Alessandro Di Pretoro

Montastruc a , ... Flavio Manenti Ludovic

Xavier Joulia

Flexibility assessment of a biorefinery distillation train: Optimal design under uncertain conditions

Keywords:

Introduction

Conventional vs flexible design procedu re

ABSTRACT

Multicomponent mixtures can be separated into their single components by mean of dilferent distillation system configurations. The typical distillation train design procedure consists of the assessment of the optimal columns configuration according to the economic and operational aspects. However, this opti mal design is strictly related to the operating conditions, i.e. perturbations, when present, can seriously compromise the operation profitability. In these cases a flexibility analysis could be of critical importance to assess the operating conditions range of better performance for different system configurations. This is the typical case of biorefineries where the floating nature of the feedstock causes composition dis turbances downstream the fermenter across the year's se. asons. A brand new ABE/W mixture separation case study has been set up; this mixture de rives from an upstream microbial conversion process and the successful recovery of at least biobutanol and acetone is crucial for the return on the investments. This paper then compares the possible distillation train configurations from a flexibility point of view. The analysis is focused in particular in highlighting the differences, if present, between the economic optimal solution and flexibility optimal configuration that could not be the same, causing this way a very prof itable design to be much less performant under perturbated conditions. Furthermore, a detailed analysis correlating the complex thermodynamics to the operation under uncertain conditions is thoroughly dis cussed. The proposed design procedure allowed to highlight the differences between weak and strong flexibility constraints and resulted in a dedicated "additional costs vs. flexibility" trend useful to improve the decision making.

ln case an equipment oversizing is not needed, the extemal duty response to process deviations is assessed during the control system design by mean of a dynamic simulation leading (hope fully) to the final project validation. The typical methodology for chemical plants design is usually made up of several steps performed in series as listed in Fig. 1. Given a preliminary feasibility assessment, the system configura tion and equipment sizing is outlined according to the process specifications. If a certain number of degrees of freedom is still present, the optimal configuration or operating conditions are se lected based on a total annualized costs optimization.

One of the main problems related to this kind of procedure is that the sensitivity analysis is carried out on a design optimized with respect to other parameters than the system flexibility. This means that the mode!, or simulation, to which disturbances are ap plied is able to predict operating conditions and the corresponding costs variations of that specific predefined configuration. Moreover, when the process simulation is not able to converge, it could be very challenging to understand if the solution failure is due to the fact that the design optimized under nominal operating conditions is not able to accommodate the perturbed variables and more vari ables should have been included during the optimization phase, if the specifications cannot be physically achieved under the dis turbed operating conditions or if the unconverged state is simply related to an algorithm convergence issue.

Process variables disturbances or uncertain operating condi tions, if taken into account, are often discussed in a sensitivity analysis usually performed a posteriori. Whether the optimal de sign is not able enough to withstand extemal perturbations it can be modified at the cost of higher investments. For all those reasons, in recent years, the usual design procedure has been replaced by the flexible one as shown in Fig. 2 . Flexibility is defined as the ability of a process to accommodate a set of uncertain parameters [START_REF] Hoch | Flexibility analysis leads to a sizing strategy in distillation columns[END_REF] and it can be selected as one of the functions to optimize in the multi-objective optimal design.

Flexible design has become a non-negligible practice for all the systems likely to undergo perturbations or operating under uncertain conditions such as all processes based on biomass feedstocks whose nature floats across the seasons. During the last few years an extensive literature production was indeed published in order to deeply analyze the main features and applications of design under uncertainty. However, when discussing about flexibility, they usually refer to the optimal series of operations among a superstructure of alternatives or to the comparison of a discrete number of case studies with variable parameter values with a consequent MINLP to be solved.

A different kind of flexibility analysis can be performed by using proper flexibility indexes, discussed in the corresponding chapter 2 , over a continuous uncertain variables domain and correlate them to the corresponding optimal design and related costs.

An additional way to take advantage of a flexibility assessment can be the estimation of possible existing units reuse or adaptation in case of plant revamping or production changeover.

Multicomponent mixtures separation

Among refinery operations distillation has always been the leading process for mixtures separation into their single components. In fact it is based on a well-established technical know-how, it is suitable for high plant capacity and, for a given separation ef- ficiency, it is relatively cheap with respect to more refined operations.

Distillation trains design is the most common practice for multicomponent mixtures separation. For instance the simplest configurations in case two components should be recovered are shown in Fig. 3 . defined as:

1. Indirect configuration: sequential recovery from the heaviest to the lightest component; 2. Direct configuration: sequential recovery from the lightest to the heaviest component; 3. Midsplit configuration: a preliminary split between heaviest and lightest components is performed, then the separation is refined to achieve specification.

Each column (and its related equipment) is designed on the basis of the lowest total annualized costs and the cheapest train configuration is selected as the optimal one. The main limitation of this procedure is that the economic assessment and equipment design are strictly related to the nominal operating conditions, i.e. they don' t take into account feedstock or operating conditions perturbations.

The direct consequence is that, whether a feed composition perturbation occurs, the system could not be able to achieve the separation specifications or at least a relevant operating costs increase can be detected causing the most profitable design not to be as profitable as expected.

In recent years integrated solutions for multicomponent mixtures separation have become the best practice. Modern multicomponent distillation design indeed employs Petlyuk/Keybal columns [START_REF] Petlyuk | Thermodynamically optimal method for separating multicomponent mixtures[END_REF] or their arrangement in a single distillation column shell, also known as dividing wall column (DWC), as well as other various thermally integrated column arrangements [START_REF] Kiss | Novel applications of dividing-wall column technology to biofuel production processes[END_REF][START_REF] Okoli | II Design of dividing wall columns for butanol recovery in a thermochemical biomass to butanol process[END_REF][START_REF] Errico | Multiobjective optimal acetone-butanol-ethanol separation systems using liquid-liquid extraction-assisted divided wall columns[END_REF][START_REF] Le | Dividing wall columns for heterogeneous azeotropic distillation[END_REF][START_REF] Ramapriya | A systematic method to synthesize all dividing wall columns for n-component separation: part II[END_REF].

However, although the theoretical background related to those units is wide and well-established, there's little evidence of their employment and, in particular, of the fact that they've completely replaced the traditional distillation systems. For this reason the flexibility analysis of classical distillation train and the corresponding economic assessment will be discussed in this paper with the aim of highlighting the main features and problems deriving from this procedure while the study of the design under uncertain con-ditions of more complex integrated distillation systems will be addressed in a dedicated paper.

In refinery' s operation problems related to variables uncertainty are less appreciable since long-term contracts for crude oil supplying and blending processes ensure an almost constant and stable feedstock quality.

However, during last 15 years there has been an increasing interest for the production of chemicals and fuels from renewable resources because of growing concerns about global warming and climatic change, increasing crude oil price and existing legislations restricting the use of non-renewable energy sources. The direct consequence of this trend results in an even more increasing demand for bio-based fuels and raw materials, i.e. bio-refinery processes. Bio-processes are nevertheless highly subjected to composition perturbations downstream the fermenter across the year's seasons due to the floating nature of the feedstock. Being fermentation usually carried out as a batch process, in order to ensure the desired daily productivity, several fermenters working at the same time are required. On the other hand, even when continuous fermenters are used, their scale up and then the feed flowrate that can be processed has a limit. These conditions cause the fermentation process section to be very expensive, therefore a constantly good performance of the products recovery section is of critical importance for the profitability of the plant.

In the light of the above an a priori flexibility analysis of the different distillation train configurations is non-optional for this kind of separations in order to allow the decision maker to make a multi-criteria-based choice about the optimal design to be selected.

Flexibility operational definition and flexibility indexes

From a process engineering point of view flexibility is defined as the ability of a process to accommodate a set of uncertain parameters [START_REF] Hoch | Flexibility analysis leads to a sizing strategy in distillation columns[END_REF]. As a direct consequence of this definition, flexibility can be seen as a accurate measure of feasibility.

In order to quantify this measurement an effective tool is required. For this purpose several flexibility indexes, both deterministic and stochastic, were proposed in literature. The first ones are the result of the works carried out by [START_REF] Swaney | An index for operational flexibility in chemical process design. Part i: formulation and theory[END_REF] and [START_REF] Saboo | Design of resilient processing plants.8. A resilience index for heat-exchanger networks[END_REF] . The Swaney and Grossmann flexibility index F SG is defined as the maximum fraction of the expected deviation of all the uncertain variables at once that can be accommodated by the system. On the other hand the resilience index RI by Saboo et al. is defined as the largest total disturbance load, independent of the direction of the disturbance, that a system is able to withstand without becoming unfeasible. Although they look similar they evaluate different properties of the same physical system; namely the former is much more conservative since, for a given flexibility index value, the perturbation to be withstood involves all the uncertain parameters at the same time. A graphical comparison between these two different indexes can be seen in Fig. 4 . From a geometrical point of view the F SG index represents the distance between the nominal operating condition (the star) and the side of the maximum hyperrectangle that can be inscribed in the feasible space. On the other hand, given the maximum allowed parameter deviations independently of each other (green circles), the Resilience Index defines the distance between the operating conditions and the most constraining of them.

Since these indexes assess different properties, in order to carry out a reliable flexibility assessment, the most suitable one should be identified. As it can be deducted from their definition, the compliance of the index is necessarily related to the expected deviation nature. In any case both of them assign to any deviation type and magnitude the same likelihood (that's why they can be defined as "deterministic").

The need of estimating the perturbation likelihood was fulfilled by the introduction of a stochastic flexibility index SF proposed by [START_REF] Pistikopoulos | A novel flexibility analysis approach for processes with stochastic parameters[END_REF] . It is defined as the integral of the deviation probability density function over the feasible domain. The price to pay to use such a detailed index is the need to know the required probability function that is seldom available. In order to outline this probability function there are two main possible procedures:

• Data collection of the system disturbances and consequent fitting with the most compliant PDF form in order to obtain the corresponding parameters; • A priori selection of a PDF according to the state of information (e.g. symmetric or skew PDF, normal distribution etc.) and parameters calculation according to reasonable hypothesis (e.g. maximum probability value under nominal operating conditions, variance selection in order to have almost the entire perturbation likelihood within the maximum deviation range etc)

In order to better understand the stochastic flexibility index a simple heat exchanger case study is shown in Fig. 5 . The feasibility constraint is represented by the heat transfer area of the available heat exchanger (red hyperbolic surface) according to the characteristic equation:

A = Q U • T lm
As it can be noticed, a positive deviation of the cooling water temperature or a negative deviation of the heat transfer coefficient make the cooling operation unfeasible. The stochastic flexibility index SF is then represented by the integral of the probability distribution function (colored Gaussian bell curve) over the right side of the uncertain space.

Finally a volumetric flexibility index F V , whose properties can be associated to the stochastic one, was introduced by Lai and Hui (20 08, 20 07) . It is defined as the fraction of the expected deviation volume contained in the feasible domain. A more complete review about these indexes and a thorough procedure to integrate them in the distillation column design were provided by Di [START_REF] Di Pretoro | Flexibility analysis of a distillation column: indexes comparison and economic assessment[END_REF] .

After the flexibility assessment an economic analysis needs to be performed in order to evaluate the additional costs related to a more flexible design. In case of deterministic indexes the distillation train design for which capital and operating costs should be estimated is univocally determined. On the contrary, if a stochastic index is employed, several design could lead to the same SF value. An economic optimization is thus required at each stochastic flexibility analysis step in order to find the cheapest system design providing the same SF value. This procedure corresponds to looking for the most flexible configuration for a given additional cost.

If cost minimization is not the most interesting or constraining condition a different constraint (e.g. controllability, energy consumption etc) should be provided in any case to fulfill the remaining degree of freedom of the flexibility problem. In the presented case study when the "x" stochastic flexibility design is discussed it will be referred to the cheapest design corresponding to the "x" SF value.

Capital and operating costs for the flexibility and economic based design coupling have been estimated using [START_REF] Guthrie | Capital cost estimating[END_REF][START_REF] Guthrie | Process Plant Estimating, Evaluation, and Control[END_REF][START_REF] Ulrich | A Guide to Chemical Engineering Process Design and Economics[END_REF][START_REF] Navarrete | Planning, Estimating, and Control of Chemical Construction Projects[END_REF] correlations. For further detail please refer to the dedicated section in the Appendix Appendix B .

The biorefinery case study

Several interesting flexibility analysis and design applications to distillation trains have been found in literature ( Adams et al., 2018;Benz and Cerda, 1992;[START_REF] Caballero | Generalized disjunctive programming model for the optimal synthesis of thermally linked distillation columns[END_REF]. However, when talking about flexibility, they almost refer to the optimal operation sequencing or to the optimal system configuration with respect to a given number of different operating conditions. The main purpose of this paper instead is to assess the performances of several configurations under a continuous wide range of operating conditions. In order to do that, a new case study referring to the separation of an ABE/W (acetone, n-butanol, ethanol, water) mixture has been outlined. The history of ABE fermentation and its industrial applications during the 20th century are wide and complex. In 1912 Chaim Weizmann succeeded in isolating a bacterium strain (later named Clostridium acetobutylicum) which was capable of using starch as a substrate in the butanol production process with higher butanol and acetone product yields with respect to the previous ones. The fermentation process via Clostridium acetobutylicum replaced then the previous technology and, with some modifications, it is still the base for the industrial fermentation applications [START_REF] Gabriel | Development of the butyl-acetonic fermentation industry[END_REF]. However, later studies highlighted that these microorganisms used in ABE fermentation still suffer from product inhibition, giving a low acetone and butanol final concentration. A complete review about this process and its future perspectives is provided by [START_REF] García | Challenges in biobutanol production: how to improve the efficiency?[END_REF] .

Due to the high alcohols dilution in the fermentation broth a dewatering extraction column is present downstream the fermenter and before the distillation train. For the same reason the effectiveness of the separation process is a critical variable for the fraction and purity of recovered product.

Biorefinery operations are particularly suitable for flexibility assessment due to the feedstock composition fluctuations during the year as a consequence of the different biomasses to be treated. On the other hand feed perturbations can be also seen as the result of a lower effectiveness in the preliminary dewatering process. In fact, as discussed by Dalle Ave and Adams (2018) , the outlet fermenter composition is strictly related to the selected extractant and to stable operating conditions. However this study will address the entire uncertain domain for water and n-butanol partial flowrates in order to provide a complete overview that could be adapted to different extraction layouts.

Even though the ABE process is a well-established technology and it has been widely studied during the last years, it still results to be one of the most suitable examples for the addressed flexibility assessment due to its highly non-ideal thermodynamics. Due to the presence of homogeneous and heterogeneous azeotropes, liquid-liquid equilibrium and complex activity model, if the system flexibility were evaluated through a sensitivity analysis, it would be very difficult to understand whether the failure to achieve a physical results is due to the actual impossibility of the system to attain the desired specification or to the inability of the algorithm to converge. Further details about thermodynamic flexibility will be then discussed in the corresponding Section 4 .

The nominal feed composition and properties related to this case study are listed in Table 1 .

The successful recovery of at least biobutanol and acetone is considered crucial for the profitability of the operation. In order to accomplish this task, a minimum of two distillation columns are required and three configurations are possible as previously shown in Fig. 3 .

Midsplit configuration specifications are as follows:

1) Split column: Specifications for direct and indirect configuration can be easily deducted from the midsplit ones.

The direct configuration resulted unfeasible under nominal operating conditions. The presence of acetone in the ABE/W mixture improves the separation performance, thus its preliminary removal moves the feed composition of the second column closer to the distillation region boundary (cf chapter 4) causing the desired butanol recovery at the designed purity to be impossible. Only indirect and midsplit configurations will be then discussed and compared.

As already mentioned, the complexity of the proposed case study, mainly caused by its highly non-ideal physical behaviour, results in the impossibility to obtain the desired split specifications independently on the operating conditions. This particular circumstances forces us to find a dedicated tool in order to preliminary assess the physical process limitations (strong flexibility constraints).

The selected methodology to perform the thermodynamic assessment will be then described in detail in the following ad-hoc chapter; in case of mixtures with no singular points, this analysis wouldn't be needed since all sharp splits would be possible with a sufficiently high number of equilibrium stages.

Thermodynamic flexibility analysis

RCMs overview

Thermodynamics of multicomponent mixtures is an everpresent research field in distillation theory. A widespread and well established tool to assess whether a mixture can be separated by distillation is the use of Residue Curve Maps (RCMs) on phase diagrams, usually ternary or quaternary. Despite their usefulness and the robustness of the theory behind them and although they are the more immediate and effective way to analyze the constraints of azeotropic multicomponent systems, RCMs have received relatively poor attention from engineers. These lines were introduced first by [START_REF] Ostwald | Dampfdrucke ternarer gemische, abhandlungen der mathematisch-physischen classe derkonige sachsischen[END_REF] and [START_REF] Schreinemakers | Dampfdrucke ternarer gemische[END_REF] to describe the thermodynamic behavior of three-component azeotropic mixtures but only after half a century [START_REF] Gurikov | Some questions concerning the structure of two-phase liquidvapor equilibrium diagrams of ternary homogeneous solutions[END_REF] developed the first classification of three-component residue curve diagrams. Later [START_REF] Zharov | Free evaporation of homogeneous multicomponent solutions[END_REF]Zharov ( , 1968aZharov ( , 1968b) ) and [START_REF] Serafimov | The azeotropic rule and the classification of multicomponent mixtures. 4. N-component mixtures[END_REF] , [START_REF] Zharov | Physico-Chemical Foundations of Bath Open Distillation and Distillation[END_REF] generalized their application to the analysis and classification of four or higher multicomponent mixtures. However, most of these works were in Russian and were not available in the other countries. The application of residue curve bundles to reversible distillation and to finite reflux distillation column optimal design is due to [START_REF] Petlyuk | Distillation Theory and its Application to Optimal Design of Separation Units[END_REF] and the following discussion will mainly refer to its works.

A residue curve is defined as the locus of compositions satisfying the equation:

dx i dξ = x i -y i (1)
It represents both the change in a mixture composition during an open distillation process and the composition profile of an infinite column at infinite reflux. Each point of this line corresponds to a certain moment of time and to a portion of evaporated liquid as well as to an equilibrium tray of an infinite distillation column. RCMs are convenient for the description of phase equilibrium because they are continuous and noncrossing.

In order to clarify how to read a phase diagram when residue curve mapping is performed a few notation details by referring to Fig. 6 will follow.

• Stable nodes (square): a stationary point at which all residue curves come to an end (the heavy compound (or pseudocompound) of a distillation bundle); • Separatrixes (black line): a boundary separating one bundle from another. In contrast to the other residue curves, the separatrixes begin or come to an end, not in the node points but in the saddle points. A characteristic feature of a separatrix is that in any vicinity of its every point, no matter how small it is, there are points belonging to two different bundles of residue curves; • Immiscibility region (Green): the composition region where two liquid phases are present. The real compositions related to the aqueous and organic phase respectively are those at the extremal points of the corresponding tie line;

• Univolatility line (Red): they are lines where α i j = K i K J = 1 . Univolatility α-lines ( α-surfaces and α-hypersurfaces) divide the concentration simplex into regions of order of components

Reg i jk ord (in Reg i jk ord K i > K j > K k ).
Temperature increases moving from the unstable node to the stable one (the same direction of a residue curve). A residue curves bundle is defined as a subregion with its own stable and unstable points and it is separated by another bundle of the whole concentration space by mean of a separatrix. In case of ideal mixtures the entire concentration space is filled with one RCMs bundle. From a topological point of view while residue curves keep being lines even for a four components system, the separatrix boundaries become surfaces (and hypersurfaces for higher dimension).

Separatrix lines are of critical importance to assess the distillation feasibility since they define at which side of the azeotropic composition the feed is located, i.e. the lightest and heaviest compounds that can be obtained by distillation for a given feed composition. That's why these subregions are also called distillation bundles and separatrixes are also called distillation boundaries. In general, if separatrixes have a relatively regular shape (i.e. not particularly skew) as for the vast majority of mixtures, it can be stated that separation by distillation is possible if feed, distillate and bottom composition points lie in the same distillation region (for further details about the theoretical background please refer to [START_REF] Petlyuk | Distillation Theory and its Application to Optimal Design of Separation Units[END_REF].

Thermodynamic model

As suggested by [START_REF] Errico | Multiobjective optimal acetone-butanol-ethanol separation systems using liquid-liquid extraction-assisted divided wall columns[END_REF] , the selected thermodynamic model for the ABE/W mixture equilibrium description is the Non-Random Two Liquids (NRTL) [START_REF] Renon | Local compositions in thermodynamic excess functions for liquid mixtures[END_REF]. Moreover, it results to be the most appropriate to describe wateralcohols as well as biofuels equilibria in general [START_REF] Kiss | Novel applications of dividing-wall column technology to biofuel production processes[END_REF][START_REF] Okoli | II Design of dividing wall columns for butanol recovery in a thermochemical biomass to butanol process[END_REF][START_REF] Le | Dividing wall columns for heterogeneous azeotropic distillation[END_REF].

The activity coefficient for the species i in a mixture of n components is given by:

ln (γ i ) = j=1 n x j • τ ji • G ji k =1 n x k • G ki + j=1 n x j • G i j k =1 n x k • G k j • τ i j - m =1 n x m • τ m j • G m j k =1 n x k • G k j ( 2
)
where:

ln (G i j ) = -a i j • τ i j
(3)

a i j = a 0 i j + a 1 i j • T (4) τ i j = g i j R • T
(5)

g i j = g i j -g j j = C 0 i j + C 1 i j • T (6)
Not all the process simulators have provided standard binary interaction parameters able to correcty describe the azeotrope location and the liquid-liquid equilibrium. Only Simulis® Thermodynamics values resulted to be reliable for the azeotropes and the liquid-liquid equilibrium prediction, but unfortunately no coefficients for the organic binary mixtures (i.e. n-Butanol-Acetone, Acetone-Ethanol, n-Butanol-Ethanol) were present. In order to have a reliable thermodynamic model, a regression was then used to adjust the missing parameters with respect to experimental equilibrium data.

As it can be noticed in Fig. 6 , the NRTL activity model with the adjusted binary interaction parameters is able to correctly predict liquid-liquid demixing (green region) as well as heterogeneous (empty triangle on the Water-Butanol side) and homogeneous azeotropes (full circle on the Water-Ethanol side) at x water = 0 . 76 3 and x water = 0 . 11 respectively. These values corresponds to those obtained by [START_REF] Luyben | Control of the heterogeneous azeotropic n-butanol/water distillation system[END_REF] for what concerns the heteroazeotrope as well as to the values reported in the Dortmund Data Bank (0 0 0 0) for the homogeneous one. Moreover, the LLE described by the adjusted binary interaction parameters matches with the experimental data provided by [START_REF] Lee | Multiphase equilibria for binary and ternary mixtures containing propionic acid, n-butanol, butyl propionate, and water[END_REF] and agrees with the model prediction of [START_REF] Kosuge | Estimation of isobaric vapor-liquid-liquid equilibria for partially miscible mixture of ternary system[END_REF] .

Thermodynamic feasibility assessment

In the light of the above the thermodynamic feasibility assessment is straightforward. The mixture under analysis shows two azeotropes, namely the water-butanol heterogeneous azeotrope and the water-ethanol homogeneous one. Columns operating conditions and composition profiles are always far from the homogeneous azeotrope; moreover, even once butanol is removed, the presence of acetone mitigates the non-ideal behaviour of the remaining fractions. It can be then concluded that the critical operation in both midsplit and indirect configuration is the butanol separation even because the most likely perturbations downstream the fermenter are related to water and butanol relative content. Since RCMs refer to infinite columns at infinite reflux, the analysis of the sharp split AEW/B holds true for the midsplit configuration as well.

Given the feed composition and the butanol product purity the corresponding two points can be plotted in a quaternary phase diagram as shown in Fig. 7 a (violet diamonds). Since recovery ratio is fixed the lever rule resulting from mass balances can be applied in order to obtain the third point related to the distillate composition. The RCMs passing through these points were then calculated and plotted as well. It can be noticed that all these RCMs have the same stable and unstable nodes, that means separation by simple distillation is possible under nominal operating conditions.

In order to assess the thermodynamic feasibility boundaries the uncertain variables need to be perturbed. The most constraining variable is the water content in the feed stream, in particular we expect the distillation to be more critical, i.e. the butanol recovery at the desired purity to be more difficult, for a higher water fraction. The increase in water partial flowrate keeping unchanged the amount of the other components in the mixture can be represented on phase diagrams by moving the feed characteristic point along the line connecting the actual feed point and the pure water vertex (cf black arrow in Fig. 7 a). For an increase in the water content up to 8% the RCMs corresponding to distillate, feed and bottom still lie in the same distillation bundle as shown in Fig. 7 b. When a 9% deviation is applied, on the contrary, the stable node of the residue curve related to the distillate stream moves from pure butanol to pure water, i.e. it crosses a separatrix (cf Fig. 7 c). The separatrix crossing results in the impossibility of obtaining such a distillate from the given feed by mean of a distillation. The same analysis was carried out with respect to each of the four components. As expected, the water molar fraction resulted to be the most constraining variable from a flexibility point of view. It can be then stated that the system thermodynamic flexibility limit is about 8%. This value represents the chemico-physical constraint to this operation whatever the affordable investment to design the distillation train is. If a higher flexibility is required the only possible solution is to select a different separation process for such a mixture.

The same procedure was performed for the F SG index, i.e. by simultaneously varying both butanol and water partial flowrates, and a value about 5% was found.

Residue curve maps analysis was carried out by interfacing Matlab®, used to solve the ODE system 1 and to plot the corresponding graphs, to the software Simulis® Thermodynamics aimed to provide the equilibrium data related to the NRTL model previously described.

Economic assessment and optimal design under uncertain conditions

As already mentioned, the ordinary design procedure has been conducted as usual: CAPital and OPerating EXpenses have been evaluated for each column of the two configurations at different numbers of stages with the optimal feed location under nominal operating conditions. Considering a life span of 10 years, for each column the number of stages corresponding to the minimum annualized cost, given by the expression

T AC = OP EX + CAP EX li f etime (7)
was then identified and the overall annualized cost of each configuration was calculated. All simulations required for the columns design were carried out by mean of ProSim Plus® process simulator. An equilibrium based distillation model with no simplifying assumptions was employed. Among the several available distillation column models, the three-phase distillation column model accounting for liquid phase demixing was selected. Optimal number of stages, feed tray and relative TAC for each column of each configuration are listed in Table 2 .

With a total cost of 933,509 $/y vs 1,084,082 $/y the indirect configuration results to be the most convenient with respect to the midsplit one under nominal operating conditions. The addition of a preliminary column indeed does not substantially affect the acetone column utilities consumption.

In order to validate this design configuration under uncertain conditions the flexibility analysis should be then performed. The most critical parameters, as already discussed in chapter 4, are water and butanol feed content, that's why their partial flowrates were selected as uncertain parameters for the analysis. The flexibility assessment results via process simulation confirmed the preliminary thermodynamic evaluation providing a F SG value about 5% (4% for the midsplit) and a RI value about 8% (7% for the midsplit) for both configurations as shown in Fig. 8 . With a proper deviation range discretization, several simulations were run over the whole uncertain domain by using as process variables initial guess the previously converged values in the closest point; the green squares refer to simulations that revealed themselves as feasible and operable, while blue squares correspond to operating conditions that didn't allow the specifications achievement.

In particular midsplit configuration resulted slightly less flexible due to the difficulty to recover enough acetone without the preliminary butanol removal. The stochastic index SF corresponding values are respectively 77.86% for the indirect configuration and 75.85% for the midsplit configuration in case of a perturbation normal PDF with a 10% variance (i.e. more than 99% disturbance likelihood within the 30% disturbance range). This PDF parameters were selected taking into account the higher butanol concentration boundary in the fermentation broth due to product inhibition [START_REF] García | Challenges in biobutanol production: how to improve the efficiency?[END_REF] and in a way that water perturbations, related to the dewatering process inefficiency, affected the analysis result with a comparable magnitude. The F V volumetric flexibility index analysis was not carried out since it can be reconducted to a particular case of the stochastic flexibility assuming a step PDF for the uncertain variables as shown by Di [START_REF] Di Pretoro | Flexibility analysis of a distillation column: indexes comparison and economic assessment[END_REF] .

Given these results the indirect configuration results slightly more flexible than the midsplit one. However, the higher flexibility of a process design is not sufficient to provide its final validation under uncertain conditions until its higher profitability is proved as well.

Flexibility analysis was then coupled to the economic assessment according to the procedure suggested by Di [START_REF] Di Pretoro | Flexibility analysis of a distillation column: indexes comparison and economic assessment[END_REF] . The costs corresponding to every perturbed operating conditions were calculated and correlated to the different flexibility values by mean of the corresponding indexes. Even in this case the cost of an additional preliminary column was not compensated by a lower utility consumption and the indirect design still results the more convenient. Total annualized costs vs. partial flowrates perturbations have been plotted for the indirect configuration in Fig. 9 . An analogous trend with higher values was obtained for the midsplit configuration. Costs result to be higher whether a bigger oversizing is necessary, i.e. positive deviation for both water and butanol flowrates, and under operating conditions close to the feasibility boundary. Fig. 10 shows for instance the trend of the first column reboiler heat transfer surface area, that is one of the most sensitive parameters, varying over a range going from 393 to 538 m 2 , i.e. more than 35% deviation with respect to the nominal operating conditions value.

The plot resuming the indirect configuration additional cost vs. flexibility for the deterministic indexes is then reported in Fig. 11 .

The shaded regions represent the flexibility limit that can't be overcome despite the affordability of a higher expense. As expected by their definition the F SG index results more conservative than the RI one since it involves the simultaneous deviation of all the uncertain variables at once. Moreover in both cases it can be noticed that after 4% flexibility (7% for RI ) much higher additional investments are required for a corresponding flexibility increase of 1% only.

The stochastic flexibility SF index trend is plotted in Fig. 12 . Differently from deterministic indexes, stochastic flexibility has non-null value even at nominal operating conditions since the de-signed system is already able to withstand part of the negative perturbations. Another characteristic feature of this index is the asymptotical trend when SF approaches the feasibility boundary value. This behaviour is independent on the selected PDF and its interpretation is that an always increasing investment should be afforded if the lowest risk of underperformance has to be attained.

The conclusions that the engineer or the decision maker in general can derive from these results are different and mainly depend on his needs and his resources. In general, except if really needed, it is not profitable to design a system in the region after the cost vs. flexibility line slope increase or close to the asymptote in case SF is used. Moreover, if a stochastic analysis is performed, an optimal design region can be calculated as shown in [START_REF] Di Pretoro | Flexibility analysis of a distillation column: indexes comparison and economic assessment[END_REF].

An alternative solution in case of plant capacity variation across the year could be the design of more than one unit in parallel and shut down/start up scheduling optimization for some of them according to the feed to be processed. In general this option is rather expensive but in specific cases it can meet other system needs (e.g. safety, maintenance operations etc) and thus become more convenient.

Conclusions

The aim of this paper is to define a thorough procedure to design a distillation train under uncertain conditions. This procedure is based on an economic and flexibility multi-criteria design optimization and analysis of the possible train configurations. A biorefinery products separation section was selected as case study due to the characteristic fluctuations related to fermentation processes; in particular the object of this analysis was the ABE process since among the biomass based processes it is one of those with the most promising future perspectives according to the goals of the fossil fuel replacement politics.

An a priori thermodynamic feasibility assessment was carried out via residue curve maps to evaluate the maximum attainable flexibility from a physical point of view and its results were confirmed by process simulation. Then the standard design procedure was carried out to detect the best configuration under nominal operating conditions. It was then followed by a flexibility assessment coupled to an economic analysis to validate the result. Both deterministic and stochastic indexes have been used in order to make a comparison and provide a complete overview according to several possible perturbation natures.

The final product of this procedure is an additional costs vs. flexibility plot allowing the decision maker to make the most possible informed choice.

The indirect configuration, that was the cheapest one under nominal operating conditions, resulted to be also slightly more flexible than the midsplit configuration. The economic gap due to the additional column is not compensated by a lower external duty demand and it is conserved under uncertain conditions as well. Although this design solution provides a maximum flexibility of F SG = 5% ( RI = 8% and SF = 77 . 86% ) it can be stated that beyond F SG = 4% ( RI = 7% and SF = 67% ) it is less worth investing since the additional costs line becomes steeper.

Beside the numerical results, the outcome of general validity is that, in thermodynamically constrained system, the feasibility and flexibility boundaries cannot go over a certain value by investing more. An a priori flexibility analysis and economic assessment could then be crucial for making the best design choice and to know the system limitation if perturbations are likely to occur.

Finally it is worth remarking that, even if the provided results are case specific, the proposed procedure can be considered valid for any analogous case study.

Fig. 1 .

 1 Fig. 1. Conventional design procedure.

Fig. 2 .

 2 Fig. 2. Flexible design procedure.

Fig. 3 .

 3 Fig. 3. Distillation train configurations for two components recovery.

Fig. 4 .

 4 Fig. 4. Flexibility index ( F SG ) vs Resilience Index ( RI ) ( Di Pretoro et al., 2019 ).

Fig. 5 .

 5 Fig. 5. Stochastic Flexibility ( SF ) assessment of a heat exchanger ( Di Pretoro et al., 2019 ).

  (a) Acetone recovery ratio in the distillate: 0.995; (b) n-Butanol recovery ratio in the bottom: 0.98; 2) Acetone recovery column (top column): (a) Acetone recovery ratio in the distillate: 0.995; (b) Distillate acetone mass fraction: 0.995; 3) n-Butanol recovery column (bottom column): (a) n-Butanol recovery ratio in the bottom: 0.98; (b) Bottom n-butanol mass fraction: 0.99.

Fig. 6 .

 6 Fig. 6. RCMs on a ternary diagram.

Fig. 7 .

 7 Fig. 7. Feasibility boundaries assessment via residue curve maps.

Fig. 8 .

 8 Fig. 8. Indirect vs midsplit feasibility (Green +: feasible, Blue x: unfeasible). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 9 .

 9 Fig. 9. Total annualized costs vs. partial flowrates perturbations.

Fig. 10 .

 10 Fig. 10. First column reboiler heat transfer surface.

Fig. 11 .

 11 Fig. 11. Deterministic indexes economic comparison.

Fig. 12 .

 12 Fig. 12. Additional costs vs. stochastic flexibility.

Table 1

 1 Feed composition and physical properties.

	Component \ Property	Value	Unit
	Acetone	12.030	mol / s
	n-Butanol	61.328	mol / s
	Ethanol	3.839	mol / s
	Water	12.428	mol / s
	Pressure	101.325	kPa
	Temperature	361.26	K

Table 2

 2 Distillation train optimal design.

			Indirect	Midsplit
	1st Column	N (feed)	16 (10)	35 (9)
		Cost ($/y)	580 016	455 493
	2nd Column	N (feed)	50 (46)	50 (47)
		Cost ($/y)	353 493	352 224
	3rd Column	N (feed)	/	16 (8)
		Cost ($/y)	/	276 365
	Total cost		933 509	1 084 082

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. List of acronyms and symbols

Symbol

Appendix B. Capital costs estimations

In order to evaluate the investment cost required for the whole system or make any kind of economic consideration and comparison, the cost of every single unit needs to be estimated.

For this purpose the Guthrie-Ulrich-Navarrete correlations described in the next paragraphs will be used [START_REF] Guthrie | Capital cost estimating[END_REF][START_REF] Guthrie | Process Plant Estimating, Evaluation, and Control[END_REF][START_REF] Ulrich | A Guide to Chemical Engineering Process Design and Economics[END_REF][START_REF] Navarrete | Planning, Estimating, and Control of Chemical Construction Projects[END_REF].

B1. Purchase equipment cost in base conditions

The purchase equipment cost in base conditions is obtained by mean of the following equation:

where A is the characteristic dimension and the K i coefficients are relative to the equipment typology (cf. Table 3 ). The provided coefficients refer to the year 2001 and to a M&S index equal to 1110. In order to update the costs estimation to the year 2016 calculations will refer to a M&S index equal to 1245.2 by mean of the correlation:

B2. Bare module cost

The equipment bare module cost can be calculated according to the following correlation:

where the bare module factor is given by:

The F M and F P factors refers to the actual constructions materials and operating pressure while the B i coefficients refers to the equipment typology (cf. Table 4 ). The F P,Kettle value is given by: log 10 (F P ) = 0 . 03881 -0 . 11272 • log 10 (P ) + 0 . 08183 • [ log 10 (P )] 2 (B.5

where P is the relative pressure in bar .

For column trays bare module cost a slightly different correlation should be used:

where N is the real trays number, F BM = 1 e F q is given by the correlation:

Supplementary material

Supplementary material associated with this article can be found, in the online version, at doi: 10.1016/j.compchemeng.2020. 106831 .

CRediT authorship contribution statement

Alessandro Di Pretoro: Conceptualization, Methodology, Writing -original draft. Ludovic Montastruc: Conceptualization, Methodology, Writing -review & editing. Flavio Manenti: Supervision. Xavier Joulia: Conceptualization, Methodology, Writing -review & editing, Supervision.


Nikola Ž Knežević

Vanja Stojanovic

Arnaud Chaix

Khaled Elise Bouffard

El Cheikh

Alain Morère

Marie Maynadier

Gilles Lemercier
email: gilles.lemercier@univ-reims.fr

Marcel Garcia

Magali Gary-Bobo
email: magali.gary-bobo@univ-montp1.fr

Dr Frédérique Cunin
email: frédérique.cunin@enscm.fr

Khaled El Cheikh

Jean-Olivier Durand

Ruthenium(II) Complex-Photosensitized Multifunctionalized Porous Silicon Nanoparticles for Two-Photon Near-Infrared Light Responsive Imaging and Photodynamic Cancer Therapy

come   L'archive ouverte pluridisciplinaire

Introduction

Photodynamic therapy (PDT) is rapidly advancing anticancer therapy which is nowadays increasingly applied in the clinical praxis alongside surgery, radiotherapy and chemotherapy. 1 This treatment option involves administration of chemical photosensitizers (PSs) and exposure of the diseased tissue to light irradiation with appropriate wavelength to induce formation of highly cytotoxic singlet oxygen ( 1 O 2 ) and reactive oxygen species (ROS), to induce cell death. In recent years research efforts have been dedicated to utilize nanomaterials for PDT of cancer, [2][3][4][5][6] which would be beneficial in terms of increasing efficacy and reducing side effects of the treatment,

with the possibilities for simultaneous targeted treatments and real time diagnostics. 8 Porous silicon nanoparticles (pSiNPs) are among the most promising types of nanocarriers for biomedical applications since the first publication by M. J. Sailor in 2009 on their application for in vivo treatment. 9 Composed of pure silicium, pSiNPs are distinguished by their spontaneous degradability in aqueous environment. In addition, pSiNP is characterized by high specific surface area, high capacity for drug loading and surface functionalization, high biocompatibility and low toxicity in-vivo. 10 Furthermore, pSiNP is intrinsically fluorescent material which can be applied for imaging and real time diagnostics even without the need for surfacefunctionalization. 10,11 During the past decades, various types of PS molecules such as porphyrin, 2 phthalocyanine, 12 chlorine 13 derivatives have been applied for PDT, which typically function by exposure to UV or visible light. However, the low light-penetration depth (millimeters) and occurrence of tissue photo-damage limits the applicability of this spectral range for PDT, which can be circumvent by application of near-infrared irradiation (NIR)(750-1100 nm), and particularly two-photon excitation (2PE) which is just emerging for PDT applications and allows deeper penetration in biological tissues (2 cm) and lower scattering losses. Furthermore 2PE allows a three dimensional spatial resolution, with a spatio-temporal control which are essential features for a very precise treatment of cancer using PDT. [START_REF] Benninger | Current protocols in cell biology / editorial board[END_REF] One of the pathways for NIR-responsive PDT has been demonstrated in the literature through laser excitation (at 980 nm) of up-converting nanoparticles which than emit higher energy light for excitation of PS. [START_REF] Qiao | [END_REF][16][17] However, this process is not highly efficient, particularly at 980 nm excitation due to substantial absorption of light by water at this wavelength. Furthermore up-converting NPs are not biodegradable and they lack the three dimensional accuracy which is characteristic for the 2PE process. Several ruthenium(II) complexes have been shown recently as promising photosensitizers, demonstrating their capabilities for absorption in the visible and ultra violet spectrum, which occurs by one-photon excitation (1PE) mechanism, as well as for NIR excitation due to the existence of long-lived triplet Therefore, coordination compounds of ruthenium(II) have been showcased recently as biocompatible, potent molecules for NIR-responsive cellular imaging, 19 and for 2PE-PDT. 20,21 However, these molecular PSs lack the cancer-targeting capabilities, which are achievable with more complex PS-nanoparticle conjugates due to enhanced permeability and retention (EPR) effect, 22 and surface functionalization strategies with ligands specific for cancer-overexpressed receptors. 23 Moreover, the attachment of PS to the nanomaterial would increase the uptake of PSs by cancer cells, as it is typical for drug nanocarriers. 24 Hence, the increased uptake of PSs by cancer cells is expected to increase the yields of 1 O 2 and ROS production within cancer cells, leading to enhanced therapeutic efficacies of PS-nanoparticle conjugates over individual PS molecules. The covalent conjugation of Ru(II) complexes to nanocarriers in order to improve 2PE-PDT applications has not been investigated yet.

Recent study demonstrated applicability of single-wall carbon nanotubes (SWCNT) for delivery of Ru(II) photosensitizer to cancer cells, which in fact increased efficacy of the photosensitizer when compared to the treatment with the molecular PS. 25 However, in this composite material the photosensitizer was physically adsorbed to the surface of SWCNT with the risk of leakage from the SWCNT matrix, while no investigation was conducted on efficacy of 2PE-PDT upon functionalization with PEG and cancer-targeting ligands. Furthermore, SWCNT nanocarrier is not biodegradable as in the case of pSiNP-based therapeutics.

In this study, we report a novel Ru(II) complex for NIR (2PE)responsive PDT, along with the first pSiNP-based material containing Ru(II) complex-PS covalently attached to its surface for 2PE-PDT and 2PE-imaging application assessments. In addition, surface functionalization with polyethylene glycol (PEG) moieties was performed, essential for improving dispersibility and biocompatibility, along with attachment of mannose molecules, for enabling selective targeting of tumor tissues (Scheme 1). 26 The newly synthesized ruthenium(II)

complex ion [Ru(5-Fluo-Phen) 2 (5-E-Phen)] 2+ , (5-Fluo-Phen) = 5dihexylfluorene-1,10-phenanthroline and (5-E-Phen) = 5ethynyl-1,10-phenanthroline, was covalently attached on pSiNP, along with PEG and Mannose, and we characterize their capabilities for two-photon imaging and in vitro 1PE-PDT and 2PE-PDT on breast cancer cells (MCF-7) upon exposure to blue light (430 nm) and short pulses (3 x 1,57 s) of near infrared (800 nm) irradiation.

Experimental section

Surface functionalization of pSiNP with [Ru(5-Fluo-Phen) 2 (5-E-Phen)] 2+

A mixture of [Ru(5-Fluo-Phen) 2 (5-E-Phen)](PF 6 ) 2 (10 mg) in 10 ml of dry THF was prepared and suspension of pSiNP (70 mg) in dry THF (10 ml) was added. The reaction suspension was degassed for 30 min and refluxed at 50 ˚C under nitrogen atmosphere for 18 h. The product was then centrifuged at 14 000 rpm for 30 min, washed with THF three times, once with ethanol and kept suspended in ethanol until further use.

Attachment of ICPES-PEG to the surface of the pSiNP-Ru

The suspension of pSiNP-Ru (50 mg) in EtOH was centrifuged at 14 000 rpm for 30 minutes, washed once with dry DMF and redispersed in dry DMF (10 ml). A second flask containing O,O'-Bis(3-aminopropyl)polyethylene glycol (M~1.500, 0.15 g, 0.1 mmol) in 5 mL of dry DMF was prepared and isocyanopropyltriethoxysilane (ICPES) (26 μL, 0.1 mmol) was added dropwise under vigorous stirring. The reaction was stirred under nitrogen atmosphere for 3h and the suspension containing pSiNP-Ru was added. The reaction mixture wasdegassed for 30 min and refluxed at 80 ˚C for 18 h. The product (pSiNP-Ru-PEG) was centrifuged, washed three times with DMF and two times with ethanol. The material pSiNP-Ru-PEG was kept in the form of suspension in ethanol until further use.

Attachment of mannoseethylsquarate to pSiNP-Ru-PEG

Mannoseethylsquarate (17 mg, 49 μmol) was dissolved in 10 mL of demineralized water and added to the suspension ofpSiNP-Ru-PEG (47 mg) in ethanol (10 mL). The suspension was degassed for 30 min and refluxed at 80 ˚C for 18 h. The product was centrifuged at 14 000 rpm for 30 minutes, washed three times with EtOH, resuspended and kept in ethanol until further use.

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Cell cultures

Human breast cancer cells MCF-7 (purchased from ATCC) were cultured in DMEM supplemented with 10% fetal bovine serum and 50 μg•mL -1 gentamycin. All cells were allowed to grow in humidified atmosphere at 37°C under 5% CO 2 . For in vitro experiments, cells were seeded into a 384 multiwell glass bottomed plate (thickness 0.17 mm), with a black polystyrene frame. One day after seeding cells were treated at 80 µg•mL

Results and Discussion

The pSiNP were constructed according to the published procedureby electrochemical etching of boron doped silicon wafer in an ethanolic hydrofluoric acid (HF) electrolyte, then electropolished in order to remove the porous silicon layer. 9

Afterwards, the obtained porous silicon was fractured by ultrasonication for 16 hours and microparticulate fragments were separated from the nanoparticles (pSiNP) by centrifugation. 11 The pSiNP were then characterized by Transmission Electron Microscopy (TEM), which reveals particles of diameter range 50-450 nm and their mesoporous texture (Figure 1a,b). Absorption spectrum of pSiNP reveals broad band in the UV region which also extends into visible portion of the spectrum (Figure S1a). Nitrogen adsorption and desorption measurements showed that pSiNP has a mesoporous structure with high specific surface area of 560 m²/g and a BJH (Barrett-Joyner-Halenda) desorption average pore diameter of 12.3 nm (Figure S1.b). The dynamic light scattering (DLS) revealed the average size of the pSiNP at 226 nm with polydispersity of 0.30, measured by intensity percent of scattered light Biodegradability of pSiNP was confirmed by stirring the material in aqueous suspension for a prolonged time and by measuring the mass of the centrifuged material (Figure S2).

The result reveals that mass of the material decreases over the measured period of 10 days which indicates slow degradation of pSiNP by aqueous hydrolysis. We synthesized the novel photosensitizer ruthenium(II) coordination complex ion [Ru(5-Fluo-Phen) 2 (5-E-Phen)] 2+ by ligand substitution in DMF solution and attached it to the surface of pSiNP by hydrosilylation of the terminal alkyne group of the 5-E-Phen ligand to the Si-H surface moieties on pSiNP, which yielded pSiNP-Ru material (Scheme 1). Attachment of bifunctionalized PEG moiety was than performed by coupling its one amine end to the isocyanatopropyltriethoxysilane (ICPES) and subsequent grafting on the surface of pSiNP-Ru through silanization to obtain pSiNP-Ru-PEG material. Finally, mannoseethylsquarate was covalently bonded to the other end of surface attached PEG moieties though nucleophilic substitution on the squarate moiety and yielded pSiNP-Ru-PEG-Man material. The attachment of all functional groups was confirmed by DRIFT and zeta potential measurements (Figure 2). After the hydrosilylation of the freshly etched pSiNP with the Ru(II) complex, new intense bands appeared at 2930 cm -1 and 2860 cm -1 which correspond to the stretching vibrations of C-H bonds. In addition, aromatic and aliphatic carbon-carbon stretching vibration bands are observed at 1450 cm -1 and 1380 cm -1

, respectively, arising from the attached Ru(II) complex. Concomitantly, intensity increase of the broad band centered at 1055 cm -1 which arises from the stretching Si-O vibrations, along with the appearance of broad band above 3000 cm -1

, corresponding to the stretching O-H vibrations, points to an occurrence of simultaneous competing oxidation reaction of the surface Si-H during the hydrosilylation reaction. In case of the pSiNP-Ru-PEG material a new band appearing at 1570 cm S3). Similarly, the mannose content in pSiNP-Ru-PEG-Man was determined after complete dissolution of the material in 1M KOH, followed by adjustment of previously published colorimetric method (Figure S5). 27 The measured values series of nanomaterials and incubated for 5 h, after which the cells were exposed to blue light irradiation (420-440 nm, 14 J•cm -2 ) for 20 min. After two days of incubation, a cell proliferation assay (MTS) was performed to determine the phototoxicity of the different functionalized materials (Figure 3a). Upon monophotonic excitation with blue light (1PE-PDT) the non-functionalized pSiNP induced 13% of cell mortality. However, in the case of the 1PE-PDT with functionalized materials, more efficient cell mortality was noted, i.e. 43%, 26% and 21% for pSiNP-Ru, pSiNP-Ru-PEG and pSiNP-Ru-PEG-Man, respectively. These results show the ability of the pSiNPbased materials to generate 1 O 2 and ROS under monophotonicexcitation. In addition, the photodynamic efficiency of the Ru(II) complex under 1PE can be evidently increased when attached to the pSiNP compared to the free Ru(II) complex efficiency (Figure S8.a). This underlines the role of the pSiNP in the vectorization of the Ru(II) complex photosensitizer to the cells. Decrease in PDT efficacy of the materials in the order: pSiNP-Ru > pSiNP-Ru-PEG > pSiNP-Ru-PEG-Man can be rationalized by the decreasing PS (Ru(II) complex) content in the same order. In vitro 2PE-PDT experiments using the same pSiNP-based materials were also performed at the treatment concentration of 80 μg•mL -1 and pre-incubation for 5 h with MCF-7 cancer cells. Two-photon excitation was achieved using a Carl Zeiss confocal two-photon microscope (maximal laser input power 3 W). The wells were irradiated by 3 laser pulses of 1.57 s each at the irradiation wavelength of 800 nm, using the 10-fold magnification/objective 0.3 EC Plan-Neofluar. Two days after irradiation, the percentage of living cells was determined by MTS assay (Figure 3b). The results reveal that two-photon excitation is also a viable option to induce PDT in cancer cells. O 2 and ROS upon the twophoton excitation. 11 In comparison, in the case of the treatment with Ru(II)-photosensitizer-functionalized pSiNP, viability of the cancer cells decreased to 36 % which clearly shows the ability of the Ru(II) complex to increase the efficacy of pSiNP material for PDT upon near-infrared irradiation. In the case of 2PE the photodynamic effect of the pSiNP-Ru is significantly enhanced in comparison to the 2PE-PDT efficiency of the free Ru(II) complex (Figure S6.b), and to the efficiency ofbare pSiNP. Additional surface functionalization with PEG moieties unexpectedly decreases 2PE-PDT efficacy significantly. However, the presence of mannose is clearly beneficial as the viability of the cells treated with pSiNP-Ru-PEG-Man decreased to 69%, a significant difference to the viability of non-irradiated cells (p < 0.05), which is not the case for pSiNP-Ru-PEG-treated cells. This result can be ascribed to the better cell-internalization of the nanoparticles containing mannose moieties. Hence, we demonstrate in this study that even though the presence of PEG moiety hinders the photodynamic efficiency of the PS-functionalized pSiNP under 2PE, the presence of cancer-targeting mannose moiety is capable of overcoming this adversity through increased cell uptake. This result is promising en route for clinical application of nanomaterials for 2PE PDT, considering that PEG, or similar stealth-enabling molecules, are necessary constituents of nanotherapeutics for avoiding premature clearance from a biological environment. In order to assess the capabilities of the prepared materials for two-photon imaging, the non-functionalized pSiNPs and functionalized-pSiNPs were incubated for 5 h at a concentration of 80 μg•mL -1 with breast cancer cells (MCF-7)

and the two-photon fluorescence imaging of living MCF-7 cells was performed at 800 nm excitation wavelength with a Carl Zeiss two-photon confocal microscope (Figure 4). As evident, pSiNP material could not be detected by this method (Figure 4a) while the red color of Ru(II)-complex-containing materials was observed by the two-photon fluorescence imaging (Figure 4b-d, Figure S5.c for Ru(II) complex). Moreover, the twophoton imaging confirmed successful endocytosis of the PSfunctionalized materials by MCF-7 cells and the uptake of pSiNP-Ru-PEG-Man was clearly more efficient than the uptake of pSiNP-Ru-PEG, which further supports the applicability of mannose as cancer-targeting moiety. The usefulness of PEG moiety is also evident by comparing the images of the cells treated with PEG-lacking pSiNP-Ru material and PEGcontaining materials. Namely, PEG moiety contributed to better dispersion of the nanoparticles, which would be beneficial for prolonged blood circulation of the functionalized nanotherapeutics.

Conclusions

We have successfully constructed porous silicon-based nanomaterial functionalized with [Ru(5-Fluo-Phen) 2 (5-E-Phen)] 2+ as a photosensitizer, polyethylene glycol moiety for Please do not adjust margins Please do not adjust margins

Scheme 1 .

 1 Scheme 1. Reaction pathways for the construction of the materials; a) hydrosilylation of [Ru(5-Fluo-Phen)2(5-E-Phen)] 2+ to the surface through the terminal alkyne moiety, followed by b) silanization of surface hydroxyls with amine-terminated PEG and c) attachment of mannose through squarate moiety.

- 1 concentration

 1 with 4 different nanostructures -porous silicon nanoparticles (pSiNP), porous silicon nanoparticles functionalized with ruthenium (pSiNP-Ru), porous silicon nanoparticles functionalized with ruthenium and polyethylene glycol (pSiNP-Ru-PEG) and porous silicon nanoparticles functionalized with ruthenium, PEG and mannose (SiNP-Ru-PEG-Man); and at 2.1 μg•mL -1 concentration with Ru(5-Fluo-Phen) 2 (5-E-Phen)](PF 6 ) 2 . Cells were incubated 5 h and then irradiated for 1 photon or 2 photon excitation (1PE or 2PE). 1PE was performed on LEICA DM IRB microscope at 420-440 nm wavelengths during 20 min. 2PE was performed on LSM 780 confocal microscope at 800 nm in the duration of 3 x 1,57 s. To measure the cell death, MTS assay was performed 48 h after irradiation and results were read on Thermo scientific multiscan FC instrument at the absorbance of 492 nm.For two photon imaging cells were incubated 5 h with 80 μg/mL nanoparticles and 2.1 μg•mL -1 Ru(5-Fluo-Phen) 2 (5-E-Phen)](PF 6 ) 2 . Cell membranes were co-stained with Cell maskTM Orange plasma membrane stain in the concentration of 1 µl•mL -1 and after 15 min of incubation on 37˚C and 5% CO 2 cells were washed with Gibco DMEM (1x) and observed on LSM 780 Zeiss confocal microscopy (63x oil). Cell membranes were visualized in green at 560 nm, and NPs were visualized at 800 nm.

Figure 1 .

 1 Figure 1. Transmission electron micrographs of pSiNP (a, b) and pSiNP-Ru-PEG-Man (c, d) (Figure S1.c). However, the corresponding value revealing scattering normalized to the number of particles of specific diameter indicates that most of the particles have a diameter less than 100 nm, with the most prevalent at 79 nm (Figure S1.d).Biodegradability of pSiNP was confirmed by stirring the material in aqueous suspension for a prolonged time and by measuring the mass of the centrifuged material (FigureS2). The result reveals that mass of the material decreases over the measured period of 10 days which indicates slow degradation of pSiNP by aqueous hydrolysis. We synthesized the novel photosensitizer ruthenium(II) coordination complex ion [Ru(5-Fluo-Phen) 2 (5-E-Phen)]2+ by ligand substitution in DMF solution

- 1 ,

 1 assignable to the amide moiety formed in the reaction between ICPES and NH 2 -PEG-NH 2 , indicates successful coupling This journal is © The Royal Society of Chemistry 20xx Please do not adjust margins Please do not adjust margins

Figure 2 .

 2 Figure 2. DRIFT spectra of the synthesized materials. Inset shows values for ζ potential of the corresponding materials of pSiNP-Ru with PEG moiety. After attachment of mannoseethysquarate to the pSiNP-Ru-PEG material a shoulder at 1180 cm -1 appears in the DRIFT spectrum, which points to the existence of the carbohydrate C-O bonds in the pSiNP-Ru-PEG-Man material. Zeta potential measurements further evidence the successful surface functionalizations (Figure 2 inset). The bare pSiNP material exhibited highly negative surface charge (-28 mV), which is due to partial oxidation of the surface and deprotonation of the surface silanols. After grafting the positively charged Ru(II) complex ion onto the pSiNP surface the zeta potential value expectedly changes to less negative charge (-3.2 mV). Further functionalization with PEG moieties leads to highly positively charged surface (28.8 mV) which indicates successful attachment of the functional group containing charged amine ending groups. After the attachment of mannose to these amine groups the surface charge expectedly decreases to 13.8 mV. Transmission electron micrographs of the pSiNP-Ru-PEG-Man material (Figure 1c,d) reveal that the mesoporous texture of the material did not change after the functionalization reactions. Concentration of the Ru(II) complex was determined in all materials upon complete dissolution of the silicon carrier in 1M KOH:EtOH solution, by UV-Vis spectroscopy (FigureS3). Similarly, the mannose content in pSiNP-Ru-PEG-Man was determined after complete dissolution of the material in 1M KOH, followed by adjustment of previously published colorimetric method (FigureS5).27 The measured values

  quantified in the form: quantity of the attached moiety/mass of the parent material, are as follows: Quantity of [Ru(5-Fluo-Phen) 2 (5-E-Phen)] 2+ in: pSiNP-Ru: 18.0 μg•mg -1 (13.6 nmol/mg), pSiNP-Ru-PEG: 17.2 μg•mg -1 (13.0 nmol/mg), pSiNP-Ru-PEG-Man: 16.0 μg•mg -1 (12.0 nmol/mg), quantity of mannose ethyl squarate moiety in pSiNP-Ru-PEG-Man: 45.2 μg•mg -1 (147 nmol/mg). The mass ratio of Ru(II) in the materials expectedly decreases upon attachment of the additional functional groups which increase the total mass of the nanoparticles. The efficacy of 1PE and 2PE photodynamic treatment with suspensions of pSiNP, pSiNP-Ru, pSiNP-Ru-PEG, and pSiNP-Ru-PEG-Man was investigated in vitro on breast cancer cell line MCF-7. All synthesized materials exhibited high dispersion stability in aqueous environment, with no evidence of precipitation. Cytotoxicity evaluation of the prepared materials without exposure to light is shown on Figure S7. In case of 1PE-PDT experiments the cells were treated at 80 μg•mL -1 with the

Figure 3 .

 3 Figure 3. In vitro photodynamic effect of pSiNP, pSiNP-Ru, pSiNP-Ru-PEG and pSiNP-Ru-PEG-Man on MCF-7 cells. a) 1PE irradiation (420-440 nm, 14 J•cm -2 , for 20 min); b) 2PE irradiation (800 nm, 3 scans of 1.57 s). Bar graphs represent means of triplicates ± standard deviation.Statistical analysis was performed using the Student's test to compare paired groups of data. *: p < 0.05 was considered to be statistically significant.

Figure 4 .

 4 Figure 4. Multiphoton imaging of living MCF7 cells, incubated 5 h with 80 μg/mL nanoparticles (a) pSiNP, b) pSiNP-Ru, c) pSiNP-Ru-PEG, d) pSiNP-Ru-PEG-Man) and co-stained with a membrane marker (green). Fluorescence images were captured with spectral detector during a 800 nm two-photon excitation. Photos are representative of at least 3 independent experiments. Left: cell membrane staining, middle: nanomaterial, right: merge of the two images.improving the biocompatibility, and with mannose molecules as targeting moieties for photodynamic therapy of cancer. The multifunctionalized-pSiNPs exhibit potent capabilities for twophoton imaging of MCF-7 cells. Cytotoxic effects of the synthesized materials were demonstrated by exposing the treated cancer cells to blue and near infrared light irradiation, which led to 1PE-and 2PE-induced cancer cell death, respectively. The obtained results are promising for improvement of PDT therapy and further work is ongoing for optimization of pSiNP-based PDT nanotherapeutics for in vivo treatment of cancers.

This journal is © The Royal Society of Chemistry 20xx J. Mater.Chem. B, 2016, 00, 1-3 | 3

This journal is © The Royal Society of Chemistry 20xx J. Mater.Chem. B, 2016, 00, 1-3 | 5

Acknowledgements

The ANR (Agence Nationale pour la Recherche, programme Blanc inter I SIMI 10, edition 2012) is gratefully acknowledged. The authors thank T. Cacciaguerra for the TEM imaging. N. Z. Knezevic and V. Stojanovic contributed equally to this work.