) hydrogen binding interactions 𝐸 𝐻 . The total cohesive energy and solubility parameter are then given by:

𝐸 𝐶 = 𝐸 𝐷 + 𝐸 𝑃 + 𝐸 𝐻 (6) 𝛿 = √(𝛿 𝐷 ) 2 + (𝛿 𝑃 ) 2 + (𝛿 𝐻 ) 2 (7)
where 𝛿 𝐷 = √( and that of a solute (𝛿 𝐷2 , 𝛿 𝑃2 , and 𝛿 𝐻2 ) in the Hansen space. The distance 𝑅 𝑎 is defined by the following equation:

𝑅 𝑎 = √4(𝛿 𝐷1 -𝛿 𝐷2 ) 2 + (𝛿 𝑃1 -𝛿 𝑃2 ) 2 + (𝛿 𝐻1 -𝛿 𝐻2 ) 2 (8)
Furthermore, a solubility "boundary" for a solute is required to define and differentiate "good solvents" from "bad solvents". This has led to the concept of the Hansen solubility sphere, which is defined by a center position whose coordinates are the HSPs of the solute and by a radius (𝑅 0 ). 𝑅 0 corresponds to the largest distance (equation ( 9)) between a solute and miscible solvents and can be determined by solubility experiments. 126 In other words, a solute is insoluble in a given solvent if 𝑅 𝑎 between the solute and solvent is larger than the 𝑅 0 of the solute. The affinity between both molecules increases with decreasing 𝑅 𝑎 and is described by the relative energy difference (𝑅𝐸𝐷), with:

𝑅𝐸𝐷 = 𝑅 𝑎 𝑅 0 (9)
A 𝑅𝐸𝐷 less than 1 implies that the solvent HSPs are inside the Hansen solubility sphere of the solute and can be considered as a good solvent. Note that the Hansen Up to now, the IBSS®CAMD method has not yet been used to search for alternative solvents for the processing of organic semiconductors. Yet, the successful implementations of IBSS®CAMD mentioned above suggest that it has a promising perspective for solving the toxic solvent issue for solution-processed organic devices such as OPVs, but also organic light-emitting diodes (OLEDs), organic solid-state fieldeffect transistors (OFETs), or organic photodiodes. [START_REF] Zheng | Green Solvent Processed Tetramethyl-Substituted Aluminum Phthalocyanine Thin Films as Anode Buffer Layers in Organic Light-Emitting Diodes[END_REF][START_REF] Wang | Flexible RFID Tag Metal Antenna on Paper-Based Substrate by Inkjet Printing Technology[END_REF][START_REF] Hong | Morphology Driven by Molecular Structure of Thiazole-Based Polymers for Use in Field-Effect Transistors and Solar Cells[END_REF] In this thesis, this tool is introduced for the first time to select alternative solvents for polymer/fullerene and polymer/non-fullerene based OPV devices. A more detailed description of IBSS®CAMD is given in the following chapter. IBSS®CAMD has also been applied to generate ricinoleic acid derivatives aiming to find new biolubricants from a biomass feedstock. 133 Since the efficiency of a pure solvent can be improved thanks to the thermodynamic synergism of forming binary or multicomponent mixtures, special attention has also been devoted to the use of azeotropic mixtures that behave as a pure compound at a given composition and pressure. For instance, new coolant azeotropic mixtures for heat-exchange devices in aerospace applications have been recently identified by using IBSS®CAMD tool 134 .

IBSS®CAMD Tool

Therefore, IBSS®CAMD is considered to be an effective tool for alternative solvent selection in different fields. This tool is described in detail in this chapter.

Fundamental Principles of IBSS®CAMD

Up to now, the selection of new molecules as alternative solvents for OPV has mostly been the result of a time-consuming trial-and-error approach. Searching for new solvents is indeed a complex problem that requires taking into account multiple properties, such as Hansen solubility parameters, boiling temperature, toxicity ..., while most of these may impact the device performance in a rather unpredictable way.

In order to cope with the challenging complexity of the problem, it is therefore highly desirable to replace the conventional "trial and error" approach by more efficient methods, capable to take into account multiple functional, economic, health, safety and lifecycle constraints simultaneously.

IBSS®CAMD can generate molecular structures "from scratch" by starting from a fixed number of chemical groups, including for instance biobased building blocks. The final solution is constrained by the nature of the selected chemical groups and their maximal number in the molecules to be constructed. A molecular structure is appropriate to replace a hazardous solvent if the corresponding physicochemical properties are within specifications. This "appropriateness" is quantified by defining Two different methods to predict the properties of alternative solvents can be applied: the database approach and the group contribution-based approach. The database approach is achieved by using existing databases of physicochemical properties of given molecules. The group contribution-based approach decomposes molecules into chemical fragments for which property databases are available and estimates the molecular properties by a linear combination of the fragment properties (see below). The molecules are evaluated by the group contribution methods (see below) and then identified so that only the best molecules are retained. In addition, IBSS®CAMD is based on four major concepts: (1) property calculation models, (2) performance criteria, (3) molecular representation model and ( 4) resolution method.

Property calculation models

A list of property calculation models can be used in IBSS®CAMD to calculate the property values of alternative solvents. The accuracy of the selected calculation techniques must be sufficient to get a meaningful final list of candidates. The property calculation models must be distinguished between a pure compound model and a mixture model.

Pure compound property estimation model

For a pure component, the user retrieves the required property models from the property package library available in CAMD tools. They should be able to compute properties for a wide diversity of chemical structures by applying group contribution models or quantitative structure activity/propriety relationship (QSAR/QSPR). 138,139 Group contribution models are widely used for alternative solvents design due to their simplicity and availability in CAMD tools. 140,141 In principle, the properties of a compound are calculated from the contributions of three types of chemical groups: first order groups, second order groups and third order groups. The first order groups are the basic ones such as -CH3, -OH, =O, -NH2, etc., and intended to describe a wide variety of organic compounds. The second and third order groups use the connectivity between basic groups in order to distinguish between isomers and to describe the proximity effects in a molecule arising from polyfunctionality. However, the second order groups are inadequate to provide an exact representation of compounds when the latter include more than one ring, or in some cases, open-chain polyfunctional compounds with more than four carbon atoms in the main chain. Thus, a further level (third order groups) is required to describe the more complex chemical structures, such as systems of fused aromatic rings, systems of fused aromatic and nonaromatic rings, etc. For the group contribution approach, a large database is required, which reports the physicochemical properties of functional groups. Any physicochemical property, P, such as phase transition temperature, viscosity, heat capacity, etc. of full molecules can then be estimated by the following general form: (10) where G1, G2 and G3 are the sets of first, second and third order groups respectively, Ak is the contribution of the first order group k to the property P that occurs n1k times in the molecule, Bk is the contribution of the second order group k that occurs n2k times and Ck is the contribution of the third order group k that occurs n3k times. For some properties, an additional adjustable model parameter (or universal constant) is used (see chapter 5).

𝑃 = ∑ 𝑛 1𝑘 𝐴 𝑘 + 𝑤 ∑ 𝑛 2𝑘 𝐵 𝑘 𝑘∈𝐺2 + 𝑧 ∑ 𝑛 3𝑘 𝐶 𝑘 𝑘∈𝐺3 𝑘∈𝐺1
For most properties, the Ak, Bk and Ck coefficients have been regressed from experimental data obtained over a large range of chemical families. 142 The series of First order group:

X (C-NH2) + X (C-NH) + X (C) + 9*X (CH)
1 Second order group 1 Third order group

For simple molecules, the property P can be estimated by using only the first term with Ak values, which are known for all first order groups that are relevant to organic molecules. For more complex structures, Bk and Ck coefficients can improve the accuracy of the estimates, provided that they are available in the CAMD database. The w and z coefficients in equation ( 10) will be set to 1 or 0 depending on the availability of Bk and Ck in the CAMD database.

Mixture property estimation model

The estimation of the properties of organic mixtures is based on the calculation of the pure compound property. Within IBSS®CAMD, a linear dependency model is used.

Taking the molecular mass as an example: (11) where z is a molar fraction.

The accuracy of the linear dependency model is limited and may result in a poor quality estimations as a consequence of nonlinear property dependencies. However, in the case of mixtures that include a minor component (or additive), the linear approximation is expected to yield meaningful results. Appendix 9.1 presents a list of properties that are included in IBSS®CAMD and their associated default calculation models.

Performance criteria

The tailor-made molecular design problem is inherently multi-objective since several physicochemical properties (section 4.2.3) must be satisfied at the same time for each molecular structure. Different molecular structures (MS) are ranked according to a GloPerf parameter that represents a weighted average performance. 143 GloPerf is

𝑃 𝑚𝑖𝑥𝑡𝑢𝑟𝑒 = ∑ 𝑧 𝑖 𝑃 𝑖 𝑛𝑐 𝑖=1
itself formulated as the average of m individual performance factors 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 (𝑀𝑆, 𝑐𝑜𝑛𝑑𝑗) each related to a single property prediction model, as shown in equation ( 12):

𝐺𝑙𝑜𝑃𝑒𝑟𝑓(𝑀𝑆, 𝑐𝑜𝑛𝑑 𝑗 ) = ∑ 𝑤 𝑝 * 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 (𝑥(𝑀𝑆,𝑐𝑜𝑛𝑑 𝑗 )) 𝑚 𝑝=1 ∑ 𝑤 𝑝 𝑚 𝑝=1 (12)
where 𝑤 𝑝 are weighting factors that are selected by the user based on its knowledge of the property significance for the targeted application. GloPerf equals unity in the ideal case, where all target properties are matched and all ProPerfp factors are equal to one.

The ProPerfp factor corresponding to a given property 𝑃 compares the property value 𝑥, predicted by the selected methods (section 4.2.2), with the targeted value 𝑉.

The ProPerfp factors depend obviously on the molecular structures MS and can also be a function of j specific "conditions" (𝑐𝑜𝑛𝑑 𝑗 ) set by the user, such as for instance the temperature and/or pressure under which the experimental process is to be performed.

The ProPerfp factors are calculated by using a Gaussian-type distance function defined by equation 13:

𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑃 (𝑥 (𝑀𝑆, 𝑐𝑜𝑛𝑑 𝑗 )) = exp [-( 𝑉-𝑥(𝑀𝑆,𝑐𝑜𝑛𝑑 𝑗 ) 𝜎 ) 2 ] (13)
where parameter 𝜎 is used to define a "tolerance" margin around a given target value V. ProPerfp takes the value 1 if the estimated value x meets the target value 𝑉 for P. The 𝜎 parameter determines the rate at which ProPerfp decreases when x deviates from 𝑉.

Three types of Gaussian function were defined based on the property constraints, as shown in

Resolution method

To solve the combinatorial problem of the design of molecules with target properties, meta-heuristic research methods are used by IBSS®CAMD. They consist of iterative improvement of candidate molecules or "solutions". In IBSS®CAMD, they are based on the probabilistic evolution of the solution and can therefore be called random or stochastic search methods.

The most frequently used algorithm in IBSS®CAMD is the genetic algorithm. At first, the genetic algorithm explores the solution space using the principle of natural selection and the laws elaborated by Darwin. Holland (1975) has introduced the fundamentals of this algorithm. 144 The population n is evaluated using a performancebiased method and the best solution in the population is modified randomly by genetic operators such as "crossover" and "mutation" to create population n+1. Population The basic functional group coding proposed by Korichi et al. (2008) 148 , is defined as diagonal atomic codes:

𝐸𝐺 = 𝑃1𝑃2𝑃3𝑃4. ( 14
)
where P1 presents the atomic number, preceded with a 1 (106 for C, 107 for N, 108 for O, 117 for Cl…).

P2 expressed the highest bond order on the atom (ex. 1 for « -C-», 2 for « -N= », 3 for « -C≡ » and a special case 4 for =C=). P4 is the number of implicit hydrogens.

Examples of the available basic groups and their encoding is shown in Table 4.2.

More available basic groups and their encoding can be found in Appendix 9.2.

Atom

Reverse Engineering Method for Alternative Solvents Design

The methodology to design alternative solvents involves five essential steps as displayed in Figure 4.6 and described in the following.

Definition of the Initial Problem

A list of functionalities has to be set taking into account the properties of the solvents to be substituted

Translation of functionalities into physicochemical properties and definition of target values

This step is commonly done by using knowledge-based analysis. For instance,

Hansen parameters are a good indicator for the capability of a solvent to dissolve a given molecule. A Newtonian fluid is related to its viscosity. A liquid solvent requires a low melting temperature, while low energy consumption can be associated with a low boiling temperature and vaporization enthalpy.

Target values for physicochemical properties can be defined in two different ways.

In the case a property needs to reach a well-defined value that is already achieved with the initial solvent to be replaced, for instance a given surface tension, the target value is set to the corresponding experimental value of the initial solvent. Otherwise, the target values may differ from those of the initial solvent, if the related properties can be improved by the alternative solvent. For instance, a safer solvent implies to seek a higher flash point.

Step 2 is commonly done by using knowledge-based analysis. For instance,

Hansen parameters are a good indicator for the capability of a solvent to dissolve a given molecule. A Newtonian fluid is related to its viscosity. A liquid solvent requires a low melting temperature, while low energy consumption can be associated with a low boiling temperature and vaporization enthalpy.

Molecular design parameters

The steps 3 (Selection of the predictive models of the physicochemical properties) and 4 (Definition of the global performance function) have been described above (section 4.1.1 and 4.1.2, respectively).

IBSS®CAMD can be us in two different ways: (1) to evaluate only the performance of a given pre-selected list of existing solvents, or (2) to design new molecules and evaluate their performances, so as to rank them. Both modes have been used in this thesis.

Step 5 (molecular design) is for mode (2) only.

When using the first mode, a list of SMILES (simplified molecular input line entry specification) codes of existing solvents must be entered and is used by IBSS®CAMD to evaluate the solvents performances.

In the molecular design mode, thousands of molecular structures are methodically generated by IBSS®CAMD and the GloPerf value is calculated for each of them. The tailor-made molecular design problem is a multi-objective optimization problem because several properties must be satisfied simultaneously. A genetic algorithm optimization method is implemented in IBSS®CAMD that allows the molecular structures to be modified in order to improve the GloPerf closer to one. In other words, the maximum GloPerf value is obtained by numerically resolving the objective function i.

Mutation operator

The mutation operator is a classic genetic operator and is not limited to CAMD. In CAMD, the mutation is used when the replacement of a single group by a group with the same connections occurs in a molecule, e.g. >CH2 by >O (see Figure 4.8).

The group is changed randomly. ii.

Crossover operator

The crossover involves two molecules. A non-cyclic fragment with the same bond type (single, double or triple bond) is randomly chosen in two molecular graph matrices thereby creating four semi-graphs. An example is shown in Figure 4.9.

The red dashed lines show the positions of the cut in both molecules. The fragments are switched and recombined to form two new molecules. The recombined bonds are symbolized by solid red lines. iii.

Insertion operator

This operator involves the addition of a group into a molecular structure. In general, the inserted group has more than two connections, which makes it possible to complete the molecular structure with some branches. An example is reported in iv.

Deletion operator

The deletion operator is used to remove a group form a given molecular structure

(

v. Substitution operator

This operator is typically adopted to modify aromatic rings, which cannot be done by the previous operators. It combines the principles of mutation and insertion, which includes the replacement of a group with a group that has more connections. In Figure 4.12, the -CH= group is replaced by a more complex fragment (orange in colour). Both groups are selected at random and the same method as insertion is used to complete the new connections.

Candidate ranking and final choice

While the IBSS®CAMD results allow the ranking of the solvent candidates according to their 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 values, a final selection by the user is often still required to take into account properties that are out-of-reach to IBSS®CAMD. For instance, the final toxicity levels for the selected solvents are not provided by IBSS®CAMD. Neither do the results allow to evaluate the complexity and related costs for the synthesis of the new solvents. Also, experimental values are needed to confirm the actual performance of each candidate.

Conclusion

The IBSS®CAMD tool presented in this chapter has several features that makes it particularly well suited for many applications.

1) the target properties can be freely chosen in view of the target application.

2) the relative importance of each target property can be adjusted by weight factors to take into account their possible impact on the solvent desired functionality

3) the Gaussian performance functions can be selected in accordance with the actual application.

4) the tolerance margins counterweigh to some extent the uncertainty of the property estimation methods.

Due to these advantages, the IBSS®CAMD can be seen as an efficient tool for the solvent selection and new solvent design in the organic photovoltaic field. In the following chapter, we will describe the case study of selecting alternative solvents for the elaboration of OPV devices. devices. 127,151,152 We have therefore chosen P3HT:EH-IDTBR as a second example to illustrate how IBSS®CAMD applies to different materials and paves the way towards a more versatile and efficient approach for identifying alternative solvents.

As we discussed in Chapter 3, the morphology of the organic layer is usually the result of a phase separation between both organic constituents that occurs during processing of the film from solution. 114,153 Pure domains are essential for exciton generation and charge carrier transport, while exciton dissociation into free charge carriers occurs at the interface between donor and acceptor domains. [153][154][155] The morphology of the active layer at the nanoscale is therefore a key factor underlying the performance of BHJ OPV devices. Although many studies have highlighted the existing correlations between various solvent properties and blend morphology, it is not yet possible to fully anticipate the solvent properties that are best suited to process a given blend to its optimum. [START_REF] Shaheen | 2.5% Efficient Organic Plastic Solar Cells[END_REF][START_REF] Zheng | Green Solvent Processed Tetramethyl-Substituted Aluminum Phthalocyanine Thin Films as Anode Buffer Layers in Organic Light-Emitting Diodes[END_REF][START_REF] Duong | Molecular Solubility and Hansen Solubility Parameters for the Analysis of Phase Separation in Bulk Heterojunctions[END_REF]156 Extensive optimization of the blend composition and processing conditions is therefore still required to achieve the highest power conversion efficiency with a given donor/acceptor system. It should be noted that in many cases solvent additives have been necessary to reach maximum efficiency.

In the following, we will first present the multiple steps that need to be considered when applying IBSS®CAMD to the identification of alternative solvents for OPV. Next, the method is applied to P3HT:PC71BM and P3HT:EH-IDTBR blends to identify new biosolvents for the fabrication of OPV devices. Finally, the photovoltaic performances of devices processed from these solvents are compared to those obtained from halogenated solutions.

Defining the Conditions to Apply IBSS®CAMD to OPV

In the following, we apply the IBSS®CAMD tool described in Chapter 4 to both blends. Six steps are required for IBSS®CAMD to search alternative solvents (see section 4.2).

Initial problem definition: Functionalities of existing solvent

For the solution-processed BHJ OPV devices, the active layer is processed from a solution containing both donor and acceptor materials. It is thus essential that the alternative solvents provide good solubility with respect to both organic materials. The morphology of the active layer is strongly dependent on the kinetics of the filmforming and drying processes and needs to match closely the configuration that leads to a maximum PCE. In addition, the alternative solvents should be Newtonian fluids, so that the active layer can be formed by a standard printing process. Keeping solvents in the liquid state at room temperature is also a prerequisite to elaborate thin films and reduce the difficulty and energy consumption during the process. Furthermore, the safety of solvents is obviously an important "functionality".

Translation of functionalities into physicochemical properties and definition of target values

The physicochemical properties and the corresponding target values are defined so as to achieve the functionalities set above. In some cases, several properties are associated with one functionality, for instance, surface tension and boiling point both have an effect on film drying. It is noted that the IBSS®CAMD tool is a computer-based prediction method, therefore the reliability and limitations of these property prediction models can directly affect the final results. For example, the boiling point is easily predicted and the predictions match the experimental results. However, surface tension predictions were poorly matched to experimental results. The match between the predicted and experimental values of several properties has been illustrated in Figure 5.2. For required properties that have less accurate predictive models, such as melting point, a low wp value reduces the impact on the final results. The miscibility between alternative solvents and organic materials can be predicted by the Hansen solubility parameter theory (HSPs). Within this theoretical framework, the cohesive energy is divided into three intermolecular interactions which are: the dispersion interactions (δD), the permanent dipole molecular interactions (δP), and the hydrogen bonding type interactions (δH). 125 The miscibility between a solvent and a solute can be estimated by the relative energy difference (RED) in the Hansen space (see Chapter 3). Following the classical rule "like dissolves like", the affinity between a solvent and a solute increase with decreasing RED. A RED value below 1 indicates that the material is miscible to some extent. The lower the RED value the higher the solubility limit. In addition, Ra is the "effective distance" between solvent and solute coordinates in Hansen space. A smaller Ra means a higher affinity between the solvent and the solute.

The kinetics of film-drying primarily depend on the boiling point and vaporization enthalpy of the solvents during film printing. The boiling point is known to impact the polymer crystallinity (in case of a semi-crystalline polymer such as P3HT) and the donor/acceptor average domain sizes. [START_REF] Nilsson | Morphology and Phase Segregation of Spin-Casted Films of Polyfluorene/PCBM Blends[END_REF]157 These parameters are therefore critical for the final device performance.

The Newtonian fluid behavior is related to moderate viscosity and density of solvents, two parameters that have to be taken into account for achieving high quality films (optimized thickness, homogeneity). A solvent that remains in the liquid state at room temperature needs to have a low melting point. Finally, the flash point, which determines the flammability of solvents and therefore the risks for explosion during the devices processing, should also be considered.

Based on the above, we have selected 11 target properties to be used by IBSS®CAMD to evaluate the performance of alternative solvents, as summarized in Table 5.1.

For each property the target values can in principle be defined following two approaches based either on preliminary experimental measurements or on reference solvents. We followed the first approach to specify the target solubility properties. The alternative solvents need to solubilize both the donor and acceptor molecules, i.e. in our case P3HT and PC71BM or EH-IDTBR. Therefore, the HSPs of P3HT, PC71BM and EH-IDTBR have been determined experimentally.

Firstly, the solubility of a solute is tested in a list of solvents. The solvents are ranked into 1 ("good" solvents), 0 ("bad" solvents) and 2 (between "good" and "bad" solvents), depending on their capacity to solubilize the solute. The software HSPiP uses the scores to build a solubility sphere which separates good and bad solvents. The center of the HSP solubility sphere yields the HSP parameters of the solute. The radius of the sphere, R0, defines the region in HSP space corresponding to the solvents that are able to solubilize the solute. The larger Ro the more easily soluble is the solute. In this work, a series of solutions were prepared with a solute concentration of 2 mg/ml. Mostly common solvents, already available in the lab, were used for the HSP measurements. The prepared solutions were annealed at 40 o C overnight. The Hansen parameters of EH-IDTBR were found to be δD=18.8 ± 0.3, δP=4.4 ± 0.75, δH=4.3 ± 0.80, and R0 was found to be 6.1. The error margins correspond to the standard deviation of the mean values.

The solubility experiments of P3HT were done by Dr. Markus Kohlstädt at the Albert Ludwigs Universität Freiburg. The HSPs of P3HT were estimated to δD=18. 5, δP=4.7, δH=5.0, and R0=4.7. The HSPs of PC71BM have been reported in literature and are given by δD=20. 2, δP=5.4, δH=4.5, R0=8.4. 113 The positions of P3HT/PC71BM and P3HT/EH-IDTBR in Hansen space are shown in Figure 5.3a and 5.3b, respectively. For P3HT:PC71BM blends, the overlap between Hansen spheres (or Hansen junction) of both molecules defines the HSP space for solvents that solubilize both molecules. The Hansen junction "barycenter", which defines the coordinates of the solvent that should interact most efficiently with both materials, can be estimated by the HSPiP software 158 . For P3HT:PC71BM, the junction barycenter values are 19.1, 5.0, 4.8 for δD, δP and δH, respectively. Therefore, the HSP target ranges for P3HT:PC71BM blends are chosen as 18< δD < 20, 4< δP < 6, and 3.5 < δH< 6, respectively. Note that the inequalities for the HSP target values given above are not enough to warrant a good solubility for both materials in the selected solvent. It is indeed necessary that the solvent HSPs also lead to RED < 1 for each compound. In our case, the rather high solubility radius R0 of PC71BM leads the Hansen solubility spheres of P3HT to be located fully inside of the solubility sphere of PC71BM (Figure 5.2a). Therefore, an alternative solvent for which RED < 1 for P3HT will necessarily be miscible with PC71BM as well. The junction values of P3HT:EH-IDTBR are 18.6, 4.5, 4.8 for δD, δP and δH, therefore the target ranges of HSPs are set to 17.5< δD < 19.5, 3.5< δP < 5.5, and 3.5 < δH < 6, respectively. The position of P3HT and EH-IDTBR in the HSP solubility space can be found in Figure 5.2b. Again, the solubility spheres of P3HT and EH-IDTBR fully overlap, so that the solubility requirement can be satisfied with RED <1 for P3HT only.

For the solvent not to be classified as dangerous according to flammable and combustible liquid hazard classifications (National Fire Protection Association, NFPA) 159 , its flash point needs to be larger than 296.15K. Similarly, a melting point lower than 283.15K is requested to keep the solvents in its liquid state at the processing temperature.

For the properties Ra, boiling point, ∆Hvap, density, and viscosity, the target values have been defined by using the second approach mentioned above, i.e. using the key properties of a "reference" solvent that is known to yield high-performance OPV devices. For the investigated materials, o-DCB is a good choice as it dissolves efficiently P3HT and has led to the highest power conversion efficiencies with the P3HT:PC70BM blends. For the P3HT:EH-IDTBR system, CB is considered to be the best "reference" solvent for the OPV field. The experimental database of the target properties for o-DCB and CB are summarized in Table 5 As shown in table 5.2, the experimental values for the boiling point, vaporization enthalpy, density, and viscosity are relatively close for both reference solvents.

Therefore, same target ranges for a given target property were chosen identical for both systems. More precisely, for the boiling point the target range for the alternative solvent is set to [373 K, 473 K] 151,160 , while for the vaporization enthalpy, density, and viscosity, the target ranges are [35 kJ/mol, 55 kJ/mol], [0.8 g/cm 3 , 1.5 g/cm 3 ], and [0.5 mPa/s, 1.5 mPa/s] respectively. All the target values are summarized in Table 5.1.

Selection of the predictive models

As mentioned above, the group contribution method is used in IBSS®CAMD to predict the solvent properties. The value of a given property, P, can be calculated using a property-estimation model and additional adjustable model parameters which depend on the property involved. The property-estimation model is based on the group contribution method and has the form of equation (10). The universal constants for each individual property were determined by a regression scheme that can be found in Table 5.3.

The density, ρ, of a given molecule is calculated using equation (16).

𝜌 = 𝑀 𝑊 𝑉 𝑚 = 𝑀 𝑊 𝑉 𝑚 (𝑃) ( 16
)
where MW is the molecular weight and Vm the molecular volume. The molecular volume is calculated based on the group contribution method from equation ( 17) The universal constant for the molecular volume, Vm0 , is summarized in

Definition of the global performance function

Table 5.1 displays the functionalities and the associated target properties for alternative solvents together with the chosen 𝜎 and 𝑤 𝑝 parameters. The 𝜎 values are set by considering the uncertainty on the selected target values and the estimated tolerance margin on the corresponding property. The 𝑤 𝑝 values are chosen by pondering the possible influence of the property on the performances of the devices, as indicated in table 1. For instance, the solvent evaporation rate, which depends on both the boiling point and ∆Hvap, influences the amount of residual solvents in deposited films as well as the degree of phase separation between donor and acceptor molecules during the film processing. We therefore set 𝑤 𝑝 to 2 and 1 for the boiling point and ∆Hvap respectively, i.e., a cumulative weight of 3 on the solvent evaporation kinetics.

Molecular design parameters

As mentioned above, IBSS®CAMD tool can be used in two different modes: to evaluate the performances of existing solvents with respect to target properties or to design new molecules and optimize their structure to fit the target properties. We have used the first mode for both P3HT:PC71BM and P3HT:EH-IDTBR blends, and the second mode for P3HT:PC71BM only.

Existing solvents performance evaluation: 139 biosolvents 164 were selected as target solvents (see appendix 9. During the molecular design mode, thousands of molecular structures are generated and their performance evaluated using IBSS®CAMD, ending up with a list of 10102 candidate solvents.

Candidate ranking and final choice

Selection from the list of existing solvents. For P3HT:PC71BM and P3HT:EH-IDTBR blends, nine evaluated candidate solvents achieved a 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 > 0.6 and are reported in Table 5. -BBzo is removed because its boiling point, ΔHvap and viscosity lead to a 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑃 ≈ 0, their estimated values being far above the target, and may hinder film formation and drying. [START_REF] Zhang | Efficient Large Area Organic Solar Cells Processed by Blade-Coating With Single-Component Green Solvent[END_REF] -CPME should be removed due to its low flash point (280 K) in order to avoid safety problems during usage and storage. Also, the low ΔHvap of CPME (37 kJ/mol) should give rise to rapid evaporation and result in insufficient phase separation between donor and acceptor materials and low P3HT crystallinity. [START_REF] Nilsson | Morphology and Phase Segregation of Spin-Casted Films of Polyfluorene/PCBM Blends[END_REF] Importantly, today the commercial CPME is currently produced from fossil resources although it could be bio-based. 165 -Similarly, THF is not retained because of its low boiling point (338 K). The RED of P3HT in THF is 0.728 under a concentration of 2 mg/ml, while a concentration of 10 mg/ml for P3HT is needed for OPV devices processing. A high processing temperature can improve the solubility of P3HT in a solvent, but the low boiling point of THF limits this. In addition, commercial THF is also currently Petro-sourced.

-IA and BA are omitted because their REDs are larger than 1 for P3HT

(𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 (𝑅𝐸𝐷) ≈ 0).

For the remaining candidate solvents AN shows the best performance with the 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 values of 0.997 and 0.946 for P3HT:PC71BM and P3HT:EH-IDTBR respectively.

Only the 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 value for 𝛿 𝐻 is slightly off the target value 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 = 0.957).

PX shows high 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 values of 0.853 for P3HT:PC71BM and 0.861 for P3HT:EH-IDTBR, however, the low 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 values of 𝛿 𝐻 (≈ 0) and 𝑅 𝑎 (0.66) for both blends, indicating that PX is a poorer solvent for P3HT than o-DCB. Yet, the RED of PX is 0,75 (<1), showing that PX can still dissolve P3HT, PC71BM and EH-IDTBR.

Compared to An and PX, PC, TPO and LM have lower 𝐺𝑙𝑜𝑃𝑒𝑟𝑓, meaning that more properties show a poor match with the corresponding target properties (Appendix 9.5, 9.6). For example, the ProPerfp of ΔHvap of 0.34 for TPO may impact the film drying kinetics of the active layer. In addition, these three solvents have a low 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 value for 𝑅 𝑎 due to the poor match of their HSPs' properties with the corresponding target properties (Appendix 9.5, 9.6). But their RED values are still lower than 1, indicating that P3HT can be dissolved in these three solvents despite the poorer solubility than that in AN.

We finally retained AN, PX, TPO, PC and LM for both blends and investigated the device performances that could be achieved using these solvents as alternative to o-DCB. property that is associated with the active layer treatment method and device stability and needs to be taken into account. for processing OPV devices. Since AN has already been selected from the list of existing candidates (Table 5.4), we have limited our device investigations to blends that were processed from the commercially available 4-ET and 2-MA.

Photovoltaic Performance

To evaluate the quality of the alternative solvents identified by IBSS®CAMD, we have elaborated OPV devices using each of the previously selected biosolvents.

Reference devices processed from o-DCB and CB solutions were also investigated. An inverted OPV structure is adopted in this thesis. It includes ITO as transparent electrode, ZnO as electron transporting layer, MoO3 as hole transporting layer and Ag as top electrode. The active layer was composed of either P3HT:PC71BM or P3HT:EH-IDTBR blends with a 1:0.7 weight ratio. The solutions were annealed and stirred overnight at various processing temperatures in nitrogen ambient (see Table 5.7). A slightly higher processing temperature was adopted for the poorer solvents PC, TPO and LM. The thin films were elaborated by spin-coating onto substrates previously heated at the same temperature. After deposition, the films were further annealed at 135 o C for 10 min, under an inert atmosphere to improve the polymer crystallinity.

The electrical properties of the devices under darkness and under illumination are recorded in Figure 5.3 and Table 5.7. In the case of P3HT:PC71BM blends, the performances of devices processed from pure 4-ET, AN, PX, PC, TPO and LM solutions were much lower than those of the reference device (see Figure 5.3). This brought us to add 3% of the non-halogenated diphenyl ether (DPE) as processing additive to these solvents. It is indeed widely known that DPE can dramatically improve the OPV performances by optimizing the morphology of the active layer. [START_REF] Zhao | A Universal Halogen-Free Solvent System for Highly Efficient Polymer Solar Cells[END_REF][START_REF] Liu | Rational Selection of Solvents and Fine Tuning of Morphologies toward Highly Efficient Polymer Solar Cells Fabricated Using Green Solvents[END_REF] It is generally believed that adding DPE enhances the solubility of PC71BM and retards the formation of PC71BM aggregates. Finally, the devices processed from each of the 6 selected alternative biosolvents could achieve comparable performances to those processed from o-DCB. Note that the processing conditions were kept identical to the reference solvent, except for the eventual introduction of DPE as solvent additive and the slight change in processing temperature for PC, TPO and LM. Interestingly, no additive was needed for devices processed from pure 2-MA. This behavior correlates with the higher solubility of PC71BM in 2-MA in comparison to the other alternative solvents. Also, its relatively high boiling point (443 K) should enhance the phase separation between donor and acceptor materials, presumably leading to domains of higher purity. In fact, the slight differences in performances between biosolvents may be attributed to the absence of full optimization of the deposition parameters. The latter would require additional experimental variables such as spin-coating parameters, solution concentration, processing temperature… to be optimized. Using TPO and LM as alternative solvent led to significantly lower performance, even after the introduction of DPE. This is in good agreement with the lower GloPerf factors of TPO and LM and suggests that solvents with still lower GloPerf values are no more appropriate to process P3HT:PC71BM into efficient devices. The JV curves of P3HT:EH-IDTBR devices and the extracted physical parameters are depicted in Figure 5.4 and Table 5.8. Similar photovoltaic performances could again be achieved with all the selected solvents. Also in this case, the solvent-to-solvent variations may be attributed to the incomplete optimization of the processing conditions. The highest PCE value, observed for AN-based devices, results mostly from the higher fill factor and photocurrent, which in turn may be the outcome of purer domains, and therefore less recombination. However, clarifying the origin of the performance fluctuations would need more in-depth investigations that lie beyond the scope of this thesis. It is nevertheless noteworthy that no processing additive was needed to achieve efficient P3HT:EH-IDTBR based devices for none of the solvents, in contrast with the behavior of P3HT:PC71BM devices. We attribute this difference to the smaller Ra and RED values estimated for EH-IDTBR for each solvent (Table 5.9), indicating that the solubility of EH-IDTBR is higher than that of PC71BM in the corresponding solvents. In other words, a higher solubility of the small molecule acceptors is likely to retard acceptor aggregation, to reduce the domain size and increase donor/acceptor interfacial area.

Conclusion

A systematic reverse engineering methodology applied via IBSS®CAMD tool has been successfully used to design and select alternative solvents for OPV devices, in replacement of current toxic solvents. The method required the identification of the solvent specifications, their translation to target physicochemical properties, and for the setting of target property values. By solving a multi-objective optimization problem with a computer assisted molecular design tool (IBSS®CAMD), the alternative solvents were ranked according to a global performance value, which evaluates the matching of the behavior of alternative solvents with a set of multiple target physicochemical properties. In our cases, 11 target properties were defined to evaluate the performance of alternative solvents to achieve high-performance OPV devices. By exploring the diversity of molecular structure, the reverse engineering approach greatly expands the list of candidate solvents compared to the trial-and-error list established beforehand and can give rise to solvents that exhibit better performances.

The method was applied successfully to two series of bulk heterojunctions solar cells using P3HT as electron donor and either PC71BM or EH-IDTBR as electron acceptor. For P3HT:PC71BM, five alternative solvents were found suitable to be used for OPV device processing, with an average PCE of 3.26% obtained by using p-cymene as processing solvent. For the second blend P3HT:EH-IDTBR, four alternative solvents could be identified, with anisole giving rise to the highest average PCE of 4.55%. Importantly, the selected solvents are all bio-sourced and are therefore of particular interest for future industrial up-scaling.

6 Case studies: Alternative Solvent Selection For New Donor

Polymers by IBSS®CAMD

Since the IBSS®CAMD tool has been proven efficient on two "reference" D/A systems in the previous chapter, it is now of interest to apply it to more recent "high performance" D/A systems. In this chapter, two efficient di-fluorinated copolymers are investigated. Fluorination of conjugated polymers was first used to fine-tune the frontier molecular orbital energy levels of electron-donor polymers. 166,167 Surprisingly, many authors found other positive effects of fluorinated polymers. For example, mixed "face-on" and "edge-on" backbone orientations of fluorinated polymers with respect to the device substrate were frequently observed and provide high out-of-plane hole mobilities. [168][169][170][171][172] Moreover, it has been found that the purity of the domains in alt- (5,6-difluoro-4,7-di(thiophen-2-yl)benzo[c]- [1,2,5]thiadiazole)] (PPDT2FBT), reaching power conversion efficiencies of 9.39% for PPDT2FBT:PC71BM OPVs. 171 solvents to prepare large-scale (an active area larger than 60 cm 2 ) PF2-based ITO-free modules, obtaining a high-power conversion efficiency (PCE) of above 6%. 175 These two alternative solvents are less toxic than standard halogenated solvents and have been selected by a trial and error approach. However, OX and TMB cannot be biosourced and TMB is still classified as hazardous. Accordingly, this chapter focuses on the selection of alternative solvents from biosolvents by using IBSS®CAMD for PF2based devices.

In addition, the impact of "side chains" on organic photovoltaic polymers has attracted considerable interest. Side chains are not only necessary for conjugated polymers to allow solution processing, they also impact molecular ordering, packing, and thin-film morphology and hence organic electronics performance. [176][177][178][179][180][181][182] In this work, we applied our solvent selection methodology based on IBSS®CAMD to study the consequences of side-chain engineering on the selection of efficient green solvents. In particular, the replacement of branched alkyl-chains by linear siloxane chains on the same conjugated backbone has been considered.

Mei et al. have reported in 2011 the introduction of siloxane functional groups as side chains in isoindigo conjugated polymers to provide sufficient polymer solubility. 176 They found that siloxane side chain could induce an unusual face-on orientation in isoindigo conjugated polymers, giving the polymer a dual face-on and edge-on orientation and improving the charge carrier mobility in transistor devices. Tang et al.

introduced siloxane functional groups as side chains for the modification of the benzodithiophene-benzotriazole alternated wide band gap copolymer, named PBDTFBTA-2Si. 182 They found that the introduction of siloxane functional groups has only a minor effect on the absorption and frontier orbital energy levels of the polymers but a significant impact on the miscibility with nonfullerene acceptors. The blends of PBDTFBTA-2Si and acceptor Y6 exhibited more balanced miscibility, carrier mobility, and phase separation, achieving a high PCE of 14.18% for OPVs.

Recently, the group of S. Mery synthesized PF2 derivatives with linear siloxane functional groups (instead of C20H41 branched alkyl chains), named KNSF2, in order to improve the photovoltaic performance.

Here, we apply the reverse engineering method to both PF2 and KNSF2 polymers blended with either PCBM or EH-IDTBR.

Major Properties for Polymers

UV-Vis characterization

The chemical structures of PF2 and KNSF2 are shown in Figure 6.1. The acceptors used in this chapter are PC71BM and EH-IDTBR, the molecular structure of which can be found in Figure 5.1. The PF2 and KNSF2 polymers were synthesized by the groups of Dr. Nicolas Leclerc and Dr. Stéphane Mery.

. 636 and 695 nm, respectively, which match closely the absorption peaks in the solid state (dashed line in Figure 6.2a). This behavior was attributed to temperaturedependent aggregation in solution, which is now considered to be responsible for the coexistence of face-on and edge-on polymer orientations in thin films. [183][184][185][186][187] There are two main processes involved in the absorption of PF2 solution:

(1) at high temperatures (above 75°C), the absorption is dominated by the dissolved polymer; and ( 2), when the temperature is below 75°C, the absorption is dominated by the aggregated polymer. At room temperature, the absorption peaks of KNSF2 in solution appears at 698, 644, and 427 nm, respectively, which are similar to the peak positions of the PF2 solution. In addition, the absorption peaks of KNSF2 solution at room temperature coincided with the absorption peaks in film (dash line in Figure 6.2b), demonstrating that the KNSF2 forms aggregates when the active layer is processed from a solution. The absorption of KNSF2 solution exhibits a weak temperaturedependent behavior, which means that KNSF2 forms aggregates even at high temperature (95 o C).

PF2 has an optical bandgap of about 1.60 eV, which is almost optimal for photovoltaic energy conversion 188 . The HOMO level was estimated electrochemically to -5,42 eV 189 while the LUMO level was calculated to be -3.83 eV, taking into account the optical band gap. KNSF2 has an optical bandgap of about 1.63 eV that is similar to PF2, which has a HOMO level of -5.25 eV.

Solubility and HSPs

HSPs for both polymers were measured using common solvents, covering a large portion of the Hansen space. A list of solutions were prepared with a solute concentration of 2 mg/ml. The prepared solutions were annealed at 40 o C overnight.

The solvent list and related PF2/KNSF2 solubility scores are shown in Appendix 9.8.

The HSPs of PF2 were found to be δD=19. 15, δP=3.87, δH=2.83, and R0 was estimated to 4.0, while the HSPs of KNSF2 were δD = 17.47, δP = 4.28, δH = 1.53, Ro = 4.9, respectively. Comparing the R0 of PF2 to KNSF2 and P3HT, PF2 is less soluble than P3HT (R0 = 4.7) and KNSF2.

The HSPs of PC71BM have been reported in literature and are given by δD=20. 2, δP=5.4, δH=4.5, R0=8.4. 113 The HSPs measurements of EH-IDTBR have been described

in Chapter 5, and the HSPs values of EH-IDTBE were δD=18. 8, δP=4.4, δH=4.3, as well as R0 is equal to 6.1. The positions of PF2/PC71BM and PF2/EH-IDTBR in Hansen space are shown in Figure 6.3 a and b, indicating that the solubility sphere of PF2 is completely within the solubility sphere of PC71BM and EH-IDTBR. fullerene acceptors blends is still on-going. The HSPs for these four materials are summarized in Table 6.1. (a)

Solvent selection by IBSS®CAMD

As mentioned in Chapter 4, six steps are required when using IBSS®CAMD to search for alternative solvents.

The same target properties (11 properties) have been chosen for PF2 and KNSF2based OPV devices, than for P3HT-based devices. However, the target values of the target properties may differ for the different donor:acceptor blends.

In this study, the target values for each target property are still adopted using two approaches mentioned in Chapter 5, which are based on preliminary experimental measurements and on reference solvents. All the target values are summarized in Table 6.2. The target values of solubility properties are specified according to the first approach. Suitable alternative solvents are required to solubilize both the donor and acceptor materials, i.e. in our case PF2:PC71BM, PF2:EH-IDTBR, or KNSF2:PC71BM.

The junction barycenter values of PF2:PC71BM blends are δD=19. 5, δP=4.4, δH=3.4.

Therefore, the HSP target ranges for PF2:PC71BM blends are defined as 18.5< δD < 20.5, For the KNSF2:PC71BM blends, the junction barycenter values are δD=18. 5, δP=4.7, δH=2.6, hence the corresponding HSP target ranges were defined as 17.5< δD < 19.5, 3.5< δP < 6, and 1.5 < δH< 3.5. Considering that the solubility spheres of KNSF2 and PC71BM only partially overlap, RED will be defined twice, once for KNSF2 and the other for PC71BM. The target range of both RED is <1. The solvent should be safe to use, thus requiring a flash point greater than 296.15 K. 159 Similarly, in order for the solvent to remain liquid at the processing temperature, a melting point of less than 283.15 K is required.

𝛿 𝑃 (MPa) 1/2 3.4 < 𝛿 𝑃 < 5.4 a 1 0.56 0.48 3.1< 𝛿 𝑃 < 5.1 b 3.5< 𝛿 𝑃 < 6 b 𝛿 𝐻 (MPa) 1/2 2.4< 𝛿 𝐻 < 4.4 a,b 1 0.24 0.48 1.5< 𝛿 𝐻 < 3.5 c Ra (MPa) 1/2 -PF2 Ra<3 3 0.84 Ra (MPa) 1/2 -KNSF2 Ra<4 2 Ra (MPa)
For the properties Ra, boiling point, ∆Hvap, density, and viscosity, the target values have been defined by using the key properties of a "reference" solvent that is known to yield high-performance OPV devices. For the investigated materials, o-DCB is a good choice as it dissolves efficiently PF2 and has led to the highest power conversion efficiencies with the PF2:PC71BM blends (~10%) and P3HT:EH-IDTBR blends (~7.3%).

As well, the KNSF2:PC71BM devices achieve a PCE of about 8% when using o-DCB as a process solvent. The experimental database of the target properties for o-DCB are summarized in Table 5.2. As the Ra values between o-DCB and PF2 is 2.48, the target value for Ra is set to be lower than 3. Since the solubility spheres of KNSF2 and PC71BM partially overlap, different Ra target values will be set for each of the two materials.

The Ra between o-DCB and KNSF2 is 4.4, which is close to the R0 of KNSF2 (R0 = 4.9).

The solvent provides poor solubility for the solute when it is at the boundary of the sphere of solubility of the solute. Therefore, the target value of Ra for KNSF2 is defined as less than 4. The target value of Ra for PC71BM is less than 3, because the Ra of PC71BM and o-DCB is 2.50.

As shown in table 5. For anisole (AN), the low GloPerf is caused by the ProPerfp values of Ra (ProPerfp- For molecular design, numerical molecular structures are designed and properties of these molecules are evaluated by IBSS®CAMD. Table 6.5 lists 8 designed solvents with a GloPerf values over 0.9 for further investigation for PF2:PC71BM blends, --> KNSF2: PC71BM blends: For the flash point, CPME has a low ProPerfp of 0, therefore a safety issue for usage and storage. Moreover, commercial CPME is currently produced from fossil resources although it could be bio-based. Therefore, CPME should be removed from the list of alternative solvents for KNSF2:PC71BM blends.

Ra = 0.17
0.21 Y 1-(3-Buten-2-yl)-4- methylbenzene (1-4-MB) 97664-18-1 0.931 N NA N 4-Methylstyrene (4-MS) 622-97-9 0.912 Y 0.52 N 1-Phenyl-2-butene (1-P-2-B) 935-00-2 0.909 N NA N 1-Methyl-2-(2-propyn-1- yl)benzene (1-M-2-B) NA 0.901 N NA N
For solubility, different Ra and RED were set for KNSF2 and PC71BM. Thus, the two materials need to be discussed separately to screen for the suitable alternative solvents.

-PX is the first candidate in the list with a GloPerf of 0.874. The imperfectly matched property is Ra-PC71BM with a ProPerfp of 0.026, indicating that PC71BM has poor solubility in PX. However, PX provides good solubility for KNSF2 (ProPerfp-Ra=1). As in the case of the P3HT:PC71BM copolymer, the solubility of PC71BM was improved by adding DPE.

-PC and CN were similar to PX for KNSF2:PC71BM blends. They provide good solubility of KNSF2, but have poor miscibility with PC71BM. In this case, high processing temperatures and additives should be used to optimize the solubility of PC71BM in the blend solution to achieve high performance devices with improved morphology.

- -α-PNE, β-PNE and PNA are located in the boundary of PC71BM, although they can provide a good solubility of KNSF2. Considering that temperature is a key factor in material solubility, a solubility measurement should be taken for α-PNE, β-PNE and PNA.

-IA will be removed from the list, as neither material is soluble in it.

Consequently, PX, PC and CN are selected as alternative solvents for KNSF2:PC71BM blends, while AN, d-LM, TPO, α-PNE, β-PNE and PNA requires additional solubility measurements to evaluate their potential for processing KNSF2:PC71BM. The investigation of OPV devices processed from these alternative solvents is still on-going.

We may nevertheless already conclude that the introduction of siloxane functional groups as solubilizing side chains onto the fluorinated conjugated backbone of PF2, has broadened the choice for candidate solvents. The JV curves and corresponding parameters of PF2:EH-IDTBR cell devices are shown in Figure 6.5 and table 6.9. The average PCE equals 8.0 when processed from PX solutions, exceeding the PCE of devices processed from o-DCB (7.29%). Interestingly, the EH-IDTBR based devices could be fabricated by a single biosolvent (without additive). The Ra and RED values of EH-IDTBR are smaller than those of PC71BM (table 6.9), indicaing that the solubility of EH-IDTBR is higher than that of PC71BM in PX. A higher solubility of the small molecule acceptors is likely to retard acceptor aggregation, to reduce the domain size and to increase donor/acceptor interfacial area.

Photovoltaic Performance

Conclusion

In summary, the IBSS®CAMD tool has been successfully used to design and select alternative solvents for PF2-based OPV devices. PX was defined as the best candidate for both blends and allowed to achieve an average PCE of 9.10% with PF2:PC71BM based devices when using DPE as the processing additive. For the second blend PF2:EH-IDTBR, PX gave rise to the average PCE of 8.03%. It is important to note, that the small number of alternative solvents with a high GloPerf is due to the small solubility sphere radius (R0) and underlines the low miscibility of PF2 in most solvents, which is itself a consequence of the high planarity and strong intermolecular stacking of the fluorinated polymer backbone.

The IBSS®CAMD results further reveal a larger R0 for KNSF2, in comparison to PF2, and consequently a broader choice of alternative solvents, suggesting that the insertion of siloxane functional groups on the side chains is an effective way to improve the solubility properties of fluorinated polymers. Nevertheless, the small overlap of the solubility spheres of KNSF2 and PC71BM is a limiting factor and suggests that other acceptors should be considered for KNSF2-based OPV devices.

Finally, the study on the fluorinated polymers corroborates the universal applicability of the reverse engineering methodology based on IBSS®CAMD for various donor and acceptor blends used for bulk heterojunctions solar cells.

Conclusion and Perspectives

My PhD project was devoted to improving the performance of organic photovoltaic devices and reducing the environmental impact of the device manufacturing. OPV is seen as an important green technology to replace conventional energy sources in the future. In recent years, the focus on research and development of organic solar cells has contributed to improving the performance of organic cells and making them economically viable. However, there is undoubtedly a need for devices to be prepared in a "greener" manner when marketing OPV modules, for example by using biodegradable organic materials or non-toxic processing solvents. In this thesis, the selection of non-toxic alternative solvents has been the focus of the work.

Taking into account that the organic electron-donor and electron-acceptor materials are continually evolving to further improve the power conversion efficiency of OPV devices and that the traditional "trial-and-error" approach for the selection of non-toxic solvents is hindered by the multiple parameters that may impact the device performances, we have introduced a reverse engineering approach, based on the IBSS®CAMD numerical tool, to select alternative solvents and applied the methodology to different organic photovoltaic materials.

IBSS®CAMD can be used in two different modes for solvents selection: (a) to evaluate the performance of a list of pre-selected existing solvents, or (b) to design new molecules and evaluate their performances. Both ways are used in this thesis, with a particular focus on bio-sourced solvents, as these are expected to exhibit low health and environmental impacts.

The utilization of IBSS®CAMD for organic photovoltaic applications required a preliminary work to identify the physico-chemical parameters of the solvent that have a strong impact on the photovoltaic performances. For each of these properties, target values, which the alternative solvent must satisfy, had to be defined. IBSS®CAMD was then used to estimate the physico-chemical properties of a large number of solvents and to evaluate the "performance" of the solvents for each property and rank them according to an overall performance criterion. Thus, eleven target properties were defined and applied to four different donor/acceptor blends:

1) P3HT:PC71BM system This blend has been used as a reference system, even though its photovoltaic performance is nowadays largely outdated. Indeed, this material has been the subject of numerous studies throughout the world and today represents the donor/acceptor system whose properties are best understood.

5 alternative solvents could be identified through the two modes of IBSS®CAMD (anisole, 2-methyl anisole, p-xylene, p-cymene and terpinolene) and allowed to reach similar device performances as with the original toxic solvent (o-DCB).

2) P3HT:EH-IDTBR system EH-IDTBR is an electron-acceptor molecule recently developed to replace fullerene derivatives (such as PC71BM) and improve the performance of OPV devices. Four alternative non-toxic solvents were selected through the first mode of IBSS®CAMD tool: anisole, p-xylene, p-cymene and terpinolene. A high average PCE of 4.55% could be obtained using anisole as processing solvent.

3) PF2:PC71BM system

The same approach was used to identify a bio-based solvent, p-xylene, for the implementation of the PF2:PC71BM mixture with only minor loss of performance, and allowed us to achieve a conversion efficiency of 9% with an experimental protocol requiring a lower annealing temperature than that based on chlorinated solvents.

4) PF2:EH-IDTBR system

Due to the limited solubility of PF2, p-xylene was the only alternative solvent selected according to the candidate list of IBSS®CADM results. P-xylene allowed the OPV device to achieve a PCE of 8.03%, showing better performance than o-DCB processed devices.

5) KNSF2:PC71BM system KNSF2 is an efficient polymer that was synthesized by the groups of Dr. Nicolas Leclerc and Dr. Stéphane Mery, and for which siloxane functional groups were introduced to replace the alkyl side-chains of the PF2 polymer. HSP measurements demonstrated that KNSF2 is more soluble than PF2. The IBSS®CAMD results also validate this conclusion by providing more solvent candidates. However, the solubility of PC71BM in the solvent candidates limited green-processing of KNSF2based OPVs. The next step will therefore be to use other acceptors instead of PC71BM to prepare green processable KNSF2-based OPVs. The molecular design model will also be used to search for alternative solvents for KNSF2-based OPVs.

In summary, the five cases studied in this PhD clearly demonstrate that the reverse engineering approach is an efficient way to select alternative solvents for organic semiconductors and to avoid the time-consuming trial and error approach. It should further be noted that while the method has only been applied to materials designed for OPV applications, it should also be of interest for the selection of solvents for other solution-processed organic semiconductor devices.

Effets de la morphologie sur l'efficacité de conversion photovoltaïque

Solvents et performances photovoltaïques

Sélection de solvants alternatifs

Comme mentionné ci-dessus, la morphologie de l'HJV peut être optimisée par un choix approprié de solvants, de mélanges Les cinq cas étudiés dans cette thèse ont clairement fait ressortir que l'approche de l'ingénierie inverse est un moyen efficace pour sélectionner des solvants de remplacement pour les semi-conducteurs organiques. Il convient en outre de noter que si la méthode n'a été appliquée dans ce travail qu'aux matériaux conçus pour des applications photovoltaïques, elle devrait également présenter un intérêt pour tout dispositif optoélectronique élaboré à partir de solutions organique.

Conclusion

  This thesis work was carried out under the supervision of Dr. Thomas Heiser, Professor at the University of Strasbourg. I would like to express sincere gratitude to him for his guidance, encouragement and support throughout these three years. I could not have imagined a better advisor and mentor for my PhD studies. I would like to thank my reporters, Dr. Guillaume Wantz, Maître de Conférences HDR of Bordeaux INP, École Nationale Supérieure, de Chimie, de Biologie et de Physique (ENSCBP), and Dr. Jean-Marie Aubry, Professor of École Nationale Supérieure de Chimie de Lille, for their interest in my work. I would also like to thank the members of the Jury: Dr. Ivonne Rodriguez-Donis, Dr. Gilles Ulrich and Ms. Sophie Thiebaud-Roux, who gave me good advice in their respective fields. I would like to thank the laboratory collaborators: Dr. Nicolas Leclerc, Ms. Stéphanie Ferry, Dr. Stéphane Méry and Dr. Kamatham Narayanaswamy for providing the polymers; Dr. Ivonne Rodriguez-Donis and Dr. Sophie Thiebaud-Roux guided me in use of the IBSS®CAMD tool; Dr. Markus Kohlstädt provided help with Hansen's parameter theory. I would like to thank all the staff of the MaCEPV team, especially Dr. Patrick Levêque, Dr. Sadiara Fall, Dr. Olzhas Ibraikulov and Mr. Nicolas Zimmermann with whom I worked closely during the fabrication of the devices. Thanks to the good atmosphere of the team and the mutual help within the team, it is really fun to come to work every day.

Figure 1 .

 1 Figure 1.1 Evolution of record photovoltaic conversion efficiencies for different families of

1

 1 Figure 1.1 Evolution of record photovoltaic conversion efficiencies for different families of semiconductors and technologies. 19 ...............................................................................

Figure 1 . 2

 12 Figure 1.2 Photographs of (a) a flexible OPV (Source: Fraunhofer ISE), and (b) a transparent OPV 31 . ..............................................................................................................................

Figure 2 .

 2 Figure 2.1 (a) Chemical structure of ethylene and polyacetylene, and (b) pz orbital overlap to form π (bonding) and π* (anti-bonding) band in C-C system. .....................................

Figure 2 . 2

 22 Figure 2.2 Band alignment of donor and acceptor materials for a heterojunction. .......................

Figure 2 .

 2 Figure 2.3 (a) The structure of OPV and (b) key steps involved in active layer (Red area: donor domains, Blue area: acceptor domains, Mixture: bulk heterojunction). .........................

Figure 2 . 4

 24 Figure 2.4 Schematic view of standard (a) and inverted (b) OPV devices. ......................................

Figure 2 .

 2 Figure 2.5 J-V characteristics of OPVs. The black and symbolic red lines represent dark and light curves, respectively. The navy point indicates the maximum power point (MPP) of a solar cell (VMPP). Green points show the open circuit voltage VOC and the short circuit current density JSC of the solar cell. The fill factor (FF) is determined by the area ratio of the yellow rectangle to the gray dashed rectangle. .........................................................................................................................................

Figure 2 . 6

 26 Figure 2.6 Diagram of the interfacial layer on the ITO after cleaning from one side. .....................

Figure 2 .

 2 Figure 2.7 (a) The OPV sample and (b) shadow mask used for JV characteristics. .........................

Figure 3 . 1

 31 Figure 3.1 AFM topography images (2 µm ◊ 2 µm) of as-cast of MDMO-PPV:PC61BM spincasted from (a) CB, (c) CS2, (e) CF, (g) pyridine, (i) trichloroethylene, (k) toluene, and (m) 1-methylpyrrole. [From REF. 87 ] (The solubilities of PC61BM in various solvents are shown at the top of the corresponding AFM images.) ................................

Figure 3 . 2

 32 Figure 3.2 Atomic force microscopy (AFM) micrographs (5 × 5 µm) of thin films of 1:1 TQ1:PC71BM (a-c) and 1:3 PC71BM (d-f) spin-coated from CF (a,d), CB (b,e), o-DCB (c,f). Scale bar indicates 1 µm. Surface roughness (RMS), as well as the

Figure 3 . 3

 33 Figure 3.3 The AFM images (size: 5 ◊ 5 μm) of (a) BDT-2T-DCV-Me: IDIC and (b) BDT-2T-CNAB: IDIC blend films processed from CF. 87 .............................................................................

Figure 3 . 4

 34 Figure 3.4 AFM height images of spin-casted PFB/PCBM blends from xylene under (a) "no

Figure 3 . 5

 35 Figure 3.5 Examples of processing additives for BHJ morphological control. .................................

Figure 3 .

 3 Figure 3.6 (a)-(d) Represents surface topography images of PTB7: PC71BM photoactive layer with different concentration of DIO (0 ,1, 3 and 5 vol%) respectively. 100 ........................

Figure 3 .

 3 Figure 3.7 (a) HSPs diagrams with the good and bad solvents resulting from the solubility tests and the fitted solubility sphere. Radius R0 of the solubility sphere as a function of temperature. The radius is fixed at a solubility limit of 10mg/mL. The dashed line is a guide to the eye. 127 ................................................................................

Figure 4 . 1

 41 Figure 4.1 Division of N-phenyl-1,4-benzenediamine molecule by group contribution methods. ..........................................................................................................................

Figure 4 .

 4 Figure 4.2 (a) shows an example corresponding to a property whose x value is within a target range defined by two boundary values and thus two different σ parameters. (b) examples corresponding to properties, whose x values need either to be higher or equal to a given target value, and (c) examples corresponding to a property whose x values need either to be lower or equal to a given target value. ..................................

Figure 4 . 3

 43 Figure 4.3 Steps of a genetic algorithm in IBSS®CAMD. ..................................................................

Figure 4 . 4

 44 Figure 4.4 Molecular graph representation of acetone. .................................................................

Figure 4 . 5

 45 Figure 4.5 Simple and complex groups representation...................................................................

Figure 4 . 6

 46 Figure 4.6 Systematic methodology based on reverse engineering and CAPD to design alternative solvents. .........................................................................................................

Figure 4 . 7

 47 Figure 4.7 Examples of chemical groups and connection types for building alternative solvents using IBSS®CAMD tool. (R1 and R2 are randomly selected chemical groups from the IBSS ®CAMD data base that are connected to other chemical groups by

Figure 4 . 8

 48 Figure 4.8 Mutation operator example. ..........................................................................................

Figure 4 . 9

 49 Figure 4.9 Crossover operator example. .........................................................................................

Figure 4 .

 4 Figure 4.10 Insertion operator example. .........................................................................................

Figure 4 .

 4 Figure 4.11 Deletion operator example. .........................................................................................

Figure 4 .

 4 Figure 4.12 Substitution operator example. ...................................................................................

Figure 5 . 1

 51 Figure 5.1 Chemical structure of donors and acceptors. ................................................................

Figure 5 . 2

 52 Figure 5.2 Differences between experimental data and IBSS®CAMD predicted values for various properties. ...........................................................................................................

Figure 5 .

 5 Figure 5.3 (a) The positions of P3HT and PC71BM in Hansen solubility space, (b) the positions of P3HT and EH-IDTBR in Hansen solubility space. ..........................................................

Figure 5 .

 5 Figure 5.4 (a) The JV characteristics of P3HT:PC71BM based OPV devices processed from various solvents without DPE, and (b) with DPE. ...........................................................

Figure 5 . 5

 55 Figure 5.5 JV curves of P3HT:EH-IDTBR based OPVs processed from various solvents.................

Figure 6 . 1

 61 Figure 6.1 The chemical structures of donor PF2 (side chain: R1) and KNSF2 (side chain: R2)......

Figure 6 .

 6 Figure 6.2 UV-Vis absorption spectra of (a) PF2 and (b) KNSF2 in solution as a function of temperature and in thin film. .........................................................................................

Figure 6 . 3

 63 Figure 6.3 The position of (a) PF2:PC71BM, (b) PF2:PEH-IDTBR and (c) KNSF2:PC71BM in Hansen space. ................................................................................................................

Figure 6 .

 6 Figure 6.4 a) The J-V curves of PF2 from o-DCB and PX/DPE solutions, and b) the JV curvers of PF2 based devices processed from PX/DPE mixture solvents at different processing temperature. ................................................................................................

Figure 6 . 5

 65 Figure 6.5 The JV charatistics of PF2:EH-IDTBR based OPVs processed from o-DCB and pxylene. ............................................................................................................................

  .................................... Table 3.1 Solubility of PC61BM in various solvents. ......................................................................... Table 3.2 Solubilities of BDT-2T-DCV-Me and BDT-2TCNAB in CF, and PCEs of the OPVs devices based on BDT-2T-DCV-Me: IDIC films and BDT-2T-CNAB: IDIC films under the illumination of AM 1.5G, 100 mW cm -2 . 87 ................................................................Table 3.3 Effects of processing additive on the PCE of several type of donor/acceptor OPVs. ....... Table 3.4 Examples of alternative solvents for several type of donor/acceptor OPVs by trial and error approach. ......................................................................................................... Table 3.5 Examples of alternative solvents for several type of donor/acceptor OPVs by HSPstheory. .............................................................................................................................. Table 4.1 Estimation of normal boiling point of N-phenyl-1,4-benzenediamine. 142 ...................... Table 4.2 Examples of available basic groups and their encoding in IBSS®CAMD........................... Table 5.1 The target properties, corresponding values for P3HT:PC71BM blends and P3HT:EH-IDTBR blends. ( a P3HT:PC71BM blends, and b P3HT:EH-IDTBR blends.) ............................ Table 5.2 The physicochemical properties and corresponding values of o-DCB and CB. ................ Table 5.3 Group contribution method-based property models and Universal constants for the target properties. ....................................................................................................... Table 5.4 The candidates provided for P3HT:PC71BM blends by IBSS®CAMD with a GloPerf > 0.6.(/: non-available data) ............................................................................................... Table 5.5 The candidates provided for P3HT:EH-IDTBR blends by IBSS®CAMD with a GloPerf > 0.6. .(/: non-available data) ............................................................................................. Table 5.6 List of the best solvent candidates selected from the results of molecular design provided by IBSS®CAMD. (Y: yes, N: no, NA: non-available data) .................................... Table 5.7 OPV device parameters of P3HT:PC71BM based devices fabricated from various solvents. .........................................................................................................................Table 5.8 The corresponding photovoltaic device parameters of P3HT:EH-IDTBR based devices fabricated from selected candidates. ................................................................ Table 5.9 Ra and RED values between various solvents and two acceptor materials. .................. Table 6.1 HSPs for PF2, KNSF2, PC71BM and EH-IDTBR. ................................................................ Table 6.2 The target properties, corresponding values for PF2:PC71BM, PF2:EH-IDTBR, andKNSF2:PC71BM. ( a PF2:PC71BM blends, b PF2:EH-IDTBR blends, and c KNSF2:PC71BM blends.) .................................................................................................. Table

  (Y: yes, N: no, NA: non-available data) ............................................................................................................................... Table 6.6 List of the best solvent candidates selected from the results of molecular design provided by IBSS®CAMD for PF2:EH-IDTBR blends. (Y: yes, N: no, NA: non-available data) ............................................................................................................................... Table 6.7 The candidates provided for KNSF2:PC71BM by IBSS®CAMD with a GloPerf > 0.6. ....... Table 6.8 Summary of PF2:PC71BM device performance for various solvents. ............................. Table 6.9 The corresponding photovoltaic device parameters of PF2:EH-IDTBR based devices fabricated from various solvents. ...................................................................................

Figure 1 . 1

 11 Figure 1.1 Evolution of record photovoltaic conversion efficiencies for different families of semiconductors and technologies.[START_REF]Best Research-Cell Efficiency Chart[END_REF]

Figure 1 . 2

 12 Figure 1.2 Photographs of (a) a flexible OPV (Source: Fraunhofer ISE), and (b) a transparent OPV 31 .

Chapter 2 Chapter 6

 26 details the basic principles of organic semiconductors and organic solar cells. Current understanding of the mechanisms of generation, transport and recombination of charge carriers is presented, as well as the state-of-the-art of the latest remarkable achievements in polymer photovoltaics. The main methods and detailed experimental steps used throughout the paper are described. Chapter 3 describes the relationship among processing solvents, morphology of the active layer and performance of OPV devices. The state-of-the-art methods of solvent selection applied in OPVs are shown. Chapter 4 reports the fundamentals of the IBSS®CAMD tool, including the basic principles and application steps. Chapter 5 focuses on the application of IBSS®CAMD to P3HT/PC71BM and P3HT/EH-IDTBR based OPV devices. The alternative solvents identified and ranked by IBSS®CAMD are used to prepare the devices, and the photovoltaic performances are compared. depicts the IBSS®CAMD application to two highly efficient donor polymers: PF2 and KNSF2. The UV-Vis absorption and solubility properties of both polymers are measured and analyzed. Then, related OPV devices prepared by alternative solvents are described.

Figure 2 .

 2 Figure 2.1 (a) Chemical structure of ethylene and polyacetylene, and (b) pz orbital overlap to form π (bonding) and π* (anti-bonding) band in C-C system.

  diffusion and dissociation into free charge-carriers at the donor/acceptor heterojunction, (3) the free carriers are transported to their respective electrodes via the drift/diffusion mechanisms and,

Figure 2 . 2

 22 Figure 2.2 Band alignment of donor and acceptor materials for a heterojunction.

Figure 2 .

 2 Figure 2.3 (a) The structure of OPV and (b) key steps involved in active layer (Red area: donor domains, Blue area: acceptor domains, Mixture: bulk heterojunction).

Figure 2 .

 2 Figure 2.4 illustrates two different OPV structures that are known as "standard"

Figure 2 . 4

 24 Figure 2.4 Schematic view of standard (a) and inverted (b) OPV devices.

Figure 2 .

 2 Figure 2.5 J-V characteristics of OPVs. The black and symbolic red lines represent dark and light curves, respectively. The navy point indicates the maximum power point (MPP) of a solar cell (VMPP). Green points show the open circuit voltage VOC and the short circuit current density JSC of the solar cell. The fill factor (FF) is determined by the area ratio of the yellow rectangle to the gray dashed rectangle.

  a) filtering the ZnO suspension by nylon filter with pore diameter of 0.45 µm; b) spin-coating at 5000 rpm, with acceleration of 1000 rpm/s, during 60 sec; c) cleaning the ZnO with ethanol from part of the substrate (Figure 2.6); d) annealing of ZnO layer at 110°C for 12 minutes in air to remove the residual solvent.

Figure 2 . 6

 26 Figure 2.6 Diagram of the interfacial layer on the ITO after cleaning from one side.

  7 a and b, respectively. There are four cells on a sample, each with an active layer area of 12 mm 2 (Figure 2.7 b), as defined by the shadow masks of all the solar cell devices discussed in this thesis.

Figure 2 .

 2 Figure 2.7 (a) The OPV sample and (b) shadow mask used for JV characteristics.

Figure 3 . 1

 31 Figure 3.1 AFM topography images (2 µm ◊ 2 µm) of as-cast of MDMO-PPV:PC61BM spin-casted from (a) CB, (c) CS2, (e) CF, (g) pyridine, (i) trichloroethylene, (k) toluene, and (m) 1-methylpyrrole. [From REF. 87 ] (The solubilities of PC61BM in various solvents are shown at the top of the corresponding AFM images.)

Figure 3 . 2

 32 Figure 3.2 Atomic force microscopy (AFM) micrographs (5 × 5 µm) of thin films of 1:1 TQ1:PC71BM (ac) and 1:3 PC71BM (d-f) spin-coated from CF (a,d), CB (b,e), o-DCB (c,f). Scale bar indicates 1 µm.

Figure 3 . 3

 33 Figure 3.3 The AFM images (size: 5 ◊ 5 μm) of (a) BDT-2T-DCV-Me: IDIC and (b) BDT-2T-CNAB: IDIC blend films processed from CF.87

  Evaporation rates will be higher than the crystallization rate if highly volatile solvents are used, restraining the crystallization of donor and acceptor materials into large domains. The relationship between drying kinetics and aggregation has been wildly reported. Taking poly[(9,9-dioctylfluorenyl-2,7-diyl)-altco-(N,N′-diphenyl-N,N′di(p-butylphenyl)-1,4-diaminobenzene)] (PFB):PCB61M system as an example, S. Nilsson et al. reported different morphologies of BHJ films which were obtained under different solvent evaporation rates.[START_REF] Nilsson | Morphology and Phase Segregation of Spin-Casted Films of Polyfluorene/PCBM Blends[END_REF] Figure 3.4 displays the morphologies of PFB/PC61BM films when spin-coated from o-xylene (boiling point=138 °C) under "no vapor" conditions, i.e. without using extra solvent vapor, as

Figure 3 . 4

 34 Figure 3.4 AFM height images of spin-casted PFB/PCBM blends from xylene under (a) "no vapor" conditions, (b) "high vapor" conditions, (c) from toluene under "no vapor" conditions and (d) from

Figure 3 . 5

 35 Figure 3.5 Examples of processing additives for BHJ morphological control.

Figure 3 .

 3 Figure 3.6 (a)-(d) Represents surface topography images of PTB7: PC71BM photoactive layer with different concentration of DIO (0 ,1, 3 and 5 vol%) respectively. 100

  𝐸 𝐷 𝑉 ) , 𝛿 𝑃 = √( 𝐸 𝑃 𝑉 ) , and 𝛿 𝐻 = √( 𝐸 𝐻 𝑉 ) are Hansen solubilityparameters. Each molecule can be represented by its position in a three-dimension space (Hansen solubility space), and the corresponding coordinates are defined by the three solubility parameters. The basic concept for describing the miscibility between two molecules is "like dissolves like." Therefore, the solute can be soluble in a solvent when they have similar molecular interactions, i.e. the similar HSPs. Such a similarity is quantified by the distance 𝑅 𝑎 between the HSPs of a solvent (𝛿 𝐷1 , 𝛿 𝑃1 , and 𝛿 𝐻1 )

  solubility sphere radius is somewhat misleading since it can depend to some extent on the experimental conditions such as temperature, annealing and stirring time of the solution. Generally, 𝑅 0 increases with temperature and stirring time, as illustrated by the work of Strohm et al. on the temperature dependency of the P3HT-Solubility sphere (Figure 3.7). 127 As a consequence, solvents that are located near the boundary of the solute solubility sphere may provide only a limited solubility for the solute.

Figure 3 .

 3 Figure 3.7 (a) HSPs diagrams with the good and bad solvents resulting from the solubility tests and the fitted solubility sphere. Radius R0 of the solubility sphere as a function of temperature. The radius is fixed at a solubility limit of 10mg/mL. The dashed line is a guide to the eye.127

  and calculating a global performance index GloPerf for each designed molecule (see below). The initial chemical structures are continuously modified according to a genetic algorithm optimization strategy (see below) in order to maximize the GloPerf index. The final list of the solvent candidates comes from the solution of the optimization problem of GloPerf on the optimization variables.

  Ak, Bk and Ck coefficients for numerous physicochemical properties estimated by Marrero and Gani 142 are used as a database by IBSS®CAMD. The corresponding additional adjustable model parameter can be found in Ref 142.

Figure 4 . 1

 41 Figure 4.1 Division of N-phenyl-1,4-benzenediamine molecule by group contribution methods.

Figure 4 . 3 .

 43 For instance, if the target is to achieve a flashpoint level above a specified value to enhance safety, the distance function is characterized by a lower target value and a single tolerance margin (figure 4.3b). On the other hand, if the target is a viscosity at 298 K within a given range, two target values and tolerance margins are needed (figure 4.3a).

Figure 4 .

 4 Figure 4.2 (a) shows an example corresponding to a property whose x value is within a target range defined by two boundary values and thus two different σ parameters. (b) examples corresponding to properties, whose x values need either to be higher or equal to a given target value, and (c) examples corresponding to a property whose x values need either to be lower or equal to a given target value.

n+1

  (children), which differs from population n (parent generation), is again evaluated using the same performance-biased method and the best solutions are modified to yield generation n+2 (grand-children), etc. The generation steps of the genetic algorithm are shown in Figure 4.3.

Figure 4 . 3 4 . 1 . 4

 43414 Figure 4.3 Steps of a genetic algorithm in IBSS®CAMD.

Figure 4 .

 4 4 shows an example of the acetone molecular representation model.

Figure 4 . 4

 44 Figure 4.4 Molecular graph representation of acetone.

P3

  represents the bond type (0 for bond with C or with the same atom. e.g. C-C-C; N-N; 1 for bond with at least one non-similar atom (C-O, C=O, C≡N, N-O); 2 for atom in a non-aromatic cycle e.g. pyridine, 3 in an aromatic ring e.g. benzene; 4 for an atom shared by two aromatic rings e.g. naphthalene; 5 for an atom shared by two cycles, one of them aromatic e.g. indane, 6 for other aromatic cases e.g. biphenyl; 7 for an atom shared by two non-aromatic rings.

  represented in the same way. But they need additional information related to their external connections. An example is shown in Figure4.5.The molecular structure of acetaldehyde can be decomposed by showing how both fragments are connected. The fragments are detailed by their graph and a vector to show their position and the connection way in a whole molecule. Each EG code identifies a unique complex group available in a database. IBSS® CAMD uses a database of more than 200 fragments for molecular design.

Figure 4 . 5

 45 Figure 4.5 Simple and complex groups representation.

Figure 4 . 6

 46 Figure 4.6 Systematic methodology based on reverse engineering and CAPD to design alternative solvents.

(

  OF) defined by: 𝑂𝐹 = 𝑀𝐼𝑁{𝐺𝑙𝑜𝑃𝑒𝑟𝑓(𝑀𝑆, 𝑐𝑜𝑛𝑑 𝑗 ) -1}(15) As discussed before (section 4.1.2), the property values of a molecule are predicted by a group contribution method. The chemical nature of each group and the connections between chemical moieties determine the GloPerf values. An important input issue for IBSS®CAMD is the definition of the chemical groups or fragments to create a platform molecule. Common chemical fragments MS (simple ones like -CH3, -OH or more complex ones such as -COOH) are usually listed in the library of CAMD tools as elementary blocks. A large number of molecular structures can be generated from these building-blocks. IBSS®CAMD generates molecules with a maximum predefined size (or number of blocks) using only the elementary blocks or attaching them to a fixed building-core. Namely, a molecule is built from the fixed fragments (contained in every potential molecule) and the free groups (connected to the fixed part).

  Figure 4.7 represents some examples of elementary/fixed blocks and different types of bonds among these building blocks. The chemical groups for molecular design are shown in Appendix 9.3.

Figure 4 . 7

 47 Figure 4.7 Examples of chemical groups and connection types for building alternative solvents using IBSS®CAMD tool. (R1 and R2 are randomly selected chemical groups from the IBSS ®CAMD data base that are connected to other chemical groups by either simple or double bonds.

Figure 4 . 8

 48 Figure 4.8 Mutation operator example.

Figure 4 . 9

 49 Figure 4.9 Crossover operator example.

Figure 4 .

 4 Figure 4.8), these branches are added into the original group.

Figure 4 .

 4 Figure 4.10 Insertion operator example.

Figure 4 . 9 )

 49 . It can lead to the deletion of whole branches of the molecule. A group of the graph is randomly chosen (-C<). The group can be deleted if it has two bonds of the same type. As a result, the extra branches are deleted and two remaining bonds (same type) are directly recombined. In Figure 4.11, the >CH-CH=CH-CH3 (blue coloured) is deleted, and the group -CH3 is connected directly to the remaining fragment (black coloured), resulting in a new molecule.

Figure 4 .

 4 Figure 4.11 Deletion operator example.

Figure 4 .

 4 Figure 4.12 Substitution operator example.

  In this thesis, we apply the IBSS®CAMD reverse engineering tool to find alternative biosolvents for processing organic photovoltaic materials. The method is applied to blends of poly (3-hexylthiophene) (P3HT) and[6,6]-phenyl-C71-butyric acid methyl ester (PC71BM) as well as to P3HT blended with Ethylhexyl-rhodaninebenzothiadiazole-coupled indacenodithiophene (EH-IDTBR). The chemical structure of P3HT, PC71BM and EH-IDTBR are shown in Figure5.1. P3HT is a well-known electrondonor polymer that has been extensively studied for OPV applications and is therefore a good reference for testing our methodology.149 In addition, despite the extensive literature data on P3HT based solar cells, only few examples have dealt with the green solvent issue. Toluene and ethyl benzenecarboxylate (EB), an additive, have been used by Shen et al. and resulted in a maximum PCE of almost 5%. 113 Chueh et al. used oxylene and processing additive 1,2-dimethylnaphthalene (1,2-DMN) to replace o-DCB on P3HT: indene-C60 bisadduct (IC60BA) based devices leading to a PCE of 5.7%. 150 EH-IDTBR is a promising non-fullerene acceptor that has recently generated a lot of interest in replacing fullerene derivatives and improving the PCE of P3HT-based

Figure 5 . 1

 51 Figure 5.1 Chemical structure of donors and acceptors.

Figure 5 . 2

 52 Figure 5.2 Differences between experimental data and IBSS®CAMD predicted values for various properties.

Figure 5 .

 5 Figure 5.3 (a) The positions of P3HT and PC71BM in Hansen solubility space, (b) the positions of P3HT and EH-IDTBR in Hansen solubility space.

  4), represented by their SMILES (simplified molecular input line entry specification) code and evaluated by IBSS®CAMD through its first operating mode. Molecular design: New molecules have been built form a list of chemical groups connected randomly by specifying possible positions and bond types (single or double) for each group. The complete chemical groups are used in IBSS®CAMD for P3HT:PC71BM blend are shown in appendix 9.3. Halogen elements like -Cl, -Br -I are discarded from the chemical group list to avoid a-priori toxic solvents.

  4 and 5.5, respectively. The corresponding full sets of 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 values are given in Appendix 9.5 and 9.6 Among these best ranked solvents, eight solvents, namely anisole (AN), p-xylene (PX), butyl acetate (BA), tetrahydrofuran (THF), terpinolene (TPO) and p-cymene (PC), isoamyl acetate (IA), d-limonene (LM) are selected for both P3HT:PC71BM and P3HT:EH-IDTBR blends, while Benzyl benzoate (BBzo) occurs only for P3HT:PC71BM, and cyclopentyl methyl ether (CPME) for P3HT:EH-IDTBR. The performance evaluation for the remaining solvents is given in Appendix 9.5 and 9.6. Further analysis of the individual 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑃 values leads us to dismiss some of these solvents:

Figure 5 .

 5 Figure 5.4 (a) The JV characteristics of P3HT:PC71BM based OPV devices processed from various solvents without DPE, and (b) with DPE.

Figure 5 . 5

 55 Figure 5.5 JV curves of P3HT:EH-IDTBR based OPVs processed from various solvents.

  polymer:fullerene blends is improved when fluorine atoms are introduced into the polymer backbone. 173 As a consequence, fluorinated polymers led to a significant increase in the PCE of BHJ solar cells. In 2014, T. L. Nguyen et al. synthesized for instance an efficient fluorinated copolymer, poly[(2,5-bis(2-hexyldecyloxy)phenylene)-

  In 2018, O. A.Ibraikulov et al. has reported a study of a series of fluorinated co-polymers with different numbers of fluorine atoms. Efficiencies over 10% could be reached on 12 mm 2 -sized devices, elaborated from hot 1,2-dichlorobenzene (o-DCB) solutions, when using a bi-fluorinated copolymer, named PF2, as electron donor and PC71BM as electron acceptor. 174 PF2 exhibits outstanding characteristics, such as well-adjusted frontier orbital energy levels, excellent light-harvesting capabilities, high out-of-plane charge transport properties together with a high morphology robustness upon blending, that translate into high PCE.174 Up to recently, PF2-based OPV devices have been prepared using toxic o-DCB, which limited the large-scale application of PF2 devices. In 2019 however, we succeeded to use non-halogenated o-xylene (OX) and1,2,4-trimethylbenzene (TMB)

Figure 6 . 1

 61 Figure 6.1 The chemical structures of donor PF2 (side chain: R1) and KNSF2 (side chain: R2).

Figure 6 .

 6 Figure 6.2 shows the normalized UV-vis absorption spectra of pure PF2 and KNSF2 in diluted o-DCB solution at different temperatures and in thin films. At room temperature, the peak positions of the absorption bands in the PF2 solution were 440,

Figure 6 .

 6 Figure 6.2 UV-Vis absorption spectra of (a) PF2 and (b) KNSF2 in solution as a function of temperature and in thin film.

Figure 6 .

 6 3 c shows the position of KNSF2 and PC71BM in Hansen solubility space, exhibiting only a partial overlap of both solubility spheres. For KNSF2 and PC71BM, the good solvent should have HSPs located in the overlapping part in HSP solubility space. The work on KNSF2:non-

Figure 6 . 3

 63 Figure 6.3 The position of (a) PF2:PC71BM, (b) PF2:PEH-IDTBR and (c) KNSF2:PC71BM in Hansen space.

3 .

 3 4< δP < 5.4, and 2.4 < δH< 4.4, respectively. The junction values of PF2:EH-IDTBR are19.0, 4.1, 3.4 for δD, δP and δH, therefore the target ranges of HSPs are set to 18< δD < 20, 3.1< δP < 5.1, and 2.4 < δH < 4.4, respectively. The position of PF2 and EH-IDTBR in the HSP solubility space can be found in Figure6.3b. Again, as the solubility spheres of PF2 and EH-IDTBR fully overlap, the solubility requirement can be satisfied with RED <1 for PF2 only.

  2, the experimental values for the boiling point, vaporization enthalpy, density, and viscosity are relatively close for o-DCB. For the boiling point the target range for the alternative solvent is set to [373 K, 473 K] 151,160 , while for the vaporization enthalpy, density, and viscosity, the target ranges are [35 kJ/mol, 55 kJ/mol], [0.8 g/cm 3 , 1.5 g/cm 3 ], and [0.5 mPa/s, 1.5 mPa/s] respectively. The third step is the selection of predictive models, which are the same as those used for the P3HT-based blends, and the list of predictive models can be found in Appendix 9.1. The fourth step is definition of the global performance function. The parameter used by IBSS®CAMD include wp, σL, and σR, which are defined in the same

  ) and a low match to the target values of HSPs, for instance the ProPerfp of δH is 0. The RED of PF2 in AN is 1.03, meaning that AN is located in the boundary of the solubility sphere of PF2. p-Cymene (PC) is similar with AN, which is located in the boundary of the solubility sphere of PF2 (RED=1.03, Ra=4.10) leading to a low ProPerfp value of Ra (ProPerfp-Ra= 0.18). The ProPerfp values of δD and δP are 0.01 and 0.02, respectively, a poor match with the target HSPs. AN and PC should therefore provide a poor solubility to PF2, as confirmed by solubility experiments with a PF2 concentration of 4mg/ml.Figure 6.4 shows pure PF2 solutions in PC and AN stirred overnight at 80 o C. As a consequence, PX is the only remaining candidate solvent for PF2:PC71BM blends and PF2:EH-IDTBR blends.

Figure 6 . 4

 64 Figure 6.4 Pictures of pure PF2 solutions (a) in PX, (b) in AN and (c) PC stirred overnight at 80 o C.

  solvents with a GloPerf values over 0.9 for PF2:EH-IDTBR blends are shown in table6.6. The full property values together with the ProPerf values of solvents whose GloPerf values are greater than 0.9 are presented in Appendix 9.11 (for PF2:PC71BM blends) and Appendix 9.12 (for PF2:EH-IDTBR blends). Interestingly, PX, which were included in the list of pre-selected solvents (see above) also occurs in the list of designed solvents, pointing out the consistency between both methods. 8 identical designed solvents are found for both donor:acceptor blends: benzyl methyl ether (BME), methyl phenethyl ether (MPE), PX, N,N-Dimethylaniline (DMA), 1-(3-Buten-2-yl)-4-methylbenzene (1-4-MB), 4-methylstyrene (4-MS), 1-phenyl-2-butene (1-P-2-B), and 1-Methyl-2-(2-propyn-1-yl)benzene (1-M-2-B). Allylbenzene (AB), 3butenylbenzene (3-BTB), 4-ethynyltoluene (4-ET), 2-methylstyrene (2-MS), and phenylallene (PA) are only for PF2:EH-IDTBR blends. These candidate solvents need to be further screened taking into account non-evaluated properties.

  AN, GTE, DBE, TPO and d-LM are located in the boundary of the solubility sphere of KNSF2, providing a bad miscibility with KNSF2. Importantly, GTE and DBE are located outside the solubility sphere of PC71BM, indicating that PC71BM is not miscible with them. AN, d-LM and TPO have a large Ra with PC71BM, indicating low miscibility with PC71BM.

  Since KNSF2:PC71BM OPV devices will be prepared after completion of selection of alternative solvents, this paragraph focuses on PF2-based devices. One reason is the solubility of PC71BM in the solvent candidates limited green-processing of KNSF2based OPVs. More efficient acceptors need to be used in the KNSF2:acceptor-basedOPVs. An inverted OPV structure is used in this study. Reference devices processed from o-DCB solutions were also studied. For PF2:PC71BM based devices, the active layer was prepared from a mixture solution of PF2 and PC71BM with an overall concentration of 10 mg/ml. The ratio of donor and acceptor is 1:1.5. The blend films were processed from hot o-DCB and PX/DPE solutions (≈ 100 o C) and spin-coated onto substrates previously heated at the same temperature. For the PF2:EH-IDTBR based devices, the active layer was composed of PF2:EH-IDTBR blends with a 1:1 weight ratio from hot o-DCB and PX solutions that were annealed and stirred overnight at 100 o C in nitrogen ambient. The overall concentration of PF2:EH-IDTBR blends is 8mg/ml.The photovoltaic properties of the devices are recorded in Figure6.4 and Table6.8. PF2 devices worked efficiently in inverted devices without any post-treatment. The devices processed from PX/DPE mixture solvents showed an impressive maximum PCE of 9.47%. In this study, 3% of DPE was added as processing additive to improve the morphology of the active layer. The slightly lower efficiency compared to devices processed from o-DCB is caused by the lower Jsc (16.5 mA cm -2 ) for PX processed devices. The latter may be the consequence of a less optimal blend morphology (larger domain sizes). The high FF of 76.5% clearly points out excellent charge carrier extraction. Interestingly, the devices processed by PX could be manufactured at a lower temperature (70 o C) than from o-DCB solutions. We attribute this behavior to the lower viscosity of PX: the active layer can be spin-coated at a lower processing temperature for achieving a similar thickness than with o-DCB.

Figure 6 .

 6 Figure 6.4 a) The J-V curves of PF2 from o-DCB and PX/DPE solutions, and b) the JV curvers of PF2 based devices processed from PX/DPE mixture solvents at different processing temperature.

Figure 6 . 5

 65 Figure 6.5 The JV charatistics of PF2:EH-IDTBR based OPVs processed from o-DCB and p-xylene.

4 :

 4 The list of selected existing solvents.

  Une cellule photovoltaïque organique à base d'une hétérojonction donneuraccepteur distribuée en volume (HJV) est un composant à couches minces, dont la couche principale est constituée d'un mélange de deux matériaux semi-conducteurs organiques : un matériau donneur d'électrons (D) et un matériau accepteur d'électrons (A). Les molécules D et A sont déposées par une technique d'impression (ex : spin-coating) à partir d'une solution organique et forment l'HJV. Pendant le dépôt, les deux matériaux se séparent en phase et forment des domaines plus ou moins purs et de taille moyenne pouvant aller de quelques nanomètres à quelques dizaines de nanomètres. La conversion de la lumière en électricité se fait en quatre étapes consécutives : (1) absorption de la lumière et génération d'excitons par l'HJV, (2) diffusion des excitons jusqu'à l'interface D/A (3) séparation des excitons en porteurs de charge libres, et (4) transport de charges vers les électrodes. Dans une HJV, la dissociation des excitons en charges libres a lieu uniquement à l'interface D/A. Elle est engendrée par la différence entre respectivement les affinités électroniques et les potentiels d'ionisation des matériaux D et A. Par conséquent, il est nécessaire que les excitons soient photo-générés à une distance de l'interface D/A inférieure à leur longueur de diffusion (typiquement de l'ordre de qqs nanomètres). Après génération, les porteurs de charge dérivent vers les électrodes respectives sous l'influence d'un champ électrique interne. Cette dérive nécessite l'existence d'un chemin continue (percolation) pour chaque type de domaine (D ou A). La morphologie de la couche active à l'échelle nanométrique est par conséquent un facteur clé pour l'efficacité de génération et de collecte des charges libres, et bien sûr pour l'efficacité de conversion énergétique d'une cellule PVO. Les propriétés du solvant utilisé pour le dépôt de l'HJV influencent considérablement la morphologie du film et doivent être prises en compte lors de la recherche de solvants organiques. La séparation de phases entre D et A se produit pendant l'évaporation du solvant et détermine la taille des domaines D et A. Le phénomène est complexe car il dépend non seulement des propriétés intrinsèques des composants D et A telles que le degré de cristallinité, leur miscibilité et les propriétés de cristallisation auto-limitante, mais aussi des conditions expérimentales de mise en oeuvre (tel que la nature du solvant ou des additifs éventuels, les traitements thermiques ou recuits en phase vapeur du solvant post-dépôt,…). Deux aspects sont à prendre en compte pour obtenir la morphologie HJV adéquate : la séparation de phases entre domaines donneur et accepteur et l'organisation moléculaire au sein des domaines. Idéalement, la séparation de phase entre les matériaux donneur et accepteur dans la HJV doit conduire à des tailles de domaine de l'ordre de la longueur de diffusion des excitons, minimisant ainsi la recombinaison des excitons et permettant la dissociation des excitons en charges libres.

  Dans le cas des dispositifs élaborés à partir d'encres, la morphologie de la couche active dépend fortement de propriétés thermodynamiques et cinétiques liées au solvant. Les propriétés thermodynamiques sont associées à diverses propriétés physico-chimiques des matériaux donneurs et accepteurs et des solvants, telles que leurs interactions intermoléculaires, leur miscibilité ou encore leurs diagrammes de phases. La cinétique du séchage du film influence fortement la morphologie et dépend de propriétés telles que le point d'ébullition ou la pression de vapeur du solvant. Actuellement, le choix d'un solvant pour les dispositifs PVO est principalement basé sur sa capacité à solubiliser les semi-conducteurs organiques qui forment l'HJV et son point d'ébullition. De nombreuses études ont porté sur l'influence de la solubilité des D et A dans le solvant sur la formation d'agrégats de dérivés du fullerène (A). L'étude de Brabec et al. 13 d'un mélange MDMO-PPV : PC61BM a ainsi été l'une des premières à apporter des éclaircissements sur la relation entre solubilité et morphologie à l'échelle nanométrique. La morphologie des films minces a en particulier pu être corrélée à la limite de solubilité du PC61BM dans divers solvants. De plus, la morphologie du film mince est fonction de la cinétique de séchage. Ainsi, en utilisant des solvants très volatils, la cinétique d'évaporation est plus rapide que la cinétique de cristallisation. Dans ce cas, la morphologie résultante est loin de celle observée dans des conditions d'équilibre. Les effets de la cinétique de séchage sur le degré d'agrégation des chaînes de polymères ont été largement étudiés en utilisant diverses techniques de dépôt et de solvants ayant des points d'ébullition différents. Dans le cas du P3HT:PC61BM, un solvant à point d'ébullition élevé permet d'obtenir une meilleure efficacité de conversion sans avoir recours à un traitement thermique. En outre, il a également été démontré que le choix du solvant avait un impact sur d'autres aspects de la morphologie de la HJV, tels que la séparation de phase verticale et l'orientation des chaînes de polymères. Pour les mélanges P3HT:PC61BM, les solvants à point d'ébullition élevé sont également préférables afin de laisser le temps aux chaînes de polymères de s'auto-organiser. Un solvant unique aux propriétés appropriées pourrait en principe suffire pour atteindre une morphologie adéquate. Cependant, comme le nombre de solvants pouvant solubiliser simultanément les deux composants, D et A, est souvent limité, d'autres méthodes sont nécessaires. Ainsi, l'ajout d'additifs dans la solution principale s'est avéré être un moyen complémentaire très efficace pour contrôler la morphologie du film mince. Par additif on désigne un solvant qui est introduit en petite proportion (généralement quelques % en volume) dans le solvant hôte utilisé pour solubiliser les matières actives. Pour les mélanges polymères:petites molécules, les additifs modifient souvent la séparation de phases et la cristallisation du polymère en dissolvant sélectivement les petites molécules (ex : dérivés de fullerène). Néanmoins, l'impact de l'additif sur la morphologie dépend du mélange D:A en question. Dans certains cas, les additifs ont augmenté le degré de séparation de phase, alors que dans d'autres c'est l'inverse. Tout dépend des propriétés physicochimiques de l'additif et de ces interactions avec les molécules photo-actives.

  de solvants et/ou d'additifs. Compte tenu de tous ces paramètres et de la grande variété de solvants et d'additifs existants, le choix de la formulation optimale en utilisant une approche de type essais -erreurs nécessite la formulation de nombreux mélanges de matériaux et la fabrication de nombreux dispositifs PVO. Par conséquent, l'optimisation de la morphologie peut être extrêmement coûteuse et prendre beaucoup de temps. Il est donc nécessaire de trouver des méthodes plus efficaces pour choisir les formulations adaptées. Une méthode récente repose sur la théorie de la solubilité de Hansen. Cette théorie utilise trois paramètres de solubilité (les « paramètres de Hansen » ou HSP) pour décrire les interactions entre soluté et solvant. Les HSP ont été largement utilisés pour les solvants dans l'industrie des revêtements, mais ils n'ont émergé que récemment dans le domaine de l'électronique organique. La solubilité d'un matériau donné peut être évaluée expérimentalement pour un nombre déterminé de solvants et permet de classer ces derniers comme « bon » ou « mauvais » solvant. Ces résultats permettent ensuite de définir la sphère de solubilité du matériau séparant les bons solvants (situés à l'intérieur de la sphère) des mauvais en fonction de leurs paramètres HSP. Cependant, trouver un solvant adéquat pour le PVO est un problème complexe, qui nécessite de prendre en compte de multiples autres propriétés, au-delà de la solubilité. Pour la plupart d'entre elles l'impact sur les propriétés du dispositif est difficilement prévisible et mais doit être prise en compte lors du processus de sélection. Il y a donc un intérêt considérable à développer des méthodologies plus systématiques pour assister la sélection des solvants alternatifs. L'« ingénierie inverse » est l'une des voies possibles et fait l'objet principal de cette thèse. L'ingénierie inverse suit les préceptes de la conception moléculaire assistée par ordinateur (CAMD) en définissant d'abord un ensemble de valeurs cibles pour un groupe de propriétés physico-chimiques sélectionnées et en dirigeant la construction in silico des structures moléculaires qui les satisfont le mieux. L'outil IBSS®CAMD 14 est un outil numérique innovant dédié à la conception de bio-solvants. Le principal avantage d'IBSS®CAMD réside dans la construction de structures moléculaires en imposant des bio-blocs comme fragments de départ pour assurer le développement de bio-solvants. IBSS®CAMD peut être utilisé selon deux modes différents pour la sélection de solvants : (a) pour évaluer les performances d'une liste de solvants existants présélectionnés, ou (b) pour concevoir de nouvelles molécules et évaluer leurs performances. Les deux modes sont utilisés dans cette thèse, avec un focus sur les solvants bio-sourcés, car ceux-ci devraient présenter de plus faibles impacts sur la santé et l'environnement.

5 .

 5 Etudes de casDans le cadre de cette thèse, des solvants durables ont été sélectionnés à l'aide de l'outil IBSS®CAMD pour cinq systèmes D:A. Les structures chimiques des trois polymères (P3HT, PF2 et KNSF2) et des deux petites molécules (PC71BM et EH-EDTBR) étudiés sont illustrées à la figure 1. Le P3HT est un polymère donneur d'électrons bien connu et largement étudié pour les applications PVO. Il constitue une bonne référence pour tester notre méthodologie. En outre, malgré les nombreuses données de la littérature sur les cellules solaires à base de P3HT, seuls quelques exemples ont traité la question des solvants verts. L'EH-IDTBR est un accepteur non-fullerène prometteur qui a récemment suscité beaucoup d'intérêt pour le remplacement des dérivés du fullerène et l'amélioration du PCE des dispositifs basés sur le P3HT. Nous avons donc choisi le P3HT:EH-IDTBR comme deuxième exemple pour illustrer comment l'IBSS®CAMD s'applique à différents matériaux et ouvre la voie à une approche plus polyvalente et plus efficace pour identifier les solvants de substitution. Le PF2 et le KNSF2 sont deux copolymères di-fluorés dont les propriétés sont particulièrement appropriées pour le photovoltaïque. La fluoration de polymères conjugués a été utilisée initialement pour ajuster les niveaux d'énergie des orbitales frontières. De manière inattendue, d'autres effets positifs des polymères fluorés ont été découverts. Par exemple, des orientations mixtes "face on" et "edge on" du squelette des polymères fluorés par rapport au substrat du dispositif ont été fréquemment observées et engendrent une mobilité des trous hors plan très élevée. En outre, il a été constaté que la pureté des domaines dans les mélanges polymère:fullerène est améliorée lorsque des atomes de fluor sont introduits dans le squelette du polymère. En conséquence, les polymères fluorés ont conduit à une augmentation significative du RCE des cellules solaires HJV. En 2018, O. A. Ibraikulov et al. 15 ont publié une étude portant sur une série de copolymères fluorés de même structure conjuguée mais avec différents nombres d'atomes de fluor, dont le PF2. Des rendements supérieurs à 10 % ont pu être atteints avec le PF2 comme donneur d'électrons et le PC71BM comme accepteur en élaborant des dispositifs à partir de solution d'o-CDB chauffée à 90°C. Le PF2 présente en effet des caractéristiques exceptionnelles, telles que des niveaux d'énergie des orbitales frontières optimaux, d'excellentes capacités de collecte de la lumière, des propriétés de transport de charge élevées et une morphologie en film mince adéquate, qui se traduisent par un RCE élevé. L'influence des "chaînes latérales" des polymères conjugués sur leurs propriétés opto-électroniques et photovoltaïques a également suscité un intérêt considérable. En effet, les chaînes latérales ne sont pas seulement nécessaires aux polymères conjugués pour les rendre solubles et manipulables sous forme d'encre, elles ont également un impact sur l'auto-assemblage moléculaire, la morphologie des mélanges D:A et donc sur les performances photovoltaïques. Ainsi, une étude récente a montré l'impact de chaînes siloxanes sur l'organisation moléculaire des polymères conjugués à base d'isoindigo. Le KNSF2 est un polymère de même coeur conjugué que le PF2, mais avec des chaines siloxanes linéaires (Figure 1). L'objectif de notre travail a été d'évaluer dans quelle mesure les chaînes siloxanes influencent les propriétés de solubilité du polymère et peuvent modifier le choix de solvants alternatifs.

Figure 1 .--

 1 Figure 1. The chemical structures of donors and acceptors.

  Une nouvelle méthode basée sur l'ingénierie inversée et reposant sur l'outil numérique IBSS®CAMD a été utilisée avec succès pour concevoir et sélectionner des solvants alternatifs non-toxiques et durables pour les dispositifs photovoltaïques organiques, en remplacement des solvants toxiques actuels (CB, o-DCB, CF...). Cette approche a nécessité l'identification des paramètres des solvants ayant un impact fort sur les performances des dispositifs photovoltaïques, leur traduction en propriétés physico-chimiques et la définition de valeurs cibles que doivent atteindre les solvants alternatifs. En résolvant un problème d'optimisation multi-objectifs avec un outil de conception moléculaire assistée par ordinateur (IBSS®CAMD), les solvants alternatifs ont été classés selon une valeur de performance globale, qui évalue la correspondance du comportement des solvants alternatifs avec un ensemble de propriétés physicochimiques cibles multiples. En explorant la diversité des structures moléculaires, l'approche de l'ingénierie inverse élargit considérablement la liste des solvants candidats par rapport aux méthodes plus empiriques de type essais-erreurs et peut donner lieu à des solvants présentant de meilleures performances.

78,79 2.4.2 Open Circuit Voltage (VOC)

	The open-circuit voltage (VOC) represents the maximum voltage that a solar cell
	can provide to an external circuit. Under open circuit conditions and steady state
	illumination, free charge carriers will accumulate at their respective electrodes,
	generating a potential difference which cancels out the built-in potential. Under this
	condition, charge carrier generation and recombination exactly compensate, therefore,
	no net current is flowing. If the contacts are ohmic, VOC is dependent on the separation
	between the electron (EFn) and hole (EFp) quasi-Fermi energy levels:

Table 2

 2

	.1. The

Table 2 .

 2 1 The list of processing solvents and additives used in this thesis.

	Solvents	Purity
	1,2-Dichlorobenzene	≥99%
	p-Xylene	≥99%
	Anisole	99.7%
	Terpinolene	≥85% (GC)
	2-Methylanisole	99%
	p-Cymene	99%
	Diphenyl Ether (additive)	99%

Table 3 .

 3 1 Solubility of PC61BM in various solvents.

	Solvents	Solubility limited (mg/mL)	References
	o-DCB	42~107	87-89
	CF	24~27	60,87,90,91
	CB	25~59.5	60,87,90,91
	Toluene	9~15.6	60,87,90,91
	Carbon disulfide (CS2)	~207	87
	Trichloroethylene	~41.8	87
	Mesitylene	29~48.1	60,88

Table 3 .

 3 2 Solubilities of BDT-2T-DCV-Me and BDT-2TCNAB in CF, and PCEs of the OPVs devices based on BDT-2T-DCV-Me: IDIC films and BDT-2T-CNAB: IDIC films under the illumination of AM 1.5G, 100 mW cm -2 . 87

	Materials	solvents	Solubility (mg/mL)	PCE (%)
	BDT-2T-DCV-Me	CF	1.7	1.56

Table 3 .

 3 3 Effects of processing additive on the PCE of several type of donor/acceptor OPVs.

				PCE (%)
	Donor/acceptors Host solvent Processing additive
				Without additives With additives
		CB	OT	0.29	2.9 89
	P3HT/PC61BM			0.56	3.02 103
		o-DCB	1.6-hexanedithiol	1.0	2.8 102
		CB	NB	0.61	3.04 108
	P3HT/PC71BM	Toluene	Ethyl	0.80	4.11 113
			benzenecarboxylate
		CB	DIO	2.9	6.9 114
	PTB7/PC71BM				8.22 115
		o-Xylene	p-Anisaldehyde (AA)	0.9	7.4 114
		Toluene	NMP		11.28 116
	PBQ-4/PC71BM	Anisole	DPE	3.60	8.37 99
	PDTSTPD/PC71BM	CB	DIO	1.37	7.32 117
	PBDT-TS1/PC71BM	o-DCB	DIO	6.94	9.15 97
		o-Xylene	NMP	2.78	9.11 97

Yao et al. introduced

OT into the host solvent CB to study how the additive

Table 3 .

 3 4 Examples of alternative solvents for several type of donor/acceptor OPVs by trial and error approach.

	Donor/acceptor system	Alternative solvents/additives	PCE (%)	Ref.
	PTB-EDOTS/ITIC	MeTHF	10.18	106
		2-MA	9.6	95
	PTB7/PC71BM	o-xylene/DIO	7.1	119
		Thiophene/DPE	8.92	98
	PBDTTT-C/oo-2PDIate	Anisole	2.24	120
	BDTSTNTTR/PC71BM	CS2	11.53	121
	BTR/PC71BM	Toluene/DPE	6.56	122
	FTAZ/IT-M 9.1 T1/BTP-4F-12 TMB o-xylene 15.3 TMB 14.9	124 124
		Tetrahydrofuran	16.1	124
	PBBDTBT/PC71BM	o-xylene/NMP	4.57	109

Table 3 .

 3 5 Examples of alternative solvents for several type of donor/acceptor OPVs by HSPs theory.

	Donor/acceptor system	Alternative solvents/additives	PCE (%)	Ref.
		Toluene/NMP	11.28	116
	PTB7/DR3TSBDT/PC71BM
		o-Xylene/NMP	11.75	116
		Thiophene	3.9	129
	DPP(TBFu)2/PC71BM	CS2	4.2	129
		Trichloroethylene	4.2	129
		o-Xylene/1-MN	4.99	127
	P3HT/IDTBR	p-Cymene/p-Bromoanisole	5.30	127
		2-MA	5.41	127
	PIDT-FQ-T:PC71BM	o-Xylene/ 1,2-Dimethylnaphthalene	7.18	128
	P3HT:IC60BA	Toluene/1-Methylnaphthalene	6.27	128
	P3HT:PC60BM	1,2-Dichlorobenzene/Dimethyl phthalate	3.20	104
	3

.3.3 IBSS® CAMD The

  Reverse engineering follows the Computer Aided Molecular Design (CAMD)precepts by first defining a set of target values for a group of selected physicochemical properties and by leading the construction in silico of the molecular structures that best satisfy them. The IBSS® CAMD tool is an innovative CAMD tool dedicated to the design of biosolvents.130 The main advantage of IBSS® CAMD lies on the construction of molecular structures by imposing bio-based building blocks as the starting fragment to ensure the development of biosolvents. Several applications of IBSS® CAMD appeared in the open literature to find new biosolvents as pure compound: substitution of acetone and methyl ethyl ketone (MEK) by furfural derivatives to

trial and error method and HSPs theory are common methodologies for solvent selection in the OPV field. However, they are both time-consuming and may miss good solvent candidates. Searching for new solvents is indeed a complex problem, which requires considering multiple properties, such as solubility, viscosity, safety, sustainability, toxicity, where most of these may impact the device properties in a rather unpredictable way. Multiple properties of the candidate solvents need therefore to be taken into account simultaneously during the selection process. There is thus a considerable interest to develop more systematic methodologies to achieve the alternative solvent selection in a more efficient and accurate way. A possible route to achieve this goal is based on the concept of reverse engineering. dissolve two epoxy resin prepolymers, bisphenol A diglycidyl ether (DGEBA) and triglycidyl p-aminophenol ether (TGPA)

131

and glycerol derivatives to solubilize nitrocellulose 132 . IBSS® CAMD was also applied to generate ricinoleic acid derivatives aiming to find new biolubricants from a biomass feedstock.

133

Moreover, since the efficiency of a pure solvent can be improved thanks to the thermodynamic synergism of forming binary or multicomponent mixtures, special attention has been devoted to the use of azeotropic mixtures that behave as a pure compound at a given composition.

For instance, new coolant azeotropic mixtures for heat-exchange devices in aerospace applications have been recently identified by using IBSS®CAMD tool 134 . It is worth to notice however that best proposed structures might be virtually excellent but infeasible at an industrial scale. Therefore, even if new molecular structures are identified by IBSS®CAMD as promising candidate, commercially available compounds are generally preferred to replace hazard solvents in the industry.

Table 4 .

 4 As an example, the N-phenyl-1,4-benzenediamine molecule was decomposed by the group contribution method, as shown in Figure4.1. The boiling point of N-phenyl-1,4-benzenediamine can be estimated according to the data given in Table 4.1, leading to an estimated boiling point, 𝑇 𝑏 𝑒𝑠𝑡 , that matches well the experimental value. The related parameters including 𝑛 1𝑘 , 𝐴 𝑘 , 𝑛 2𝑘 , 𝐵 𝑘 , 𝑛 3𝑘 , 𝐶 𝑘 , and adjustable parameters for the target properties are taken from Ref 142.

	1 Estimation of normal boiling point of N-phenyl-1,4-benzenediamine. 142
				Molecular structure
	N-phenyl-1,4-benzenediamine
	(experimental value:
	𝑇 𝑏 = 627 K)
	First order groups	𝑛 1𝑘		𝐴 𝑘	∑ 𝑛 1𝑘 𝐴 𝑘
	X(C-NH2)	1		3.8298
	X(C-NH)	1		2.9230
					15.8281
	X(C)	1		1.5468
	X(CH)	9		0.8365
	Second order groups	𝑛 2𝑘		𝐵 𝑘	∑ 𝑛 2𝑘 𝐵 𝑘
	X(1,4-substituted aromatic ring)	1		0.1007	0.1007
	Third order groups	𝑛 3𝑘		𝐶 𝑘	∑ 𝑛 3𝑘 𝐶 𝑘
	X(C-NH-C)	1		0.5768	0.5768
	𝑃 = ∑ 𝑛 1𝑘 𝐴 𝑘 + ∑ 𝑛 2𝑘 𝐵 𝑘	+ ∑ 𝑛 3𝑘 𝐶 𝑘	= 15.8281 + 0.1007 + 0.5768 = 16.5056
	𝑘∈𝐺1	𝑘∈𝐺2	𝑘∈𝐺3
	𝑇 𝑏
			(error = 627-624 = 3K)

𝑒𝑠𝑡 = 𝑐 × 𝑙𝑛(𝑃) = 624𝐾, calculated with the universal constant for the boiling point c = 222.543.

Table 4 .

 4 2 Examples of available basic groups and their encoding in IBSS®CAMD.

  . Typical examples are: high solubility power, Newtonian fluid, low energy consumption, good capillarity, safety, non-toxicity. In our case, the goal is to replace toxic solvents during processing with safer alternative solvents, in keeping with legislation (for instance, with the Registration Evaluation, Authorization of Chemical Substances regulations (REACH) (EC/1907/2006) implemented by the EU on June 1st 2007), environmental protection and customer needs. The translation of such solvent functionalities into physicochemical properties that can be revaluated by IBSS® CAMD tool is further required.

Table 5

 5

	.1 The target properties, corresponding values for P3HT:PC71BM blends and P3HT:EH-IDTBR
		blends. ( a P3HT:PC71BM blends, and b P3HT:EH-IDTBR blends.)
	Functionalities	Target properties	Target values	Parameters
				wp	𝜎 𝐿	𝜎 𝑅
		𝛿 𝐷 (MPa) 1/2	18< 𝛿 𝐷 < 20 a	1	0.48	0.21
		𝛿 𝑃 (MPa) 1/2	17.5< 𝛿 𝐷 <19.5 b 4< 𝛿 𝑃 <6 a	1	0.56	0.48
	Solubility	𝛿 𝐻 (MPa) 1/2	3.5< 𝛿 𝑃 <5.5 b 3.5< 𝛿 𝐻 < 6	1	0.24	0.48
		𝑅 𝑎 (MPa) 1/2	𝑅 𝑎 <3	3		0.84
		RED	<1	2		0.28
		Boiling point (Tb/K)	373< BP<473	2	8.4	10.6
	Film drying	Vaporization enthalpy	40<∆Hvap < 55	1	1.7	1.7
		(∆Hvap kJ/mol)
	Film processing/	Density (kg/m 3 )	800< ρ <1500	1	19.8	19.8
	Newtonian fluid	Viscosity (mPa/s)	0.5< μ <1.5	1	0.13	0.13
	Safety	Flash Point (Tf/K)	> 296	1	2.8
	Liquid state	Melting point (Tm/K)	<283	0.5		4.2

Table 5 .

 5 2 The physicochemical properties and corresponding values of o-DCB and CB.

		Property values
	Physicochemical properties
		o-DCB	CB
	Non-polar interactions (δD, MPa 1/2 )	19.2	19.0
	Polar interactions (δP, MPa 1/2 )	6.3	4.3
	Hydrogen bonds (δH, MPa 1/2 )	3.3	2.0
	Distance (Ra, MPa 1/2 ) with P3HT	2.83	3.19
	Relative energy difference (RED) with P3HT (defined by Ra/Ro)	0.64	0.68
	Boiling Point (Tb, K)	453	405
	Evaporation enthalpy (∆Hvap, kJ/mol)	49.08	40.76
	Density (ρ, g/cm 3 )	1.31	1.11
	Viscosity (η, mPa s)	1.30	0.76
	Flash Point (Tf, K)	339	301
	Melting Point (Tm, K)	256	228

Table 5

 5

	-3.

Table 5 .

 5 3 Group contribution method-based property models and Universal constants for the target properties.

	Property (X)	𝑃 =		Universal constants	Refs
	δD (MPa 1/2 )	𝛿 𝐷
	δP (MPa 1/2 )	𝛿 𝑃
	δH (MPa 1/2 )	𝛿 𝐻
	Boiling Point (Tb, K)	𝐸𝑋𝑃(𝑇 𝑏 𝑇 𝑏0 ⁄ )	222.543
	Evaporization enthalpy (∆Hvap, kJ/mol)	𝐻 𝑣𝑎𝑝 -𝐻 𝑣𝑎𝑝0	11.733
	Molecular volume (Vm, cm 3 /kmol)	𝑉 𝑚 -𝑉 𝑚0		0.0160
	Viscosity (η, mPa s)	𝑙𝑛𝜂
	Flash Point (Tf, K)	𝑇 𝑓 -𝑇 𝑓0		170.7058
	Melting Point (Tm, K)	𝐸𝑋𝑃(𝑇 𝑚 𝑇 𝑚0 ⁄	)	147.450

Table 5 .

 5 Molecular design. A total of 10102 designed solvents were evaluated by IBSS®CAMD, leading to a significantly larger number of solvents with a high global performance factor. The purpose of using the IBSS®CAMD tool in OPVs is to find alternative solvents to replace toxic halogenated solvents. Therefore, 14 designed solvents with high 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 values over 0.9 for further investigation, which were listed in Table5.6. The complete predicted values of solvents whose 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 values are larger than 0.9 are given in Appendix 9.7 together with the performance factors. 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 value of 1, indicating that the estimated values of both have a perfect match with the target values. The next best ranked solvent is 4-

	5 The candidates provided for P3HT:EH-IDTBR
	blends by IBSS®CAMD
	with
	a
	GloPerf
	>
	0.6.
	.(/:
	non-available
	data)

Methylphenyl Vinyl Ether (4-MPVE) with a 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 of 0.998, because the boiling point (474 K) and ΔHvap (55.26 kJ/mol) of 4-MPVE are slightly larger than the corresponding target values resulting in a non-perfect match. Interestingly, AN, which were included in the list of pre-selected solvents (see above) also occurs in the list of designed solvents among the best ranked solvent, pointing out the consistency between both methods. All designed solvents (listed in

Table 5.6)

show a 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 of 1 for RED, meaning these candidates can dissolve P3HT:PC71BM blends.

Methyl Anisole (2-MA) and Methyl Benzoate (MB), have been retained. In addition, the chemical stability in air of alternative solvents is another important non-evaluated

Table 5 .

 5 PVE) is susceptible to moisture deterioration, therefore it needs to be stored and handled under nitrogen. Thus, PVE has also been avoided. At last, among the three remaining designed solvents, AN, 2-MA and MB, MB has a higher boiling point (470 K) and a larger ΔHvap (55.6 KJ/mol). Therefore, taking into account the energy consumption for film drying, we considered 4-ET, AN and 2-MA as the better options

	6 List of the best solvent candidates selected from the results of molecular design provided by
		IBSS®CAMD. (Y: yes, N: no, NA: non-available data)
	Candidates	CAS	𝐺𝑙𝑜𝑃𝑒𝑟𝑓 Commerciality Cost (€/g)	Stable (at room temperature)
	4-Ethynyltoluene	766-97-2	1	Y	9.3	N
	3-Ethylcyclopentane-	NA	1	N	NA	N
	1-carbaldehyde
	4-Methylphenyl vinyl	1005-62-5	0.998	N	NA	NA
	ether
	Anisole	100-66-3	0.997	Y	0.4	Y
	Allyl phenyl ether	1746-13-0	0.989	Y	1.9	Y
	Phenyl vinyl ether	766-94-9	0.978	Y	4230	N
	4-Acetylcyclohexene	7353-76-6	0.977	Y	1961.6	NA
	2-Methyl anisole	578-58-5	0.946	Y	0.7	Y
	2-Vinyl anisole	612-15-7	0.931	Y	39.8	N
	Methyl benzoate	93-58-3	0.923	Y	0.9	Y
	4-Methoxystyrene	637-69-4	0.923	Y	20.0	Y
	(1R,2R)-2-
	Vinylcyclohexanecarb	NA	0.920	N	NA	N
	aldehyde
	3-Cyclohexen-1-yl	15766-93-5	0.916	Y	3712	NA
	methyl ether
	Cyclopentyl formate	62781-99-1	0.901	N	NA	N

4-Ethynyltoluene (4-ET) is an "ideal" solvent with a GloPerf value of 1, indicating that the estimated values have a perfect match with the target values. Phenyl Vinyl

Table 5 .

 5 7 OPV device parameters of P3HT:PC71BM based devices fabricated from various solvents.

	Processing	Processing	Voc (mV)	Jsc (mA/cm 2 )	FF (%)	PCE (%)	Thickness
	solvents	temperature					(nm)
	o-DCB	( o C) 80	594±5	6.3±0.1	59.0±3	2.3±0.2	~100
	4-ET/DPE	100	575±3	7.2±0.2	61.5±2	2.6±0.1	~110
	4-ET	100	540±6	3.3±0.5	49.2±5	0.9±0.2	~110
	AN/DPE	100	575±3	7.4±0.1	62.9±1	2.7±0.1	~140
	AN	100	571±5	4.2±0.2	45.7±3	1.1±0.2	~140
	2-MA	100	587±2	8.3±0.1	64.5±1	3.1±0.2	~90
	PX/DPE	90	577±2	7.5±0.1	63.6±1	2.7±0.2	~130
	PX	90	585±5	4.5±0.3	50.7±2	1.1±0.3	~130
	PC/DPE	110	585±6	8.5±0.2	65.3±1	3.3±0.1	~120
	PC	110	555±7	5.0±0.3	42.8±4	1.2±0.2	~120
	TPO/DPE	110	606±6	5.5±0.2	57.3±2	1.9±0.2	~90
	TPO	110	645±8	3.5±0.2	41.8±2	1.0±0.1	~90
	LM/DPE	110	669±7	3.3±0.2	42.8±3	1.0±0.1	~100

Table 5 .

 5 8 The corresponding photovoltaic device parameters of P3HT:EH-IDTBR based devices fabricated from selected candidates.

	Processing solvents	Processing temperature ( o C)	Voc (mV)	Jsc (mA/cm 2 )	FF (%)	PCE (%)	Thickness (nm)
	CB	80	780±5	8.1±0.3	53.4±4	3.4±0.4	~120
	AN	80	752±3	9.2±0.2	65.6±2	4.55±0.1	~140
	PX	80	742 ±3	8.9±0.4	57.0±2	3.79±0.3	~150
	PC	90	749±6	8.9±0.3	65.3±1	4.42±0.1	~120
	TPO	90	787±5	7.8 ±0.1	58.8±1	3.59±0.1	~100
	LM	100	816±7	3.6±0.3	35.7±2	1.04 ±0.2	~100

Table 5 .

 5 9 Ra and RED values between various solvents and two acceptor materials.

		PC71BM			EH-IDTBR
	Processing solvents
		Ra	RED	Ra	RED
	o-DCB	2.50	0.30	2.11	0.35
	AN	4.52	0.54	2.24	0.37
	PX	4.61	0.55	2.85	0.47
	PC	6.74	0.80	3.93	0.64
	TPO	7.52	0.90	4.51	0.74

Table 6 .

 6 1 HSPs for PF2, KNSF2, PC71BM and EH-IDTBR.

	Materials	δD	δP	δH	R0
	PF2	19.2	3.9	2.8	4.0
	KNSF2	17.5	4.3	1.5	4.9
	PC71BM	20.2	5.4	4.5	8.4
	EH-IDTBR	18.8	4.4	4.3	6.1

Table 6 .

 6 2 The target properties, corresponding values for PF2:PC71BM, PF2:EH-IDTBR, and KNSF2:PC71BM. ( a PF2:PC71BM blends, b PF2:EH-IDTBR blends, and c KNSF2:PC71BM blends.)

					Parameter values
	Specifications	Target properties	Target values
				wp	𝜎 𝐿	𝜎 𝑅
			18.5< 𝛿 𝐷 < 20.5 a
		𝛿 𝐷 (MPa) 1/2	18< 𝛿 𝐷 < 20 b	1	0.48	0.21
			17.5< 𝛿 𝐷 < 19.5 c
	Solubility

Table 6 .

 6 3 The candidates provided for PF2:PC71BM by IBSS®CAMD with a GloPerf > 0.6.

	Properties	o-DCB	p-Xylene	Anisole	p-Cymene
	CAS	95-50-1	106-42-3	100-66-3	99-87-6
	GloPerf	1	0.931	0.724	0.693
	δD	19.5	18.6	18.1	17.4
	ProPerfp-δD	1	1	0.50	0.01
	δP	5.1	3.8	4.9	2.3
	ProPerfp-δP	1	1	1	0.02
	δH	3.1	1.6	6.1	2.4
	ProPerfp-δH	1	≈ 0	≈ 0	1.00
	Ra	1.37	1.70	4.12	4.10
	ProPerfp-Ra	1	1	0.17	0.18
	RED	0.34	0.42	1.03	1.03
	ProPerfp-RED	1	1	0.99	0.99

Table 6 .

 6 4 The candidates provided for PF2:EH-IDTBR by IBSS®CAMD with a GloPerf > 0.6.

	Properties	o-DCB	p-Xylene	Anisole	p-Cymene
	CAS	95-50-1	106-42-3	100-66-3	99-87-6
	GloPerf	1	0.931	0.758	0.714
	δD	19.5	18.60	18.1	17.40
	ProPerfp-δD	1	1	1	0.21
	δP	5.1	3.80	4.9	2.30
	ProPerfp-δP	1	1.00	1	0.13
	δH	3.1	1.60	6.1	2.40
	ProPerfp-δH	1	≈ 0	≈ 0	1
	Ra	1.37	1.70	4.12	4.10
	ProPerfp-Ra	1	1	0.17	0.18
	RED	0.34	0.42	1.03	1.03
	ProPerfp-RED	1	1	0.99	0.99

Table 6 .

 6

	Candidates	CAS	𝐺𝑙𝑜𝑃𝑒𝑟𝑓 Commerciality Cost (€/g) Stability
	Benzyl methyl ether (BME)	538-86-3	0.975	Y	2.66	Y
	Methyl phenethyl ether (MPE) 3558-60-9	0.966	Y	1.32	Y
	PX	106-42-3	0.931	Y	0.18	Y
	N,N-Dimethylaniline (DMA)	121-69-7	0.931	Y

5 List of the best solvent candidates selected from the results of molecular design provided by IBSS®CAMD for PF2:PC71BM blends. (Y: yes, N: no, NA: non-available data)

Table 6 .

 6 6 List of the best solvent candidates selected from the results of molecular design provided by IBSS®CAMD for PF2:EH-IDTBR blends. (Y: yes, N: no, NA: non-available data) Considering the toxicity of above three solvents, PX and 4-MS are less toxic than DMA, which is in fact a highly toxic solvent. In addition, 4-MS must be removed from the list of alternative solvents due to its low chemical stability in air. The reason is that 4-MS has a double-bond in its chemical structure, which is unstable and prone to break, which may lead to OPV device instability.For the other 5 designed solvents, PA is not commercially available. AB, 3-BTB, 4-ET, and 2-MS are costly compared to other commonly used solvents such as PX and anisole. In addition, AB, 3-BTB, 4-ET and 2-MS are unstable when exposed in air, due to the fact that either double-bond or triple-bond in their chemical structure tend to break in air. Therefore, only PX has been retained as candidate solvent for PF2:PC71BM blends and PF2:EH-IDTBR blends.

	Candidates	CAS	𝐺𝑙𝑜𝑃𝑒𝑟𝑓 Commerciality Cost (€/g) Stability
	Methyl phenethyl ether (MPE)	3558-60-9	1	Y	1.32	Y
	Benzyl methyl ether (BME)	538-86-3	0.997	Y	2.66	Y
	1-(3-Buten-2-yl)-4-	97664-18-1	0.989	N	NA	N
	methylbenzene (1-4-MB)
	Allylbenzene (AB)	300-57-2	0.932	Y	2.84	N
	1-Phenyl-2-butene (1-P-2-B)	935-00-2	0.932	N	NA	N
	PX	106-42-3	0.931	Y	0.18	Y
	4-Methylstyrene (4-MS)	622-97-9	0.931	Y	0.52	N
	N,N-Dimethylaniline (DMA)	121-69-7	0.931	Y	0.21	Y
	3-Butenylbenzene (3-BTB)	768-56-9	0.930	Y	9.73	N
	1-Methyl-2-(2-propyn-1-	NA	0.929	N	NA	N
	yl)benzene (1-M-2-B)
	4-Ethynyltoluene (4-ET)	622-96-8	0.923	Y	7.04	N
	2-Methylstyrene (2-MS)	611-15-4	0.914	Y	19.01	N
	Phenylallene (PA)	2327-99-3	0.903	N	NA	N
	For the 8 identical solvents, 5 candidates are commercially available. However,
	taking the cost into account, only 3 candidates, which are PX, DMA and 4-MS, have
	been retained.

Table 6

 6 The boiling point, ∆Hvap, density, and viscosity of the candidates are almost identical to the target values, which means that they are good alternative solvents for film formation and drying. In addition, they are liquid at room temperature, meeting the requirement for reduced energy consumption in device manufacturing.

	.7 lists 13 candidate alternative solvents with GloPerf > 0.6 for the
	KNSF2:PC71BM blends. They are p-xylene (PX), p-cymene (PC), 1,4-cineol (CN), anisole
	(AN), cyclopentyl methyl ether (CPME), α-pinene (α-PNE), glycerol -1,2,3-triethyl ether
	(GTE), pinane (PNA), dibutyl ether (DBE), β-pinene (β-PNE), terpinolene (TPO), d-
	limonene (d-LM), isoamyl acetate (IA). The full target property values and ProPerfp
	values for candidate solvents with a GloPerf >0.6 for KNSF2:PC71BM blends are
	presented in Appendix 9.13.
	The GloPerf value for o-DCB is 0.977 rather than 1 because the Ra value between
	o-DCB and KNSF2 is greater than 4, which results in a ProPerfp-Ra value of 0.824 for
	KNSF2. This result was expected because of the previous setting of the KNSF2 target
	value for Ra.

Table 6 .

 6 7 The candidates provided for KNSF2:PC71BM by IBSS®CAMD with a GloPerf > 0.6.

	Candidates	CAS	𝐺𝑙𝑜𝑃𝑒𝑟𝑓	Ra-KNSF2	ProPerfp-Ra-KNSF2	Ra-PC71BM	ProPerfp-Ra-PC71BM
	o-DCB	95-50-1	0.977	4.37	0.824	0.88	1
	p-Xylene (PX)	106-42-3	0.874	2.31	1	4.61	0.026
	p-Cymene (PC)	99-87-6	0.812	2.66	1	5.11	0.002
	1,4-Cineol (CN)	470-67-7	0.751	2.47	1	6.75	≈ 0
	Anisole (AN)	100-66-3	0.742	4.74	0.465	4.52	0.038
	Cyclopentyl methyl ether (CPME)	5614-37-9	0.725	2.80	1	7.44	≈ 0
	α-Pinene (α-PNE)	80-56-8	0.699	3.13	1	8.00	≈ 0
	Glycerol -1,2,3-triethyl ether (GTE)	162614-45-1	0.694	4.46	0.741	9.46	≈ 0
	Pinane (PNA)	473-55-2	0.689	2.83	1	8.06	≈ 0
	Dibutyl ether (DBE)	142-96-1	0.640	4.50	0.703	10.08	≈ 0
	β-Pinene (β-PNE)	127-91-3	0.626	2.90	1	8.08	≈ 0
	Terpinolene (TPO)	586-62-9	0.619	4.21	0.940	7.52	≈ 0
	d-Limonene (d-LM)	138-86-3	0.610	4.20	0.945	7.71	≈ 0
	Isoamyl acetate (IA)	123-92-2	0.600	5.55	0.034	9.04	≈ 0

Table 6 .

 6 8 Summary of PF2:PC71BM device performance for various solvents.

	Processing solvents	Processing temperature	Voc (mV)	Jsc (mA cm -²)	FF (%)	PCE (%)	Thickness (nm)
	o-DCB	100 o C	754±5	17.9±1.3	73.5±0.5	9.8±0.7	~115
	PX/DPE3%	100 o C	753±3	15.9±0.6	75.5±1	9.1±0.4	~130
	PX/DPE3%	90 o C	753±5	15.3±0.5	75.5±1	8.8±0.2	~120
	PX/DPE3%	80 o C	758±3	15.4±0.2	74.5±1	8.8±0.1	~125
	PX/DPE3%	70 o C	761±6	15.3±0.4	74.8±1	8.8±0.2	~135

Table 6 .

 6 9 The corresponding photovoltaic device parameters of PF2:EH-IDTBR based devices fabricated from various solvents.

	Materials	Processing solvents	Voc (mV)	Jsc (mA/cm 2 )	FF (%)	PCE (%)
		o-DCB	1040±5	12.87±0.2	57.9±1	7.3±0.2
	PF2:EH-IDTBR
		PX	1070±3	13.21±0.1	55.8±1	8.0±0.1

8: The list of solvents used in HSPs measurements of PF2 and KNSF2. (/:Not used for HSP measurements)

	181	N. 1 3 5 7 9 11 13 15 17 19 21 23 25 95 97 99 Density (g/cm 3 ) 2-Methoxy-1,3-propanediol Name 1,2-dichlorobenzene (reference solvent) Anisole 2-Methylanisole p-Xylene Isoamyl acetate Benzyl Benzoate p-Cymene Terpinolene Butyl acetate Tetrahydrofuran d-Limonene Cyclopentyl methyl ether Isobutyl acetate Isopropyl Acetate Diethoxymethane Acetic acid Tributyl citrate acetate 1,4-Butanediol 2,3-Dimethoxy-1-propanol 2-Hydroxypropanoic acid 1,2,3-Propanetriyl triacetate Alpha-Terpineol 2,3-Diethoxy-1-propanol 2-Methoxy-2-methylbutane (2,2-Dimethyl-1,3-dioxolan-4-yl)methanol 2-Ethylhexyl lactate Geraniol O-Acetylcholine 1.280 0.974 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 𝛿 𝐷 (MPa 1/2 ) 19.5 18.1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 𝛿 𝑃 (MPa 1/2 ) 5.1 4.9 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 𝛿 𝐻 (MPa 1/2 ) 3.1 6.1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1 0.96 𝑅 𝑎 (MPa 1/2 ) 2.77 1.39 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 1 RED 0.59 0.30 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 1 Viscosity (mPa s) 1.089 0.569 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity 1 1 𝛿 𝐷 (MPa 1/2 ) 19.3 18.1 N. 2 4 6 8 10 12 14 16 18 20 22 24 26 96 98 100 102 104 106 108 110 112 114 116 118 120 122 124 126 0.873 1 18.6 1 3.8 0.88 1.6 ≈ 0 3.54 0.66 0.75 1 0.568 1 18.6 Chlorobenzene (reference Name solvent) Methyl 9,12-octadecadienoate Geranyl acetate Dimethyl Adipate Nopol Methyl myristate 2-Octanol 2-Furylmethanol 1,3-Dioxolan-4-ylmethanol Ethyl myristate Ethyl palmitate Bis(2-ethylhexyl) succinate Methyl palmitate 2,3-Dibutoxy-1-propanol 5-(Hydroxymethyl)-2-furaldehyde 4-(Hydroxymethyl)-1,3-dioxolan-2-one Triethyl citrate Hexamethyldisiloxane Ethyl acetate Tributyl citrate 3-Ethoxy-1,2-propanediol 2-Ethoxy-2-methylpropane 2-(2-Butoxyethoxy)ethanol 3-Butoxy-1,2-propanediol Acetone 2-Hydroxy-N,N-dimethylpropanamide 3-Hydroxypropanoic acid 2-Ethoxy-1,3-propanediol Glycerol 0.868 1.123 1 1 15.8 19.8 ≈ 0 1 4 6.3 1 0.68 6 4.7 1 1 5.59 3.04 ≈ 0 0.99 1.19 0.65 ≈ 0 1 0.903 5.224 1 ≈ 0 17.4 15.8 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 1 0.96 ≈ 0 𝛿 𝑃 (MPa 1/2 ) 4.8 4.9 3.8 2.3 4 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 1 0.01 1 𝛿 𝐻 (MPa 1/2 ) 2.7 6.1 1.6 2.4 6 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1 0.96 ≈ 0 ≈ 0 1 𝑅 𝑎 (MPa 1/2 ) 1.58 1.39 3.54 4.20 5.59 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 1 0.66 0.130 ≈ 0 RED 0.41 0.3 0.75 0.89 1.12 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 1 1 1 0.64 Viscosity (mPa s) 0.682 0.569 0.568 0.897 0.903 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity 1 1 1 1 1 ΔHvap (kJ/mol) 47.9 51.8 55.3 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -ΔHvap 1 1 0.98 Density (g/cm 3 ) 0.946 0.912 0.971 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 1 𝛿 𝐷 (MPa 1/2 ) 18.2 18.1 18.5 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 1 𝛿 𝑃 (MPa 1/2 ) 4.4 6 5 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 1 𝛿 𝐻 (MPa 1/2 ) 4.5 4.4 5.7 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1 1 1 𝑅 𝑎 (MPa 1/2 ) 0.89 1.70 0.75 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 1 1 RED 0.19 0.36 0.16 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 1 1 Viscosity (mPa s) 0.721 1.090 0.759 Cost (€/g) 0.7 39.8 0.9 20.0 Tetrachloroethylene 18.3 5.7 0 / Butyl Benzoate 18.3 5.6 5.5 / Commerciality Y Y Y Y Iodobenzene 19.9 5.6 6.1 5 1,2,3-Trichloropropane 17.8 12.3 3.4 / Stability Y N Y Y o-Xylene 17.8 1 3.1 1 Phenetole (Ethyl Phenyl Ether) 18.4 4.5 4 / 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity 1 1 1 1 Chlorobenzene 19 4.3 2 3 Anisole 17.8 4.4 6.9 0 Viscosity (mPa s) 0.668 0.759 1.340 0.759 o-Dichlorobenzene 19.2 6.3 3.3 1 Methanol 14.7 12.3 22.3 0 / 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 1 1 1 Tetrahydronaphthalene 19.6 2 2.9 0 Cyclohexane 16.8 0 0.2 0 RED 0.34 0.20 0.61 0.16 Chloroform 17.8 3.1 5.7 3 Methyl Isobutyl Ketone (MIBK) 15.3 6.1 4.1 0 𝑅 𝑎 (MPa 1/2 ) 1.60 0.92 2.86 0.75 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 1 1 1 Hexane 14.9 0 0 0 Tetrahydrofuran (THF) 16.8 5.7 8 2 Dibasic Esters (DBE) 16.2 6.5 8.4 0 / Ethyl Acetate 15.8 5.3 7.2 0 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 0.21 1 1 1 n-Butyl Acetate 15.8 3.7 6.3 0 γ-Butyrolactone (GBL) 18 16.6 7.4 0 𝛿 𝐻 (MPa 1/2 ) 6.6 5.9 5.3 5.7 1,4-Dioxane 17.5 1.8 9 0 1-Butanol 16 5.7 15.8 0 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity 1 1 1 Stability N N / Commerciality Y N N Cost (€/g) 9.3 / / 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 1 1 𝛿 𝐷 (MPa 1/2 ) 18.6 18.4 18.7 18.5 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 1 1 𝛿 𝑃 (MPa 1/2 ) 4.4 4.5 7.5 5 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 ≈ 0 1 δD δP δH Score-PF2 Score-KNSF2 Methyl Ethyl Ketone (MEK) 16 9 5.1 0 Propylene Glycol Monomethyl Ether 15.6 6.3 11.6 0 Propylene Carbonate 20 18 4.1 0 / Dimethyl Formamide (DMF) 17.4 13.7 11.3 0 Ether Acetate 15.6 5.6 9.8 0 Propylene Glycol Monomethyl Appendix 9.Solvents Dimethyl Sulfoxide (DMSO) 18.4 16.4 10.2 0 Appendix 9.9:	0.864 1 17.4 0.21 2.3 ≈ 0 2.4 ≈ 0 4.20 0.13 0.89 1 0.897 1 16.9 0.21 1.8 ≈ 0 4.8 1 4.35 0.08 0.93 1 0.748 1 46.5 1 0.974 1 18.1 1 4.9 1 6.1 0.96 1.39 1 0.30 1 0.569 / N N 1 1.382 1 0.50 2.35 1 1 4.3 1 Y Y 0.4 1 17.6 0.5 5.9 1	0.855 1 16.9 0.005 1.8 ≈ 0 4.8 1 4.35 0.08 0.93 1 0.748 1 16.9 0.21 4.2 1 4.1 1 3.42 0.78 0.73 1 0.557 1 51.4 1 0.957 1 17.8 0.84 4.4 1 4.5 1 1.58 1 0.34 1 0.721 1 Y Y 1.9	0.873 1 15.8 ≈ 0 5.1 1 6.5 0.34 5.67 ≈ 0 1.21 0.58 0.724 1 15.8 ≈ 0 5.1 1 6.5 0.34 5.67 ≈ 0 1.21 0.58 0.724 1 51.4 1 0.963 1 18.8 1 5.7 1 6.3 0.68 1.72 1 0.37 1 0.668 3712 Y / 1 0.611 1 0.64 3.02 0.99 1 5.2 1 N Y 4230 1 17.1 0.03 3.7 0.75	0.872 1 16.9 0.005 4.2 1 4.1 1 3.42 0.78 0.73 1 0.557 1 16.6 0.03 3.7 1 3.7 1 4.20 0.13 0.89 1 0.494 0.87 55.2 0.99 0.969 1 4.4 1 / 0.820 N 1 N 0.36 1 1 0.944 1.69 1 1 0.71 5.2 3.32 0.86 0.96 0.68 6.1 17.7 1 / Y 1961.6 1 17 0.01 5.4 1	9. APPENDIX
		27 29 31	2-Methyltetrahydrofuran Propylene carbonate Ethylene carbonate 1-Decanol Toluene 1,3-Dioxolane 1,2-Pentanediol Diethylene Glycol Ethanol Ethanolamine	18 18.1 16.6 15.8 17	28 30 32 128 130	1.4 6.6 12 8.8 15.5	Dimethyl sulfoxide Dimethyl isosorbide Butyl laurate 1,4-Bis(aminooxy)-1,4-2 9.3 / butanedione 19 hydroxyethyl)octanamide 1 / N,N-Bis(2-19.4 0 21 /
		33 N-Methyl-2-Pyrrolidone (NMP) Glycerol -1,2,3-triethyl ether Cyclademol 35 Dimethyl Succinate 37 1,2,3-Trimethoxypropane Butyl stearate Acetonitrile 15.3 18 12-Hydroxy-9-octadecenoic acid Diacetone Alcohol 15.8	34 132 36 38 134 136	12.3 18 8.2	9,12-Octadecadienoic acid 2-Butoxy-1,3-propanediol 7.2 / (9Z,12Z)-, ethyl ester Propionic acid Methyl 9-octadecenoate Dimethyl carbonate 6.1 0 Methoxy(trimethyl)silane 10.8 0
		39	Diethyl carbonate 9-Octadecen-1-ol 2-Phenoxy Ethanol	17.8	40 138	5.7	Dioctyl-succinate Isopropanol 14.3	/
		41	Furfural Ethanol Dipropylene Glycol	16.5	42 140	N,N-Dimethyldec-9-enamide Butyl 3-hydroxybutanoate 10.6 17.7 0
		43	5-Methyldihydro-2(3H)-Methyl 9,12-Cyclohexanol octadecadienoate furanone Acetone	17.4 15.5	44	4.1 10.4	Methyl stearate 13.5 7	/ 0

The candidates provided by IBSS®CAMD with a GloPerf > 0.5 for PF2:PC71BM.

  recherche de solvants bio-sourcés efficaces est encore plus difficile.

		permettent de fabriquer des dispositifs PVO de grande surface avec un impact
	194	Candidates CAS 𝐺𝑙𝑜𝑃𝑒𝑟𝑓 Melting Point (Tm, K) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Tm Boiling Point (Tb, K) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 Viscosity (mPa s) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED dichlorobenzene 1,2-95-50-1 1 255 1 449 1 1.089 ≈ 0 𝑅 𝑎 (MPa 1/2 ) 2.69 2.66 Viscosity (mPa s) 0.902 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 𝑅 𝑎 (MPa 1/2 )-PC71BM 2 9.46 p-xylene 106-42-3 100-66-3 99-87-6 120-51-4 Anisole p-Cymene Benzyl Benzoate 0.931 0.724 0.693 0.566 229 239 224 306 1 1 1 ≈ 0 419 428 450 573 1 0.17 0.18 0.83 0.568 0.569 0.897 ≈ 0 ≈ 0 1.70 1.77 2.87 0.721 1.012 0.707 Glycerol -1,2,3-triethyl ether 162614-45-1 0.517 210 1 467 ≈ 0 5.224 ≈ 0 1.94 ≈ 0 Isoamyl acetate 123-92-2 123-86-4 Butyl acetate 0.517 0.517 202 201 1 1 420 407 ≈ 0 ≈ 0 0.962 ≈ 0 2.79 0.815 0.568 1 1 1 1 4.61 5.11 6.75 4.52 7.44 8.06 10.08 8.08 7.52 7.71 𝑅 𝑎 (MPa 1/2 )-PC71BM Density (g/cm 3 ) 1.280 0.873 0.974 0.864 1.123 0.893 0.868 0.873 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 1 1 1 1 1 1 𝛿 𝐷 (MPa 1/2 ) 19.5 18.6 18.1 17.4 19.8 15.5 15.8 15.8 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 0.50 0.01 1.00 ≈ 0 ≈ 0 ≈ 0 𝛿 𝑃 (MPa 1/2 ) 5.1 3.8 4.9 2.3 6.3 4.8 4 5.1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 1 0.02 0.03 1 1 1 𝛿 𝐻 (MPa 1/2 ) 3.1 1.6 6.1 2.4 4.7 3.6 6 6.5 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1 ≈ 0 ≈ 0 1 0.68 1 ≈ 0 ≈ 0 𝑅 𝑎 (MPa 1/2 ) 1.51 1.70 4.12 4.10 3.36 7.51 7.52 7.85 𝛿 𝐷 (MPa 1/2 ) 19.5 18.6 18.1 17.4 19.8 15.5 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 1 0.21 1 0.00 𝛿 𝑃 (MPa 1/2 ) 5.1 3.8 4.9 2.3 6.3 4.8 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 1 0.13 ≈ 0 1 𝛿 𝐻 (MPa 1/2 ) 3.1 1.6 6.1 2.4 4.7 3.6 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1 0.00 0.00 1 0.68 1 𝑅 𝑎 (MPa 1/2 ) 1.51 1.70 4.12 4.10 3.36 7.51 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 1 0.17 0.18 0.83 ≈ 0 RED 0.38 0.42 1.03 1.03 0.84 1.88 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 1.00 0.99 0.99 1 ≈ 0 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 1 1 0.10 1 𝛿 𝐷 (MPa 1/2 ) 15.8 15.8 18.4 18 15.4 17.9 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 0.00 0.00 1 1 0.00 0.96 𝛿 𝑃 (MPa 1/2 ) 4 5.1 21.2 12.5 2.9 18.3 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 ≈ 0 ≈ 0 0.88 ≈ 0 𝛿 𝐻 (MPa 1/2 ) 6 6.5 6.3 8.8 2.7 5 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 0.00 0.00 0.00 0.00 1 0.21 𝑅 𝑎 (MPa 1/2 ) 7.52 7.85 17.82 10.84 7.65 14.89 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 ≈ 0 ≈ 0 ≈ 0 ≈ 0 ≈ 0 ≈ 0 RED 1.88 1.96 4.46 2.71 1.91 3.72 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -ΔHvap 1 1 1 1 1 0 1 Density (g/cm 3 ) 0.946 0.935 0.873 0.937 0.883 0.889 0.888 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 1 1 1 1 1 𝛿 𝐷 (MPa 1/2 ) 18.2 18.1 18.6 18.6 17.8 18.3 18.2 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 0.68 0.50 1 1 0.12 0.84 0.68 𝛿 𝑃 (MPa 1/2 ) 4.4 3.9 3.8 3.9 3.2 3.2 1.9 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 1 1 0.88 0.88 ≈ 0 𝛿 𝐻 (MPa 1/2 ) 4.5 4.3 1.6 4.1 2.9 2.4 3.2 Commerciality Y Y Y Y N Y N Cost (€/g) 2.66 1.32 0.18 0.21 NA 0.52 NA Stable (at room temperature) Y Y Y Y N N N 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 1 1 1 1 𝛿 𝐷 (MPa 1/2 ) 18.1 18.2 17.8 18.1 18.2 18.6 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 0.84 1.00 1.00 1 𝛿 𝑃 (MPa 1/2 ) 3.9 4.4 3.2 2 1.9 3.8 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Density 1 1 1 1 1 𝛿 𝐷 (MPa 1/2 ) 18.6 18 18.4 18.2 18.1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 1 1 1 𝛿 𝐷 (MPa 1/2 ) 19.5 18.6 18.5 17 18.1 16.6 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 1 1 1 0.339 1 0.030 𝛿 𝑃 (MPa 1/2 ) 5.1 3.8 2.6 3.4 4.9 3.7 𝛿 𝐷 (MPa 1/2 ) 15.5 17 15.4 16.9 16.9 16.7 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐷 ≈0 0.339 ≈0 0.210 0.210 0.062 négligeable sur l'environnement et la santé humaine, sans réduire l'efficacité de Dans ce contexte, l'objectif principal de cette thèse a été d'appliquer une méthode conversion du dispositif. d' «ingénierie inversée », reposant sur la conception assistée par ordinateur de 𝛿 𝑃 (MPa 1/2 ) 4.8 1.6 2.9 1.6 1.8 2.2 Parmi les nombreux nouveaux matériaux organiques qui ont été développés pour molécules organiques, à la recherche de solvants de remplacement pour les matériaux 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 1 0.02 0.01 1 𝛿 𝑃 (MPa 1/2 ) 3.9 1.9 3 2.9 2.8 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 1 0.075 0.969 1 1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 ≈0 0.317 ≈0 ≈0 0.005 augmenter l'efficacité des dispositifs de PVO, seuls quelques exemples ont été mis en photovoltaïques. Cette méthode a été développée initialement, et utilisée avec succès, 𝛿 𝐻 (MPa 1/2 ) 4.3 4.5 2.9 3.1 3.2 1.6 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝑃 1 0.01 0.97 0.88 0.75 𝛿 𝐻 (MPa 1/2 ) 3.1 1.6 1.9 3.7 6.1 3.7 𝛿 𝐻 (MPa 1/2 ) 3.6 1.4 2.7 1.8 4.8 4.9 oeuvre avec des solvants alternatifs non ou moins toxiques. La solubilité étant fonction pour la recherche de solvants alternatifs en cosmétique. Dans ce travail, il s'agissait 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1.00 0.96 1.00 1.00 1.00 ≈ 0 𝛿 𝐻 (MPa 1/2 ) 4.1 3 3.1 1.8 2.7 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1 1 1 0.841 ≈0 0.841 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 0.958 0.841 1 1 0.001 ≈0 de la structure moléculaire du soluté, les solvants de remplacement ne peuvent d'appliquer une approche similaire à la problématique du PVO et de rendre la 𝑅 𝑎 (MPa 1/2 ) 2.66 2.69 2.87 2.86 2.79 1.70 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 1.00 1.00 1.00 0.00 1 𝑅 𝑎 (MPa 1/2 )-KNSF2 4.37 2.31 2.66 2.47 4.74 2.80 𝑅 𝑎 (MPa 1/2 )-KNSF2 4.46 2.83 4.50 2.90 4.21 4.20 cependant pas être appliqués universellement à tous les semi-conducteurs organiques. recherche de solvants alternatifs, voire bio-sourcés, moins empirique. La méthode a 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 1 1 1 1 1 𝑅 𝑎 (MPa 1/2 ) 1.77 3.07 1.81 2.41 2.42 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 -KNSF2 0.824 1 1 1 0.465 1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 -KNSF2 0.741 1 0.703 1 0.940 0.945 0.034 Ethylene carbonate 96-49-1 0.514 283 1 ≈ 0 1.81 0.655 1 8.00 9.04 413 1.30 1 18.4 0.96 21.2 ≈ 0 6.3 ≈ 0 17.82 1 0.918 1 18.4 0.96 3 0.60 3.1 N NA N 1 18.3 1.00 1 18.3 1 17 0.339 1.3 15.8 ≈0 4 3.2 2.7 ≈0 1 1 0.60 2 6 2.4 4.1 1 ≈0 1.00 1 3.13 5.55 1.94 1 2.48 1 été appliquée avec succès aux mélanges de poly (3-hexylthiophène) (P3HT) et de RED 0.67 0.67 0.72 0.71 0.70 0.42 0.48 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 0.99 1 1 1 1 RED-KNSF2 0.88 0.47 0.54 0.50 0.97 0.57 0.64 RED-KNSF2 0.91 0.58 0.92 0.59 0.86 0.86 1.13 PC71BM (un dérivé soluble du fullerène) ainsi qu'au P3HT mélangé avec du EH-IDTBR, 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝛿 𝐻 0.96 1 ≈ 0 1 1 1 1 1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 1 1 1 1 1 1 RED 0.44 0.77 0.45 0.60 0.60 0.62 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED-KNSF2 1 1 1 1 1 1 1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED -KNSF2 1 1 1 1 1 1.000 0.801 un accepteur non-fullerène. Deux polymères à haut rendement (PF2 et KNSF2),	9. APPENDIX
		𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Tb RED 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity Viscosity (mPa s) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity Viscosity (mPa s) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 -PC71BM 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -𝑅 𝑎 -PC71BM 0.38 1 1	1 0.903 1 NA 1	1 0.42 ≈0	1 1.03 1 0.724 1 0.888 0.026 1 ≈0	1 1.03 1 0.824 1 0.002 1 ≈0	≈ 0 0.84 1 NA ≈0	1	1 1.88 0.722 0 1 0.612 1.88 1 1 0.038 1.142 ≈0 ≈0 1 ≈0	1 1.96 0.797 1 1 0.655 1 ≈0	1 4.46 1 1 NA ≈0 ≈0
		Flash Point (Tf, K) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Tf ΔHvap (kJ/mol) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED Viscosity (mPa s) 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity RED 0.67 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED 1 Viscosity (mPa s) 0.721 1.089 332 1 50.1 1 Commerciality Y Cost (€/g) 1.32 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity RED-PC71BM RED-PC71BM Commerciality 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED-PC71BM 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -RED -PC71BM Stable (at room temperature) Y Cost (€/g) Viscosity (mPa s) Viscosity (mPa s)	301 1 43.4 1 0.568 0.568 1 0.42 1.00 Y 2.66 0.55 1.13 0.67 1 1 0.902 0 0.24 Y 1 1 0.815 Y 0.21 1.089 0.568 0.962	314 1 46.5 0.99 0.569 1 0.96 Y 1 9.73 /	323 1 50.1 0.99 0.897 1 0.44 1 NA N NA 0.61 1.20 0.80 419 1 85.75 1 5.224 0.72 1 1.012 Y 2.84 0 0.96 1 0.54 0.962 343 1 60.2 ≈ 0 N 1 1 1 0.599 1 N N NA 7.04 0.48 1 1 0.655 N NA 1 0.90 Y 1 N 0.897 / 0.569 0.612 / /	312 1 48.9 ≈ 0 0.903 0.89 1 0.494 0.92 0.70 46.0 305 1 ≈ 0 0.724 1 1 0.815 Y 0.18 1 Y 1 Y 19.01 /	324 1 49.3 ≈ 0 0.824 0.45 1 NA Y 0.95 1.08 0 0.52 N 1 0.929 N NA / 0.903
		𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -ΔHvap 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity Stable 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity 1 𝑃𝑟𝑜𝑃𝑒𝑟𝑓 𝑝 -Viscosity	1	1 Y 1	1	1	1 1	1 N ≈0	0 1	1	1	≈ 0 N ≈0	1	≈0	1	≈ 0	N ≈0	1	≈ 0 0.870	≈0	1 N	≈ 0	≈ 0 0 N ≈0 1
		Comme de nouveaux matériaux donneurs ou accepteurs sont continuellement conçus
		et synthétisés dans les laboratoires de recherche afin d'améliorer encore les
		performances des dispositifs PVO, le développement d'une méthode plus efficace et
		rapide pour identifier des solvants alternatifs serait particulièrement utile. Il convient
		de noter que la recherche de solvants alternatifs est également nécessaire pour les
		dispositifs autres que les PVO, tels que les diodes électroluminescentes organiques,
		les transistors organiques à effet de champ ou encore les cellules solaires pérovskites.
		Enfin, dans le cadre du développement durable, les solvants synthétisés à partir de

De fait, jusqu'à présent, la sélection des solvants de remplacement était principalement le résultat d'une approche empirique et fastidieuse, de type essaiserreurs, laquelle risque de manquer des solvants candidats plus appropriés. La recherche de nouveaux solvants est en effet un problème complexe nécessitant la prise en compte simultanée de nombreuses propriétés interdépendantes, l'augmentation en performance d'une propriété pouvant entraîner la réduction de la performance d'une autre. Ainsi, la recherche d'un solvant de remplacement est souvent le compromis d'un problème à objectifs multiples. Des propriétés telles que la solubilité, la viscosité, la sécurité, la durabilité, la toxicité..., sont toutes importantes pour l'application finale et ont toutes un impact sur les performances du dispositif. produits issus de l'agriculture (i.e. les « biosolvants ») suscitent un intérêt croissant.

Toutefois, étant moins « polyvalents » que la plupart des solvants chlorés ou hydrocarbonés, la synthétisés par les équipes de N. Leclerc d'ICPEES et de S. Méry à l'IPCMS, ont également été étudiés.

Acknowledgements

way as the rules discussed in Chapters 4 and 5. Note that the weight of each RED is reduced to 1 and the weight of each Ra is reduced to 2 as they are defined for KNSF2 and PC71BM, respectively.

For the existing solvent performance evaluation, 139 biosolvents (see Appendix 9.4) were also selected as target solvents for PF2 and KNSF2-based OPVs. For molecular design, the chemical groups that are shown in Appendix 9.3, are selected to design new molecules only for PF2:PC71BM blends and PF2:EH-IDTBR blends.

-PF2: PC71BM blends and PF2:EH-IDTBR blends:

3 best ranked alternative solvents candidates for PF2:PC71BM blends and 3 best ranked alternative solvents candidates for PF2:EH-IDTBR blends with a GloPerf >0.6 are displayed in table 6.3 and 6.4. The full target property values and ProPerfp values for candidate solvents with a GloPerf >0.5 for PF2:PC71BM blends are presented in Appendix 9.9, and those for candidate solvents with a GloPerf >0.5 for PF2:EH-IDTBRE blends are presented in Appendix 9.10.

According to IBSS®CAMD, the best candidate solvent turns out to be p-xylene (PX), with a GloPerf of 0.931 for both blends. All individual performance functions of PX do indeed equal unity except δH (ProPerfp ≈ 0). The estimated viscosity and density of PX are similar with the values of o-DCB, allowing similar conditions to be applied when processing PF2 solutions. Also, the Ra and RED values of PX are smaller than those of the other alternative solvents, providing a good solubility for PF2.

Resumé

Recherche par ingénierie inversée de solvants alternatifs, non-toxiques et bio-sourcés, pour la fabrication de cellules solaires organiques

Introduction

Jing WANG Searching sustainable solvents for high-performance organic solar cells by reverse engineering

Résumé

Pour la production de modules photovoltaï ques organiques (OPV), le remplacement des solvants halogénés par des solvants "verts" est indispensable. En raison des liens complexes entre propriétés des solvants et performances OPV, la sélection de solvants s'est basée jusqu'à présent sur une approche de type essaierreur. Ici, nous explorons une méthode moins empirique, de type conception moléculaire assistée par ordinateur, en utilisant l'outil IBSS®CAMD, initialement développé pour la recherche de bio-solvants en cosmétique. IBSS®CAMD modélise les propriétés physicochimiques de molécules et applique un algorithme génétique pour concevoir des molécules aux propriétés souhaitées. A partir de valeurs cibles de multiples propriétés, IBSS®CAMD établit une classification de solvants en terme de performances globales. Les performances réelles des solvants sélectionnés sont évaluées en élaborant des dispositifs OPV et en comparant les rendements de conversion avec des références. Pour chacun des matériaux étudiés, les résultats obtenus avec les solvants alternatifs sont équivalents aux références, confirmant l'efficacité de la méthode.

Mots-clés: Photovoltaï que organique, solvants durables, conception de produits assistée par ordinateur

Résumé en anglais

For a sustainable scale-up of organic photovoltaic (OPV) modules, the replacement of halogenated solvents by "green" solvents is a critical pre-requisite. Due to the complex relationship between solvent properties and device performance, the selection of alternative solvents has so far relied primarily on a trial-and-error approach. In this thesis, we introduce a less empirical solvent selection tool, IBSS®CAMD, and apply it to the fabrication of OPVs. IBSS®CAMD models the physicochemical properties of molecules and applies a genetic algorithm to design molecules with the desired properties. This allows us to establish lists of alternative solvents ranked by a global performance function encompassing a given number of desired properties. The actual performances of the selected solvents are evaluated by elaborating photovoltaic devices and comparing the performance with those obtained with devices processed from halogenated solvents. For each of studied blends, the performances of the devices obtained with the alternative solvents were similar to those of standard devices processed from halogenated solvents, corroborating the relevance of the proposed method. Keywords: Organic photovoltaics, sustainable solvents, computer-aided product design