Laëtitia Diez
email: laetitia.diez@univ-lorraine.fr

Maintenance contribution to promote the regeneration paradigm

Keywords: maintenance, sustainability development, circular economy, regeneration paradigm, prognostic

For decades, the problems of resources availability and environmental impacts continue to grow. Actions are needed to remedy it. Several foundations propose to change the economy to move towards a circular economy. This economy considers that resources are in finite quantity and waste do not exist. It is inspired by nature and talks about regeneration paradigm. In our works, we study this concept to apply it to the industrial world. This study brings to light the necessity to add new stakeholders to the classic supply chain: the decomposers. They impose new requirements to the other stakeholders of a system. We propose to study the impact that their requirements may have on other stakeholders and to monitor them to maximize the regeneration. For this, we use the processes of maintenance (monitor, detection and prognostic). To sum up, this paper presents realized works and develop directions for future works.

1

Problem Statement

Context

The concept of sustainable development is a development that meets the needs of the present without compromising the ability of future generations to meet their own needs.

In other words, the sustainable development must meet the issues concerning climate change, increase of greenhouse gases and goods consumption, exhaustion of natural resources, accumulation of waste, etc. In this sense, several conferences and projects (UNCSD, Rio+20, COP2, Europe 2020 project) are organized to remedy these issues. One conclusion of these conferences is that the current economic model (take-makedump) is not sustainable. It must be changed. However, before this, studies must approach new economic models, new ways of producing and consuming, etc. That is why; the sustainable development issues also affect the world of research and are the subjects of much research.

Therefore, our works are in a context of sustainable development, especially in a paradigm shift. Indeed, they are based on the regeneration paradigm initiated by the circular economy. Moreover, our works focus on its inclusion in the industrial environment through maintenance.

State of art

1.2.1 Circular economy One of economy studied is the circular economy (make-use-return infinitely). This economy is an economy breaking with the current economy. It considers that the natural resources are in limited quantity and that the notion of waste does not exist [START_REF] Foundation | Report Version 1, 2 & 3 : Towards the Circular Economy[END_REF]. The main idea is to transform waste into resources by creating closed loops for reuse the manufacturing goods as long as possible. The circular economy can be also called "regeneration paradigm". Its principle is based on several schools of thought:

-Biomimicry [START_REF] Benyus | Biomimicry[END_REF] is the study of nature to design goods and to develop new technologies. For example, the eagle form has inspired the high-speed train; -Industrial Ecology [START_REF] Ayres | A Handbook of Industrial Ecology[END_REF] is the study of material and energy flows through the industrial system to add value to waste produced by a firm. A good example of this concept is the Kalundborg area; -Regenerative Design [START_REF] Cole | Regenerative design and development: current theory and practice[END_REF] is the study of the environment and communities of a place to design in harmony with them. The permaculture is an example. -Cradle-to-Cradle [START_REF] Mcdonough | Cradle to Cradle: Remaking the Way We Make Things[END_REF] is the popular term of regenerative design and uses the biomimicry approach to design a good. The authors consider the materials as nutrients (organic and technical). With this perspective, they want to highlight the fact that industry must operate as nature. These schools of through are oriented design and consider a perfect exchange of waste between different firms. Moreover, with all these concepts, the regeneration paradigm is difficult to set up. We can use some concepts move towards the regeneration.

1.2.2

Eco-design One of design fields that shows the idea of circular economy is the eco-design called also design for environment. This design is sustainable design. Actually, the main idea of eco-design is to reduce the environmental impacts from the design phase, i.e., to reduce the production of waste and the consumed resources and energies over the product lifecycle, and to use resources more healthy for the environment [START_REF] Knight | Adopting and applying eco-design techniques: a practitioners perspective[END_REF]. It is a multi-step and multi-criteria approach, which the stakeholders are raw materials suppliers, manufacturer, transporters, recycler and environment. In the literature, several tools and methods exist to apply the eco-design. The more used is the lifecycle assessment. It allows identifying and assessing environmental impacts of a product or process by considering every life phase. Furthermore, it is the subject of standard, and of many tools. Checklists and guidelines are also tools to apply ecodesign. Some of them focus on one lifecycle phase. It is the case for the "design for X" ("X" corresponds to studied phase). The most papers are interested in the end-of-life phase (remanufacturing, disassembly and recycling). Nevertheless, even if the retirement is studied, few papers consider it from design phase [START_REF] Balanca | Development of a design for end-of-life approach in a strongly guided design process[END_REF]. Even in the eco-design, the question of the retirement is often considered in end-of-life of the system. In the best case, the system is designed for one retirement process, principally recycling process. The possibility to multiply the number of retirement processes is not present. Another point, this design stops its thinking at these processes. It is not considering other life cycles.

1.2.3

Maintenance and sustainable development Maintenance turns also towards the sustainable development. Among the emerging concept, we can quote green maintenance [START_REF] Ajukumar | Evaluation of green maintenance initiatives in design and development of mechanical systems using an integrated approach[END_REF] and maintenance-centered circular manufacturing [START_REF] Takata | Maintenance-centered Circular Manufacturing[END_REF]. The first concept focuses on the elimination of waste produced and associated with maintenance. For this, it practices the pollution prevention, reduces the use of toxic products and is based on the ecodesign. Several approaches are proposed to evaluate the green maintenance efficiency. They use a multi-criteria decision-making and various sustainable requirements. The second concept is based on a circular manufacturing and assumes that manufacturing, reuse and maintenance can be integrated. Here, maintenance as the core of manufacturing. In other words, maintenance is the only process being related to the use. Other works focus on the use of maintenance tools to predict the time to remanufacturing a system. Indeed, to preserve the potential of a system and these parts, [START_REF] Song | Proactive remanufacturing timing determination method based on residual strength[END_REF] propose to make a proactive remanufacturing. They study the most critical component of a system to determine when to remanufacture the studied system. Similarly, [START_REF] Hu | Remanufacturing Decision Based on RUL Assessment[END_REF] propose a methodology to choice a remanufacturing process according to the system's RUL (Remaining Useful Life). These various papers show that maintenance is very important in the sustainable development.

Regeneration paradigm

The concept of circular economy talks about the regeneration concept, but it does not explain its origin. We want to understand what it means and how to apply it in the industrial world. This part is the subject of a conference paper [START_REF] Diez | Maintenance as a Cornerstone for the Application of Regeneration Paradigm in Systems Lifecycle[END_REF]. The biology literature defines "regeneration" as a process "to grow again". It uses to define the regeneration organic tissue (lizard's tail grow back), and trophic organization (food web). Only the second case interests us. Indeed, in this organization, the concept of waste does not exist; all is nutrient. Each entity (living being) feeds another entity (Fig. 1). Even organic matters produce by each entity is nutrient. Decomposers (fungi, worms, bacteria) eat them and transform them in new nutrients (mineral). Finally, the essential elements are decomposers. Without them, nature would be similar to the linear industrial organization. Therefore, we must add "industrial decomposers" in the industrial world to transform produced waste in resources and to become circular (Fig. 2). Thus, wastes become nutrients for other enterprises. These decomposers are new companies and new business. Moreover, contrary to nature, they can supply different industrial sectors, and increase the number of possibilities to regenerate waste. We can compare the industrial decomposers with existing retirement processes. Later our paper, the notion "product" can be replaced by the term "system, sub-system or component". [START_REF] Govindan | Reverse logistics and closedloop supply chain: A comprehensive review to explore the future[END_REF] have identified four technical decomposers:

-Repair process: it is a physical action taken to restore a required function of a faulty product. This process preserves the product functionalities; -Reuse process: it is defined as an exhaustion of the items lifetime. This process makes a transformation in space and preserves the product functionalities; -Remanufacturing process: this term is not clearly defined and includes many processes (disassembly, cleaning, control, etc.). This process makes a transformation of space and shape and does not preserve the product functionalities. Nevertheless, the functionalities of these sub-products must be preserved; -Recycling process: this process includes the material and energy recovery. The energy recovery does not allow the indefinitely regeneration of resources. Therefore, we focus on the material recovery. This process makes a transformation of space and shape and does not preserve any functionalities. To represent this total destruction of functionalities, we name it "destructuring process". In addition, we add the "detechnification process". This process is similar to destructuring process, but it is able to clean a product to make it healthy for nature (Fig. 3).

Fig. 3. Interactions between maintenance and decomposers in supply chain

However, we have identified another process essential for the regeneration: maintenance process. Indeed, this process includes repair decomposer, but it is also able to manage the regeneration. It knows everything about a product.

Research questions

To fulfil its manager role and support the regeneration, maintenance needs to know what and how to monitor. For this, we need to determine the regeneration requirements (decomposers and environment). In our work, we concentrate on those of decomposers. Indeed, in the literature, many papers focus on how to meet the environmental requirements, but few of those decomposers.

Eco-design provides some requirements to meet the sustainable development, which concerns all phases of the lifecycle. With these requirements, it is possible to design a product meeting those of regeneration. However, how to consider these new requirements and to accept to the enterprises? What is happening to the other phases? How to determine if a user meets these requirements? Moreover, all products are not eco-designed. Indeed, if a user want to regenerate its products, how to take account of these new requirements? What impacts will they on existing requirements?

Once the requirements and their impacts identified, we can monitor them. However, each decomposer is different and have not the same needs. We must find a way to visualize each decomposer requirement in function of the product state. Moreover, to ensure maximum possibilities of regeneration, it could be interesting to predict the time when a product will not be regenerable by a decomposer. To go further in the regeneration, we might consider the future product lives to choice a decomposer. For this, we can use the prognostic used by maintenance. It will allow determining when to stop the use of a product and which decomposer to use.

Work plan

From an industrial point of view, there are two ways to make the regeneration. The first is to have direct exchanges between enterprises (user and future user). The user (enterprise that uses the product and wants to regenerate it) regenerates its products for sale to the future user (enterprise that uses a regenerated product). The second is to have intermediary firms, the decomposers. Thus, the user sells its used products to decomposers that regenerate and sell them to the future user. In the first case, the user plays the role of decomposers, so he knows its own requirements to regenerate its products.

In the second case, the user must know the decomposers needs to ensure proper regeneration of its products. In our work, we study the second case.

Identification and impacts of regeneration requirements

To improve the regeneration possibilities, the user must consider the decomposers requirements. Each decomposer has requirements to regenerate a product. Some are identical to a different satisfaction level and others are specific to a decomposer. The user knows these req. and must meet them. For this, he must identify which of his requirements are affected by those of decomposers. Indeed, each stakeholder has a requirements repository. It is established for each product and is divided into several categories (functional, interface, performances, operational and constraints). This repository may depend on the stakeholder and the phase in which the product is. For example, in the design phase, the user wants a product that does what he requests it, it adapts to its operating environment, etc. The user focuses on all requirements categories. While, in the use phase, he wants to be profitable, and focuses on performances (principally productivity), functional and operational requirements. Firstly, to determine the decomposers requirements, we use guidelines and methods developed in the eco-design literature. Some are usable only by design phase. However, we can base us on them and adapt them on the use phase. For example, the design requirement "the product must be disassembly" could become "the product must stay disassembly" for the user. The addition of "stay" term obliges the user to supervise each interface of the product. Moreover, if the decomposers want to make profits and to sell their production, they must find a purchaser. To find a purchaser, they must meet his requirements. These requirements affect those of decomposer and indirectly, those of user, which increases the difficulty in meeting the regeneration requirements.

Secondly, we will propose a method to identify the affected requirements by those of decomposers. For each of his requirements, the user must consider whether it is affected by any decomposer requirement. If this is the case, the user can link the two requirements. For this, he could use a matrix, and check the box at the intersection of both.

Then, for each checked intersection he must consider how each of his requirement is affected and what consequences this may have. In function of this, the user can improve his repository; implement new actions plan, etc. The same method can be used with the environment requirements and can be applied on all lifecycle.

In the same time, we will study the repository evolution in function of the decomposer. Indeed, the decomposer requirements are not always the same or change at the time.

For example, for the repair decomposer, the functionality of the product must be conserved, but for the destructuring decomposer is not necessary. The current user needs a certain productivity level, while another user needs a lower level than the first. With these first observations, we suppose that the regeneration requirements can be deleted, transformed, degraded or conserved intact. We want to model these evolutions. Before this, we need to determine which tool is the most adapted for our problem.

With this model, we will be able to identify the critical requirements for the regeneration, which must be monitored to maximize the regeneration possibilities.

Monitoring and evaluation

With these critical requirements, the regeneration failures appear. The regeneration failures are defined as "the fact that an item cannot meet decomposer requirements, and consequently, removes regeneration possibilities". In other words, a product must always be regenerable by the destructuring decomposer. To avoid these failures, we propose to use the maintenance capacities, and more particularly, the processes used by the PHM community. Only maintenance is able to provide information on the state of a product. It can know the evolution in real time of each critical item. One of maintenance capacities that interests us is the prognostic. It is defines as a process that "analyses the products of faults to predict future condition and residual life within design parameters". In the regeneration paradigm, it can also be used to predict when an item must be stopped to no exceed the regeneration threshold. In addition, we want to maximize the number of lifecycles. For this, we will use also prognostic capacities. Indeed, prognostic can help decision-making to select a decomposer in function of product state and regeneration requirements but also in function of the future regenerations.

In first, we propose to visualize the evolution of these requirements over time by using a radar chart. Indeed, this representation is the most adapted to visualize different data on the same chart. This chart could be created for each item of a product or a subproduct, which are identified as critical in the regeneration perspective. These items will be principally the structures. Undeniably they are the more expensive to make in economy or ecology perspective, but they are also the most resistant. However, the others items should not be neglected. Particularly for the items that are not or hardly destructurable, and must be landfilled. The radar chart must represent different data: data on the user requirements, in other words, the minimum use thresholds to no exceed, data on the decomposers (one line by decomposer), and data on the current state of the system, sub-system or component. The decomposers line can be represented on different charts but on each chart will have to appear user and current state data (Fig. 4). The environmental data can be also added to the chart as the requirements, or create a chart, especially for the environment. This chart will allow to pilot the product exploitation and to provide a decision-making. In second, to maximize the regeneration, we propose to use the prognostic capacity to evaluate a scenario proposed by decision-making process. Here, the challenge is to have a product that remains efficient, productive and economically viable in each lifecycle while respecting the regeneration requirements. Indeed, initially, we can suppose that the repair process is best to able to maximize the number of the lifecycles. Nevertheless, it is possible that this decomposer and the product use (with always the same cadences) degrade quickly its different items. In this case, by choosing the disassembly decomposer after two repairs could have been better. To make this, decision-making process must be able to produce various scenarios in function of product state and the respect of regeneration requirements.

The decomposers can also use this approach to orienting an item toward the best customer (after regeneration) in function of the level of requirement satisfaction.

Conclusion

The first part of these work are accepted in two conferences. The first, CSDM 2015, presents the work about the regeneration paradigm and the nutrient view in the industrial world. The second, AMEST 2016, presents the work of the contribution of maintenance in the regeneration paradigm and conversely. In the near future, we aim to publish them a journal (Journal of Cleaner Production, Production Planning & Control, or Journal of Quality in Maintenance Engineering).

To finalize our work, we could apply it to a concrete example, requalify every regenerate product and consider the requirement environment.

Fig. 1 .

 1 Fig. 1. Trophic organization Fig. 2. Circular industrial organization

Fig. 4 .

 4 Fig. 4. Radar charts for repair and disassembly requirements (req. = requirement)


Marcelo A Carignano

Y Saeed

S Assa Aravindh

I S Roqan

Jacky Even

Claudine Katan

Close examination of the structure and dynamics of HC(NH 2 ) 2 PbI 3 by MD simulations and group theory

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

I. INTRODUCTION

The realization a few years back of solar cells employing the unconventional hybrid organic inorganic perovskite (HOP) as the active material and displaying high conversion e ciency triggered a tremendous development e↵ort mainly aimed to achieve a commercially viable device [1][2][3][4][5][6][7][8][9] . In spite of the always important commercial application, the material responsible for this research presents many interesting properties that represent a challenge for the current state of the art in materials science from experimental [10][11][12][13][14][15][16] and theoretical [17][18][19][20][21][22][23] points of view. In both cases, the main thrust of the research activity has been around the methylammonioum (MA) lead iodide perovskite, but the interest has broadened to include other compounds not only by replacing and/or mixing the halides 24,25 but also exploring the effect of other organic cations 26,27 . In particular, a formamidinium (FA) lead iodine perovskite solar cell having a maximum conversion e ciency greater than 20 % has recently been achieved by Yang et al. 28 . Also, Saliba et al. 29 have demonstrated that a triple cation recipe (Cs, FA, MA) allows to improve the stability and reproducibility of the cell while reaching an e ciency of 21.1 %.

The complex physical chemistry of the hybrid perovskites, in particular for those compounds having a) Electronic mail: mcarignano@qf.org.qa b) Electronic mail: jacky.even@insa-rennes.fr c) Electronic mail: claudine.katan@unv-rennes1.fr CH 3 NH 3 as organic cation, was recognized long ago after a series of detailed experiments [30][31][32][33][34][35][36][37] . The picture emerged from these pioneering papers is that of a material evolving from a low temperature towards one or two phases in which the mobility of the organic cation gained rotational degrees of freedom. Moreover, the possibility of orientational disorder in the intermediate phases was also suggested. Recent experiments [38][39][40] and large scale molecular dynamics simulations 23,[41][42][43] are in line with those earlier works. Noteworthy, the system size and complexity of the interactions prohibit a full thermodynamic characterization using first principles methods and more e↵orts are needed in order to have an overall picture with atomistic detail.

The structure of HC(NH 2 ) 2 PbI 3 , also referred to as FAPI, was first studied by Stoumpos et al. 44 using single crystal X ray di↵raction. Two phases were identified. A black trigonal (P 3m1) phase, which is also referred to as quasi cubic, was found to be stable at temperature over 60 C and a yellow hexagonal phase that appeared as the stable phase at room temperature. Nevertheless, it was noted that the properties of these materials in general depend of the preparation method. Further refinements by Weller et al. 39 obtained from high resolution neutron di↵raction suggested that the so called black phase is indeed cubic (P m 3m) with a lattice parameter a = 6.3620 Å. Interestingly, the orientation of the formamidinium molecules is reported as formally disordered with 24 possible orientations. The inorganic lead iodide framework is characterized as soft, and iodine atoms display a strong anisotropic motion in the plane perpendicular to the Pb-I-Pb direction. By means of low temperature dielectric measurements, Fabini et al. 40 studied comparatively CH 3 NH 3 PbI 3 (MAPI) and FAPI and reported, for both systems, the characteristic signatures of a (rotational) glassy system: the broad peak in the frequency dependent dielectric loss shows a dramatic dynamic slowing down as the system approached the glass temperature.

Such a glassy behavior is consistent with our recent analysis of large scale first-principles molecular dynamics simulations on MAPI 43 . More generally, based on the experimental and theoretical understanding of hybrid perovskites we proposed that a natural and comprehensive perspective to theoretically analyze these systems is to place them at the intersection of three distinct classes of materials: First, and related to its intended application, HOP touch the realm of conventional semiconductors. Second, due to their underling atomic organization the HOP should be considered as an extension of fully inorganic perovskites, for which much of the current density functional theory methodology finds many successful applications. Finally, and because of the rotational degrees of freedom of the organic cation, the HOP are plastic crystals and exhibit many of their complex dynamical behavior. With this overall scenario in mind, this paper presents a first principles molecular dynamics study of HC(NH 2 ) 2 PbI 3 along with a group theory analysis. It is an important intermediary step before considering more complex composition such as the triple cation 29 or 2D/3D perovskite composition 45 that have demonstrated clear improvements with stabilized output power under operational conditions as compared to the prototype CH 3 NH 3 PbI 3 . 46

II. COMPUTATIONAL DETAILS

The molecular dynamics simulations were performed using periodic boundary conditions and under isothermal-isobaric conditions. All simulations were performed using the CP2K package [47][48][49] as in our previous works on similar systems. The time step for the integration of the dynamic equations was set to 1 fs. The temperature was controlled using the Nosé-Hoover thermostat 50,51 with three chains and a time constant of 50 fs. The volume fluctuations were controlled by imposing a fully anisotropic pressure coupling as implemented by the NPT-F option of CP2K, which follows the method of Martyna et al. 52 . The reference pressure was set at 1 atm and the barostat time constant at 50 fs.

The electronic density is represented in CP2K by a combination of Gaussian basis functions and plane waves in the GPW method. The PBE functional was used to calculate the electronic structure properties and the Grimme D3 correction scheme was included to account for the dispersion interactions 53,54 . DZVP-MOLOPT basis sets 55 were used to expand the Kohn-Sham orbitals, complemented by the auxiliary plane wave set that were defined by an energy cuto↵ of 300 Ry. Norm-conservative GTH pseudopotentials 56,57 were used to complete the inter atomic interactions. The main simulated system contains 64 cubic unit cells and the initial configuration were obtained by replicating the experimentally determined coordinates 39 to form a 444 supercell with an edge of 25.448 Å. Therefore, the initial state contains all the FA molecules oriented in exactly the same way. Four sets of simulations are presented in this paper. Based on the 444 system we performed an MD simulation at 300 K that extended to 50.7 ps and a second one at 450 K that was extended to reach 58.9 ps. The analysis of the two trajectories shows that for this supercell size and for the particular conditions implemented here, the system requires about 25 ps to relax and reach an equilibrium state where the cell parameters cease to drift in a systematic way. For that reason, all the analysis presented below relies on the second half of the simulated trajectories. A snapshot of the simulation box corresponding to t = 58.9 ps at 450 K is displayed in Figure 1. The structure shows that although the inorganic atoms do follow a regular pattern, the orientation of the FA molecules appears to be random.

In our previous work, based on simulations of the MAPI perovskite, we observed a strong odd-even effect in the results related to the relaxation of the MA molecules 43 . The origin of this persistent e↵ect was attributed to two possible causes, one related to the dipolar coupling of the MA molecules between neighboring cells, the second related to limitations imposed by the -point sampling of the simulations. The small dipole moment of the FA molecules o↵ers the possibility to discern which of these two e↵ects dominates the observed odd-even artifacts. Then, a 333 supercell (324 atoms) was also simulated at 300 K. For the smaller system 333, we performed a single simulation run at 300 K covering a total of 20 ps.

The smallest supercell alternative, the 222 system with only 96 atoms, was also simulated at 300 K in order to asses the magnitude of the fluctuations associated with its small size.

III. RESULTS

At room temperature, the experimental unit cell contains a single FA molecule in the cubic inorganic cage and therefore the replication process to create a 444 system results in a low entropy structure with all FA molecules having identical orientation. The start of the NPT simulations, which was performed by assigning random velocities consistent with the Maxwell distribution at 300 K, reflects the unphysical initial condition by undergoing a fast expansion accompanied by rotations of the organic molecules. This initial expansion, which can be observed in Figure S1, relaxes in about 10 ps to the equilibrium cell dimensions. This procedure of a sudden shake up of the system at the start of the simulation is the same that we used in our previous work for MAPI, and although it requires an extra equilibration time with respect to a slow heating protocol it has the benefit to automatically introduce a random orientational entropy of the organic components. The MD trajectory is continued up to 50.7 ps, and only the second half of the simulation is used for the collection of results. The equilibrium structure of the FAPI resulting from the simulations is cubic, with an average lattice parameter a = 6.39 Å. The fluctuations of the three independent cell edges follows nicely a normal distribution with a standard deviation 0.025 Å. Similarly, the distribution for the simulation cell angles is centered in 90 and have a standard deviation of 0.55 (detailed information is provided in the Supporting Information file).

A second simulation at 450 K was started by setting the initial coordinates and velocities to those of an equilibrated conformation from the simulation at 300 K (frame corresponding to t = 25 ps). In this case, the simulation cell expanded smoothly from its initial size until it reached larger equilibrium dimensions after 30 ps of simulation. The analysis of equilibrium properties on this system are based on the lapse going from 30 ps to 58.9 ps. The simulation cell fluctuates with a larger amplitude than for the case at the lower temperature, but the system remains cubic with an average lattice parameter a = 6.50 Å.

The analysis of the structure of the system, performed by calculating the radial pair distribution functions g(r), is shown in Figures 2 and3. The figures display the results for 300 K and 450 K, and in order to perform an adequate comparison, the radial distances are scaled by the corresponding cell parameter a. For the atoms defining the inorganic cage, the picture that emerges is that of a crystalline material with the Pb atoms having a neatly defined simple cubic structure and the I atoms displaying a larger degree of local mobility. In Figure 2-A g(r) for the Pb-Pb pairs is reproduced. It stands out the perfect cubic order of the succession of peaks at a, p 2a, p 3a, 2a and so on. Even though in this work the simulation conditions allows for the independent variation of all the cell edge dimensions and angles, the overall fluctuation of the systems are su ciently small to nicely reproduce the experimental cubic crystal structure with a small noise. Larger simulation cells, which will decrease the local fluctuations even more, are prohibitively expensive for our current resources. Figure 2-B displays the radial distribution function for the Pb-I pairs that show, first of all, peaks that are not symmetric. Indeed, the first peak at r = a/2 is slightly skewed towards larger values of r. The origin of the e↵ect lies in the anharmonic character of the equilibrium position of the I atoms that can explore the region normal the the Pb-Pb connecting lines at a much lower energetic cost than along those lines, see snapshot in Figure 1. This e↵ect is reflected as a nearly double second peak for the 300 K case, but as a single wide peak for 450 K. The di↵erence between the two temperatures has to be related to the characteristic times for the slow fluctuations of the I atoms across the Pb-Pb connecting lines that decreases significantly as the temperature is increased (see average structures, Figure 4). Finally, in Figure 2-C we show the g(r) corresponding to the I-I pairs, which display almost a liquid character beyond the second peak. The reason for this is the above mentioned higher mobility of these atoms in addition to the fact that they are more numerous, it result in a succession of overlapping peaks showing a fast approach to the asymptotic limit. For reference, Figure S5 gives the g(r) for the inorganic atoms pairs obtained for the smaller 222 supercell size.

The pair distribution functions of the pairs involving N and C having Pb and/or I as the reference atom are useful to display the average location of the FA molecules inside the cubic inorganic cages. These results are shown in Figure 3. As expected by the geometry of the overall system and the FA molecule, the C atoms occupy the central region of the cages. Nevertheless, for the 300 K case, the C atom is in average slightly o↵ the geometric center of the cage as revealed by the maximum of the Pb-C pair distribution function. By increasing the temperature to 450 K the C atom distributes almost evenly around the geometrical center. Considering the I atoms as the reference point, then the I-C pair distribution functions display a double peak at 300 K, which is related to the displacements of the I atoms from their ideal positions (see Figure 4). The N atoms are o↵-centered in the cage at both temperatures. For 300 K, the first peak is located at r c 0.62 Å and r c 0.73 Å for the Pb and I cases, respectively, with r c being the ideal geometrical center of the inorganic box represented by the vertical dashed lines in the figures. Considering that the CN bond is of 1.3 Å, the average radial distribution functions do not o↵er a clear picture of the preferred orientation of the molecule inside the inorganic cage.

The average structure of the inorganic frame of FAPI, calculated over the whole production part of the simulated trajectory, is displayed on Figure 4. At 300 K the Pb-I-Pb lines are not straight, but follow a zig-zag pattern that define elongated cavities to host the FA molecules. By increasing the temperature to 450 K the mobility of the I atoms increases substantially and the corresponding average structure displays only a minor departure from the perfect cubic structure with all cavities having essentially the same regular shape. This regularity in the structure is also reflected in the pair distribution functions displayed above in Figure 2 for the Pb-I case, which shows the disappearance of the bimodal second peak at 450 K. Noteworthy, the projections of the average structure displayed in Figure 4 correspond to the plane normal to direction a, but the projections on the other two planes display essentially the same pattern. The question that arises is whether there is a coupling between the lattice distortions and the orientation of the molecules. A simple qualitative answer can be obtained by averaging the coordinates corresponding to the molecule's atoms over the whole production run, as done for the inorganic frame. The results indicate a strong coupling at 300 K that vanishes at 450 K, as is explained in the Supporting Information file.

In order to quantify the tilting of the PbI 6 octahedra we calculate the angles (✓, ) defined by the octahedral axes with respect to the fixed reference coordinate system of the simulations. The polar angle ✓ is measured with respect to the positive direction of z axis, and the azimuthal angle is measured on the xy-plane from the positive direction of the x axis. Each one of the three axes define an orientation, that we denote by the indexes 1, 2 and 3. The orientation 1 is nearly parallel to the x axis, orientation 2 is close to the y axis and orientation 3 follows the z axis. Then, the three pairs of angles calculated along the MD trajectories represent deviations from the ideal positions of the cubic phase that are ✓ 1 = ⇡/2, 1 = 0; ✓ 2 = ⇡/2, 2 = ⇡/2 and ✓ 3 = 0, 8 3 . In Figure 5-A we present a schematic representation of a tilted octahedron and the three characteristic direc- tions. The distributions for the three pairs of angles is shown in Figure 6 for 300 K and 450 K as a color map. The color scale represents the residence time for a particular orientation and is proportional to the probability density of finding any given molecule in a particular orientation. At the lower temperature, the tilting of the octahedra define distinctive angles as follow: for the orientation 1, the four spots are centered at hcos ✓i = ±0.12, h i = ±0.11. For orientation 2, the average centers are hcos ✓i = ±0.12, h i = ⇡ ±0.12. Finally for orientation 3, the average centers are hcos ✓i = 0.98, h i = ±0.90 and ±2. 26. By increasing the temperature to 450 K the four spots coalesce into a single one centered around the ideal orientation of the perfect cubic crystal with no tilting, as represented in the right panels of Figure 6.

x y z A) ✓ 3 , 3 ✓ 2 , 2 ✓ 1 , 1 B) C N 1
The orientation of the FA molecules in their cages can be discerned by monitoring characteristic directions in terms of the three heavy atoms of the molecules. First, we consider the vectors defined by the molecular bonds, r1 = (r N1 rC ) and r2 = (r N2 rC ). Second, we look at the vector defined by the sum of the two CN bonds: r+ = r1 + r2 . Finally, using the direction defined by the line joining the two N atoms of the molecule we define r = r1 r2 . A schematic representation of these directions is presented in Figure 5-B. In order to characterize the directions of r1 , r2 , r+ and r , we compute the polar angle ✓ and the azimuthal angle for each one of them. In this way we can represent the distribution of orientations using a color scale in the plane (cos ✓, ). It is important to note that the two N atoms are indiscernible and therefore the di↵erence vector has arbitrary direction. Namely, it is equally correct to choose the direction pointing from one N to the other, or vice-versa. In order to have a systematic approach we always chose the direction that corresponds to a positive value for cos ✓. We display on Figure 7 the distributions for r+ and r obtained from the simulated trajectories at 300 K and 450 K. At both temperature the orientation of sum vector is parallel to the edges of the simulation cell, and isotropically distributed towards each of the six directions. However, the color maps show a very strong contrast in the lower temperature case, indicating a very high probability for the molecules to have their r + vector oriented according to (100) directions. The intensity of the distribution drops to essentially zero between the bright spots, suggesting that the molecules are quite static or undergoing sudden reorientations between the most probable directions. Vectors r+ and r point approximately towards the center of the cube faces. At 450 K the same pattern can be distinguished, but all directions in the plane are well populated implying a more uniform rotational dynamics than in the low temperature case. The corresponding distributions for the di↵erence vector r display essentially the same pattern, but in this case only half of the space is represented because of the arbitrarity in the labeling of N 1 and N 2 .

Besides, the orientational distributions in a cubic lattice can be interpreted in terms of cubic harmonics 58,59 .

FIG. 6. Orientational maps describing the tilting of the PbI6 octahedrons. The left column corresponds to the simulation at 300 K, and right column is for 450 K. From top to bottom, the rows describe the orientations case 1, 2 and 3, respectively, as explained in the text. FIG. 7. Distribution for the orientations of the vectors bond sum (r+) and di↵erence (r ) vectors. At 300 K (top panels) the high contrast figure reflects the persistent directionality of the molecules that are oriented in such a ways that the two perpendicular vectors are in (100) directions. At 450 K (bottom panels), the overall pattern persists, although with a very small contrast arising from a more uniform rotational pattern of the molecules.

For a characteristic direction u within a system with an underlying cubic symmetry the probability distribution f (u) can be expressed as

f (u) = 1 4⇡ " 1 + n X i=4 c i K i (u) # (1)
where c i are the coe cients associated with each cubic harmonic K i . The number of terms required to describe is small for smooth distributions, but increases for sharper distributions like the one we observed for 300 K.

In Figure 8 we reproduced the results obtained by fitting the orientational map corresponding to r+ using the expansion in cubic harmonics up to the n = 12 (see Supporting Information for details). The coe cients of the expansions are reproduced in the Supporting Information file. A three dimensional representation of the fits is also included in Figure 8. For 300 K the directionality of the orientational pattern is much stronger that for 450 K. Also, it evident from the comparison with Figure 7 that there is a certain degree of departure from a perfect cubic symmetry at 300 K, which cannot be capture by the fit based on cubic harmonics. This is evident by looking at the bright spots corresponding to = 0, ⇡ and ⇡, which are horizontally elongated. (A corresponding vertical elongation is present for = ⇡/2, ⇡/2, although it FIG. 8. Distribution for the orientations of the vectors bond sum (r+) obtained by fitting the data from the simulation trajectories at 300 K and 450 K using a 12 th order expansion on cubic harmonics, see Eq. ( 1). The figures on the right are 3D representations of the orientational probability and reveal the higher contrast at 300 K.

is not appreciable due to the chosen plotting range) The origin of this deformation is related to the tilting of the PbI 6 octahedron, which does not randomize within the simulated time scale. For the higher temperature case, the tilting average to zero and this e↵ect disappears in the corresponding color maps.

On Figure 9 we present the bonds orientational maps obtained from the two simulated trajectories. Namely, the orientation defined by the direction of the CN bonds, represented by the vectors r1 and r2 defined above in Figure 5-B. For the case corresponding to 300 K, the slow rotational dynamics translates to 12 very well defined spots. As the temperature is increased to 450 K, the pattern is completely lost and no clear directions can be recognized as the most likely ones.

The characterization of the rotational dynamics of the FA molecules can be done by studying the time dependent self correlation functions of the type c(t) = hr(0).r(t)i, where r is any of the above described vectors. In Figure 10 we show the relaxation curves corresponding to r+ and r that define the corresponding self correlation curves c + (t) and c (t). First of all, it is clear that the rotation of the molecules is not isotropic at any of the two temperatures since c + (t) relaxes faster than c (t). Since these two vectors are nearly orthogonal, then one vector can be considered as the rotational axis for the other one and vice-versa. The results imply that for 300 K the rotations are almost exclusively about the r direction. At 450 K, the mobility increases in such a way that both directions of rotation are clearly visible at the timescale of our simulations. The results at 450 K can be fitted very well with a simple exponential function, yielding relaxation times of 0.5 ps and 1.2 ps for c + (t) and c (t), respectively. The case for 300 K is di↵erent, and a stretched exponential fits c + (t) with a stretching parameter = 0.77, resulting in a relaxation time of 4.3 ps. For c (t) at 300 K, the strong correlation does not permit to calculate any accurate relaxation time. The behavior at 300 K captured by a stretched exponential resembles the results for the MAPI in the cubic phase. In that case, the relaxation of the individual molecules reveals a heterogeneous dynamics. Similarly, in the case of the FAPI we observe that in the timescale of the simulations there are molecules having very little or no rotations, while other undergo a relatively fast rotation (see Figure S7).

On the origin of the odd-even e↵ect

In our previous work related to the MAPI system, we observed that the results alternate in behavior depending on the number of unit cells contained in the simulation supercell. This e↵ect was observed to appear in the relaxation of the MA molecules time dependent self correlation function, in the heterogenous character of the rotational degrees of freedom of the MA molecules, and in the average structure of the inorganic cage. Two possible explanations for this odd-even e↵ect were proposed: (i) the dipolar coupling of the MA molecules between neighboring cells, or (ii) the impossibility of the MD oddsupercell to properly represent e↵ects that are related to Brillouin zone (BZ) folding as the used MD technique relies only in -point sampling. In the case of the FA the dipole moment is very small and therefore provides an adequate example to discriminate on the importance of the two possible origins of the odd-even e↵ect.

In order to further explore this e↵ect we studied a 333 system composed by 27 FA molecules resulting for the triple replication of the cubic unit cell along the three Cartesian directions. The simulation settings were the same as in the simulations of the 444 systems presented above and the temperature was set to 300 K. In Figure 11 we present the results that show that the FAPI system with odd number of cells behaves similarly to equivalent MAPI systems. Namely, the 333 system has a faster homogeneous dynamics than the 444 system simulated at the same conditions. The average inorganic cage reflects the faster fluctuations by producing a nearly perfect cubic structure, contrary to the corresponding averages performed using the supercell with even number of cells. Due to the small magnitude of the dipole moment of the FA molecules, we conclude that the odd-even e↵ect is related to the inadequate description of of the electronic wave-function at the edge of the BZ resulting from the -point sampling 43,60 .

IV. DISCUSSION

The structural instabilities in conventional perovskites can be usually inspected on the basis of Landau theory using the theory of group symmetry. A low temperature phase may appear after the condensation of a phonon mode of the P m3m parent phase at a critical transition temperature. Some of these classical structural instabilities have been characterized in halide perovskites leading FIG. 11. Time dependent self correlation function for r+ (black lines) and r (red lines) at 300 K for a 333 system. In the insert, average structure of the inorganic atoms that show a nearly perfect cubic arrangement to tetragonal centered I4/mcm (MAPbI 3 ), orthorhombic P nma (MAPbI 3 ) or tetragonal P 4/mbm (CsPbCl 3 ) (Figure 12). Using Landau theory, it is straightforward to predict that these various instabilities are related either to phonons with R + 4 or M + 3 symmetries, or simultaneous condensations of R + 4 /M + 3 phonon modes for the P nma case. The symmetries of the collective atomic displacements of metal and halide atoms, as well as molecular centers of mass, can be predicted from group theory as well (Table 1). R + 4 or M + 3 irreducible representations (IR) only appear in the decomposition of halide atoms motions. M + 3 and R + 4 optical phonon modes are indeed associated respectively to in-phase and anti-phase rota-FIG. 12. Schematic diagram indicating the group-subgroup relationship between some of the space groups observed in HOP and AIP (solid red lines). The tilt systems are given using Glazer's notation, as well as the P m3m IR related to the lattice instabilities. M + 3 and R + 4 order parameters are related to pure in-phase and anti-phase PbI6 octahedra tilts, respectively. The dashed red line indicates that a transition from I4/mcm to P nma space groups must be a first order phase transition. tions of MX 6 octahedra. From molecular dynamics simulation of FAPI (Figure 4), we deduce that the structural instability is associated to the simultaneous and progressive (Figure 9) condensations of three M + 3 pure in-phase modes. It corresponds to an Im3 averaged structure (Figure 12), related to an eight-fold increase of the cubic cell size.

We have shown in our previous theoretical study of MAPI that stochastic molecular reorientations can be also analyzed using a symmetry analysis of the molecular orientational probability. It is possible either to choose simplified pseudospin (PS) descriptions of the discrete molecular orientations or continuous rotator functions. The symmetries of the collective molecular orientational distributions can be derived at various points of the Brillouin zone by analogy to the phonon modes. The condensation of a PS mode at a structural phase transition is indicative of an order-disorder character by contrast to a displacive character for phonon modes. A vectorial PS was defined in our previous study of MAPbX 3 by considering the C-N molecular axis, thus focusing on the tumbling modes of the MA + cation. PS scenario A for MAPbX 3 compounds was defined as the case where the C-N axes are pointing toward the faces of the cubic cell (Table 1). As mentioned in the section devoted to MD results, a discrete PS description of the stochastic rotation of the FA + cation in FAPbX3 compounds requires to account for its specific shape and planar geometry (Figure 5-B). In scenario A, where the C atoms are pointing toward the faces of the cubic cell, two sub- -

R + 1 + R + 3 + R + 4 + R + 5 M + 1 + M + 2 + M + 3 + M + 4 + M + 5 I atoms (3d) 2 4 + 5 - M 3 + M 5 PS: + 1 + + 3 R + 5 M + 3 + 2M + 4 MA cation (A, 1b) 4 R 2 + R 3 M 2 + M 5 PS: + 1 + + 2 + 2 + 3 R + 4 + R + 5 3M + 3 + 3M + 4 FA cation (A1, 1b) 2 4 + 5 R 1 + R 2 + 2R 3 M 1 + M 2 + 2M 5 PS: + 1 + + 3 + 5+ R + 1 + R + 3 + R + 5 M + 1 + M + 3 + 2M + 4 + M + 5 FA cation (A2, 1b) 2 + 3 + 4 R 2 + R 3 + R 4 M 2 + 2M 3 + M 4 + M 5
scenarios A1 and A2 may be considered (Figure 13). For PS A1 and A2, the (C, N1, N2) plane corresponds respectively to the h and d symmetry planes of the Oh point group. The symmetries of the collective PS modes A1 and A2 can be predicted from group theory (Table 1). From the orientational maps of FA cations (Figure 7), it appears that PS scenario A1 is most likely to describe the stochastic reorientations. As shown on Table 1, the M + 3 irreducible representation (IR) appears in the decomposition of PS A1. We can thus conclude from this analysis, that the mechanism of the structural instability in FAPI is associated to a linear coupling between collective (deterministic) rotations of PbI 6 octahedra and collective (stochastic) reorientations of the FA + cations. A mixed displacive/order-disorder character is expected for the structural instability. More, we may infer that these low-frequency rotational modes of the PbI 6 octahedra undergo a large broadening related to this coupling mechanism.

V. CONCLUSIONS

In the quest to achieve a theoretical understanding of hybrid organic perovskites that recommenced with the application of these materials for energy harvesting applications, molecular dynamics has been moderately employed. The reasons are several. First, the science involved in the solar cells development is essentially of a quantum nature, and therefore an adequate description calls for a computationally expensive density functional theory approach. Second, the system has a molecular component with rotational degrees of freedom that, while making the system more interesting imposes the need for long simulation times. Third, an intrinsic anisotropy in the dynamic of the halide component further complicates the matter calling also for long simulation times. In spite of this issues requiring very large computational e↵orts, the first principles simulation community performed initial studies with relatively small systems. Increasing the size of the supercell, at least within the approach that we have been employing, revealed an odd-even e↵ect that actually prompted us to work with even larger systems in order to overcome artificial results and at the same time su ciently reduce the fluctuation associated with small simulation supercells. Our results, using a model system with a four fold replication of the unit cell in each direction, show a very organized inorganic framework in which the organic cation is located.

The formamidinium rotational dynamics exhibit a heterogeneous behavior at room temperature, similarly to the behavior previously observed for the methylammonium cation. The rotation of the formamidinium is anisotropic, having a preferential axis of rotation along the line connecting the two nitrogen atoms. At room temperature, the rotation is almost exclusively along the NN line. Increasing the temperature results in the activation of other rotational modes, like the axis defined by the sum of the two CN bonds. We have analyzed the dynamic of the cation in terms of rotator functions, in particular by fitting the rotational pattern in terms of cubic harmonics considering up to the 12 th order term. At room temperature, the orientation of the sum vector is essentially (100) and all the directions are equally populated indicating a rotational entropy characteristic of plastic crystals that, together with the heterogeneous dynamics, suggest that the system should form a rotational glass at lower temperatures.

Based on Landau and group theories, we further identify a mixed displacive/order-disorder character for the Pre-print of Phys. Chem. Chem. Phys., 2016,18, 27109-27118 DOI: 10.1039/C6CP02917E structural instability, which may lead at low temperature to an Im3 phase. This structural instability in FAPI is predicted to be associated to the simultaneous and progressive condensation of three M + 3 modes involving deterministic rotations of PbI 6 octahedra and stochastic reorientations of the FA + cations.

FIG. 1 .

 1 FIG. 1. Snapshot of the system corresponding to 450 K after 58.9 ps of simulation. The thin yellow lines are drawn between bonded Pb and I atoms. The I atoms are in general displaced from their ideal position along the Pb-Pb connecting lines. The rotational degrees of freedom of the FA molecules are clearly visible and the nearly perfect cubic supercell is shown in fine black lines.

FIG. 2 .

 2 FIG.2. Radial distribution functions for the atoms forming the inorganic cage. Panels A, B and C correspond to Pb-Pb, Pb-I and I-I, as indicated. The radial coordinate r is normalized by the average lattice parameter obtained for each temperature. The black curves correspond to 300 K and the red curves to 450 K, respectively. The green vertical lines are located at the ideal position of the peaks for the di↵erent cases.

FIG. 3 .

 3 FIG. 3. Radial distribution functions for the pairs Pb-N (black lines), Pb-C (blue lines), I-N (red lines) and I-C (green lines). Panels A) and B) correspond to 300 K. Panels C) and D) correspond to 450 K. The vertical dashed lines indicate the ideal center of the inorganic cage.

FIG. 4 .

 4 FIG. 4. Structure obtained by averaging the position of the Pb and I atoms over the production section of the trajectory at 300 K (left) and 450 K (right). The deformations are in line with the known anharmonic response of the I atoms which have a relatively long characteristic time (⇠ 10 ps). The higher temperature simulation average out the anharmonicity resulting in a cubic structure.

FIG. 5

 5 FIG. 5. A) Scheme of the tilting of the PbI6 octahedron defining the three characteristic set of angles. The directions (✓1, 1), (✓2, 2) and (✓3, 3) represent departures from the ideal orientations along the x, y and z Cartesian axes, respectively. B) Scheme of the FA molecule and the characteristic vectors r1 , r2, r+ and r used to describe the molecular orientations.

FIG. 9 .

 9 FIG. 9. Distribution of the orientation of the two bonds of the FA molecules, r1 and r2, calculated from the simulations at 300 K (top panel) and 450 K (bottom panel).

FIG. 10 .

 10 FIG.10. Time dependent self correlation function for r+ (black lines) and r (red lines) at 300 K (solid lines) and 450 K (dashed lines).

FIG. 13

 13 FIG. 13. (a) Schematic diagram showing one of the 12 positions for the PS A1 and PS A2. The molecule is represented schematically with the C, N1 and N2 atoms discarding the H atoms. In both cases, the C atom is pointing toward a face. For PS A1 and A2, the (C, N1, N2) plan corresponds respectively to the h and d symmetry planes of the Oh point group. (b) Symmetry operations of the Oh point group.

TABLE I .

 I IR decompositions for the strain tensor, phonons and MA or FA pseudospins excitations (PS) in HOP compounds at the , R and M points of the P m3m BZ. The contributions from each site (1a, 1b, 3d) are indicated. The symmetric (+) and antisymmetric (-) PS IR correspond to elastic and electric multipoles, respectively.

			R	M
	Volumetric strain Tetragonal strain Shear strain	+ 1 + 3 + 5	---	---
	Optical Phonons:	-	-	-
	Pb atom (1a) Optical Phonons:	4 -	R 4 R + 5	M 3 + M 5 -
	FA/MA cations (1b)	4	-	M 2 + M 5
	Optical Phonons:

VI. ACKNOWLEDGEMENTS

For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia. Y. Saeed acknowledges the support of the Qatar National Research Fund under the PDRA-1-0119-14119 postdoctoral grant. M. A. Carignano held an invited position at University of Rennes 1, which is gratefully acknowledged. The work was supported by University of Rennes 1 within Action Incitative, Défis Scientifiques Emergents 2015. J. E.'s work is supported by the Fondation d'entreprises Banque Populaire de l'Ouest under Grant PEROPHOT 2015.


Thierry Bontems
email: thierry.bontems@umrpacte.fr

Sabine Goulin
email: sabine.goulin@univ-lorraine.fr

Caroline Censier-Calmus

Françoise Taillebot

Caroline Calmus
email: caroline.calmus@univ-reims.fr

une réponse aux problématiques de gestion de la qualité des projets pour des équipes géographiquement dispersées

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Le Cloud Computing, une réponse aux problématiques de gestion de la qualité des projets pour des équipes géographiquement dispersées

Cas issus du pilotage de projet pour des équipes administratives et recherches géographiquement éloignés Thierry BONTEMS -Sabine GOULIN -Caroline CALMUS Auteur Principal (assurera la présentation) : -Thierry BONTEMS -CNRS Grenoble -Université Grenoble Alpes et Réseau RELIER Co-auteurs : -Sabine GOULIN -Université de LORRAINE et réseau RELIER -Caroline Calmus -Université de REIMS et réseau RELIER -traduction en Anglais par Françoise TAILLEBOT, université Paris 1 Panthéon Sorbonne et réseau RELIER

Abstract

Mettre à disposition de la donnée, travailler ensemble cette donnée pour en faire de l'information relève d'un exercice complexe en terme de partage d'information entre les membres d'une équipe, qui plus est lorsque les membres de l'équipe sont situés dans des espaces géographiques distant. Garantir la qualité de ces mêmes données relève alors d'une gageure. L'objet de cet article est de démontrer, en partant de retour d'expérience issus du pilotage de projet de recherche et du pilotage de réseau de cadre de pilotage comment l'utilisation de technologies innovantes en terme d'infrastructure informatique permet de garantir les concepts fondamentaux de la qualité.

To put at data layout, to work together this data to make information of it concerns a complex exercise in term of division of information between the members of a team, which more is when the members of the team are located in geographical spaces distant. To guarantee the quality of these same data concerns a challenge then. The object of this article of is shown on the basis of experience feedback resulting from the piloting of research project and the piloting of network of manager how the use of technology innovating in term of computer infrastructure makes it possible to guarantee the fundamental concepts of quality -

---------------------*---------------------

Les avantages.

Depuis plusieurs années, nous utilisons ces Espace Collaboratif de Travail afin de garantir la qualité de certains projets de recherche ou la coordination de réseaux de personnes. Les outils collaboratifs en Cloud permettent d'étendre ces services à la protection intellectuelle des données du participant au projet. L'objectif de la démarche est de garantir la qualité des projets en répondant à plusieurs objectifs :

• Culture commune, valeurs et transparence : travailler ensemble sur un même document, partager le même niveau d'information et co construire de manière itérative les briques d'un projet constitue un véritable levier pour développer une culture commune. La culture qualité prend directement appui sur ce type de dispositif qui sert de levier pour l'ensemble d'une démarche de management de la qualité. En matière de transparence, l'accès a ces espaces peut être ouvert complètement ou en partie au parties prenantes du programme ou les donneurs d'ordres, ce qui leurs permet de suivre l'avancée des travaux de l'équipe projet qu'il finance.

• La propriété intellectuelle par l'horodatation des documents : lorsqu'un document est créé ou importé sur le serveur, il est automatiquement horodaté (date de dépôt, heure de dépôt, propriétaire). Cette horodatation est garantie par un « tiers de confiance » (le fournisseur du service de cloud) qui fait foi en cas de procédure judiciaire. Toutes les modifications faites sur un document sont également enregistrées et l'utilisateur peut consulter les modifications et le cas échéants restaurer versions antérieures. Ce concept va également dans le sens d'une certaine garantie de traçabilité des documents, nous y reviendrons plus loin.

• Unicité, partage et stockage de l'information : L'information du projet est stockée sur le « cloud ». Toute personne membre du projet a accès en ligne à l'information à jour (agenda, compte-rendu de réunion, documents institutionnels, corpus de données, objet en cours d'écriture…). Les documents du projet, définitifs ou en cours d'élaboration, sont à disposition sur l'espace de travail partagé, sur les listes de diffusions, les bases de documentations, les forums de discussions de l'espace collaboratif réservés aux équipes du projet.

• Traçabilité du projet : toutes les informations d'un groupe-projet sont stockées sur le même espace. Chaque personne autorisée peut accéder ainsi au déroulement du projet et peut le « retracer ». De plus un des gros avantages de ces outils de management de contenus (contents management system -CMS) est de gérer les différentes versions d'un document. Pour tous les documents modifiés, on peut donc avoir accès aux différentes versions du document depuis son dépôt, aux modifications réalisées, ainsi qu'à l'auteur et aux dates des modifications.

• Sécurisation de l'information : En matière de sécurité de l'information, nous connaissons tous les risques liés à un vol de portable, à une casse matérielle. Combien d'années de recherche ont été perdues à cause d'un accident ou d'une panne ? Avec l'avancée des technologies, les vols d'informations sont de plus en plus fréquents, notamment lors des déplacements à l'étranger. Les serveurs de nos partenaires sont accessibles à partir du monde entier. Certains collègues travaillant dans des pays sensibles sur des données également sensibles stockent la totalité de leurs travaux sur ces serveurs, et n'ont sur leur portable que les outils d'exploitations et le minimum de données de travail.

• Chiffrement des communications et des transferts de données : toujours afin de garantir un maximum de sécurité et de confidentialité dans les transferts de données, tous les accès à l'entrepôt de donnée ainsi qu'à l'espace collaboratif sont cryptés grâce à l'utilisation d'un protocole SSL 128Bit. La connexion est cryptée au moyen de RC4_128 avec SHA1 pour l'authentification des messages et RSA pour la méthode d'échange des clés.

• Simplicité d'utilisation : l'outil est très simple à utiliser, il faut environ trois à quatre heures pour concevoir un espace projet et deux heures pour former les membres de l'équipe qui seront administrateurs du site. Aucune formation n'est nécessaire à l'utilisation des espaces ; l'outil est intuitif, les systèmes d'alertes mails pour prévenir les membres du projet ainsi que l'interaction avec les autres logiciels bureautiques en font un outil pratique et convivial. De plus l'administration de chaque site est géré sur l'équipe projet.

L'ensemble de ce dispositif est utilisé pour le management de la qualité des projets de recherche au sein d'établissements d'enseignement supérieur et pour les projets nationaux et internationaux (UMR PACTE Grenoble, IEP...),ainsi que la gestion de plusieurs évènements scientifiques (congrès colloques...). il permet de sécuriser l'ensemble du processus et de développer une approche qualité partagée. La dimension qualité induite par le dispositif favorise la valorisation des travaux produits et l'implication des enseignants chercheurs et partenaires qui trouvent ainsi une reconnaissance et une sécurisation du travail produit.

2 -Utilisation d'un système de gestion de donnée de type datawarehouse.

Une des particularités ces outils est de savoir gérer de front un nombre de données non structurées très importantes et réparties sur des lieux géographique différents. L'utilisation d'un outil de stockage partagé et de travail collaboratif nous permet de créer un entrepôt de données stocké en cloud-computing et accessible de façon sécurisé par l'ensemble des membres du projet. Le choix d'associer à ces outils un système d'information de type entrepôt de données est en grosse partie dû à la capacité de ces systèmes de gérer des données non structurées et à organiser et présenter des données référencées par plusieurs mots clefs. Plus souple à l'usage qu'une base de données classique, ces outils permettent néanmoins une structuration pertinente des corpus de données en restructurant les données suivant une arborescence établie en concertation entre les collaborateurs du projet.

L'outil utilisé à ce propos est une base de données de gestion documentaire, cette base de données permet de stocker un document, des informations associées à ce document sous forme de méta données de type tags (comme sur les blogs). Les outils de recherche associés aux datawarehouse permettent de retrouver les documents associés par un système de mot clef, par requête « classique ».

L'ensemble de ce dispositif est utilisé pour le management de la qualité des projets de recherche

3-Retour d'expérience, le cas du réseau Relier

Le REseau quaLIté Enseignement supérieur et Recherche (RELIER) s'est constitué à la suite de la conférence Qualité et Enseignement supérieur du 5 décembre 2012, et sous l'impulsion conjointe du comité Qualité de la CPU et des acteurs eux-mêmes, afin de fédérer les approches et les compétences des différents acteurs de la Qualité des établissements d'enseignement supérieur et de recherche (ESR). Il recueille et croise à la fois les préoccupations des Présidents et des équipes qui les entourent et celles de ces mêmes acteurs sur le terrain, pour devenir force de proposition dans une démarche d'amélioration continue.

Constitué de cadres administratifs et d'enseignants-chercheurs, impliqués dans la gouvernance de leur établissement et dans la mise en oeuvre opérationnelle de démarche qualité.

Il est animé par un comité de pilotage de 15 personnes réparties sur l'ensemble du territoire, représentatives des différentes structures de l'enseignement supérieur différentes fonctions de direction des universités (équipe politique, direction générale, pilotage et services d'appuis). Ce comité de pilotage se réuni une journée toute les six semaines environ, néanmoins, tout les membres de ce comité travaillent régulièrement ensemble à distance pour faire vivre ce réseau.

Les outils que nous avons mis en place pour répondre aux problématiques de gestion de la qualité des projets pour des équipes géographiquement dispersées sont tous basés sur un système d'information en cloud computing Tout d'abord notre outils de base, portail d'entrée est notre site Intranet. Cet outil regroupe :

• un blog (avec possibilité de déposer des commentaires) de news, permettant a tout les membres de déposer une news pour les autres membres • un agenda partagé couplé à nos agendas personnel (ci ces derniers sont compatibles), la gestion d'un fichier des coordonnées des membres du projet. • La liste des actions en cours sous formes de to do lists avec gestion de l'état de l'avancement de l'action.

  Se pose alors beaucoup de questions, la première étant qui a LA dernière version du document ? La réponse à cette question est PERSONNE ! Chacun des collègues a une PSEUDO version, mais plus personne n'a LA dernière version. De plus se pose la question de la propriété intellectuelle. Qui est propriétaire des données a cet instant ? Ce que nous venons de montrer pour la rédaction d'un article vaut également pour le pilotage de projet et le travail sur les données et tableaux de bord de pilotage. Lors de la préparation de projet scientifique, pédagogique ou de gouvernance, la question de la maîtrise des données et des indicateurs mobilise de nombreux moyens humains et du temps. Comment avoir TOUS les documents et données du projet à jour et disponible en permanence pour l'ensemble des collaborateurs du projet ? Comment garantir la traçabilité des modifications d'un document ?Les garanties de sécurité et les outils proposés par les fournisseurs de solutions en Cloud permettent de définir une stratégie complète dans les domaines du stockage des données, du contrôle de l'accès et du transfert de données. Les stratégies sécurités proposées par les fournisseurs de solutions garantissent la sécurité de l'information de sa création à sa diffusion que ce soit en terme purement technologique, notamment en matière de continuité de service ou de reprise après sinistre (ISO 27002) qu'en terme de d'organisation du système d'information à par entière. Dans leurs versions contractuelles les outils proposés par les fournisseurs de système d'information en cloud computing, notamment par les géants informatiques proposant des solutions grand publics mais non sécurisées, la « mise sous contrat » garantit à l'utilisateur une sécurisation des données ainsi qu'une confidentialité basée

	Quel collaborateur a modifié quoi ? À quel moment ? Comment s'assurer que chaque acteur
	partage la même donnée de pilotage et de gestion d'un dossier ?
	De par nos expériences, que ce soit dans le pilotage de projet de recherche ou la coordination
	de réseau nous allons montrer dans cet article en quoi les outils informatiques et les systèmes
	d'informations dont la technologie est basée sur le Cloud Computing sont aujourd'hui une
	réponse aux problématiques de gestion de la qualité des projets et des données pour des
	équipes géographiquement dispersées.
	1 -Description du système -Un espace collaboratif de travail et
	un datawarehouse[1] (entrepôt de données) géré en cloud-
	computing ouvert à l'ensemble des équipes du projet.
	Afin de gérer leur projet, les équipes disposent de plusieurs espaces collaboratifs de travail.
	Basé sur une technologie de type « Cloud computing[i] », l'espace de travail collaboratif est mis
	en place au début du projet et permet la réalisation de plusieurs tâches nécessaires à ce
	dernier : le partage de l'information, l'échange de données entre plusieurs membres d'une
	même équipe, le travail en mode distant sur un même document et en simultané, et enfin le
	partage des agendas et des documents. Tous ces éléments sont accessibles par un portail web
	interactif de type intranet.
	Qu'est-ce que le cloud computing ?
	Le cloud computing peut se définir comme un mécanisme de sous-traitance informatique,
	comportant des caractères qui n'existaient pas dans l'externalisation informatique jusqu'à
	présent, en particulier : un service rendu au client sur base de ressources et d'équipements
	dont le client peut ignorer la

Au moment de rédiger un article à plusieurs mains, disons quatre personnes pour l'exemple la question se pose de partager les données, les informations avec les collègues qui doivent coécrire l'article. Dans la plupart des cas, l'usage du mail est la règle. Le premier collaborateur rédige un premier brouillon, le fait parvenir par mail pour modification à ses trois collègues. A partir de cet instant précis, il n'y a plus un mais quatre articles minimum (si on occulte les sauvegardes et autres transfert sur clef USB). localisation précise (le fameux nuage) ; et un service fourni et facturé à la demande, capable de s'adapter immédiatement à l'évolution des besoins du client.0 F 1 Pourquoi le cloud computing ? sur des normes comme la norme SAS 70 Type II (http://sas70.com/) ou encore ESCROW vérification niveau III (www.escroweurope.fr) qui protège la propriété intellectuelle des données de l'utilisateur. Les applicatifs sont basés sur une technologie de type cloud computing, c'est-àdire que l'infrastructure technique est déportée sur internet (dans le « cloud »). L'avantage d'une solution de Cloud est qu'elle permet de s'affranchir du média et du risque de perte ou de destruction accidentel de ses données. De plus, il permet un accès à ses données depuis n'importe quel endroit dans le monde, à condition de bénéficier d'un accès Internet. Enfin, le terminal d'accès (l'ordinateur de l'utilisateur) n'a pas nécessairement besoin d'être très puissant, les services et données étant déportés.

Les auteurs de la communication Thierry BONTEMS CNRS-Grenoble -Université Grenoble Alpes UMR 5194 Pacte -Responsable Qualité Institut d'études politiques -BP 48 38040 Grenoble cedex 9 -France Tel : +33 476 826 132 thierry.bontems@umrpacte.fr Sabine GOULIN Université de Lorraine Directrice -Délégation à l'AIde au Pilotage Et à la Qualité 34 cours Leopold 54052 NANCY Cedex Tel : +33 354 505 483 sabine.goulin@univ-lorraine.fr Caroline CALMUS Présidence de l'Université de Reims Champagne Ardenne Cellule d'Appui au Pilotage (CAP)-Directrice de la coordination managériale La Villa Douce -- 9 bd de la Paix 51097 REIMS CEDEX Tel : +33 326 918 295 caroline.calmus@univ-reims.fr [1]

  • Une présentation des membres du comité de pilotage que chacun des membres peut mettre à jour • un espace dédier au stockage des comptes-rendus de réunions, des présentations faites par les membres du comité, des présentations du réseau Le second outil indispensable à notre communication externe est le site Web du réseau www.relier-univ.fr dont l'adresse pointe sur le site https://sites.google.com/a/iepg.fr/relier-univ/ extension du site intranet et basé sur les mêmes technologies. Ce site est ouvert en lecture seule à l'ensemble de la population du monde et ouvert en modifications aux membres du comité de pilotage. Enfin troisième outil, un datawarehouse, qui permet à tous les membres de stocké, de modifier (en simultané ou en décalé) les documents. Les documents stockés dans cet entrepôt sont "tagués" avec des mots clefs, sur lesquels l'équipe s'est préalablement entendu afin de rendre les recherches plus aisées. Dans tous les cas les outils de cloudcomputing sont dotés d'outils de recherche par mot clefs ou plein texte. Cet outils est indispensable pour la rédaction de document et le travail collaboratif. Nous l'utilisons quotidiennement en le couplant a des outils d'audio ou de visio conférence. En conclusion, si le partage de données n'est pas une chose aisée lorsque les collaborateurs sont géographiquement dispersé, l'usage des technologies de type Cloud Computing garantie a chacun l'accès à la donnée à jour, à la modification de cette donnée, à la traçabilité de cette modification et de celle de ces collègues, enfin la modification en simultanée de documents de travail et ceci a distance, permettant le travail en collaboration parfaite. La qualité des travaux, des conditions de productions, de l'investissement des participants est accrue et l'ensemble du projet s'en trouve bénéficiaire. Questions pour la discussion : -Comment établir la confiance en de tels dispositifs aussi bien pour les enseignants chercheurs que pour les chefs de projets ou encore les parties prenantes comme les partenaires ou les financeurs? -Comment et en quoi cet outils contribue à la qualité des résultats et à l'atteinte des objectifs ? -Peut-on réellement changer de paradigme concernant la qualité des données et des documents avec une technologie de type cloud computing et si oui, comment initier ce dispositif ? Le lieu de stockage intermédiaire des différentes données en vue de la constitution du système d'information décisionnel est appelé entrepôt de données (en anglais datawarehouse). Le datawarehouse est ainsi le lieu unique de consolidation de l'ensemble des données du projet. Le créateur du concept de DataWareHouse, Bill Inmon, le définit comme suit : « Un datawarehouse est une collection de données thématiques, intégrées, non volatiles et historisées pour la prise de décisions. » Ses principales caractéristiques sont donc les suivantes : Le datawarehouse est orienté sujets, cela signifie que les données collectées doivent être orientées « métier » et donc triées par thème Le datawarehouse est composé de données intégrées, c'est-à-dire qu'un « nettoyage » préalable des données est nécessaire dans un souci de rationalisation et de normalisation Les données du datawarehouse sont non volatiles ce qui signifie qu'une donnée entrée dans l'entrepôt l'est pour de bon et n'a pas vocation à être supprimée Les données du datawarehouse doivent être historisées, donc datées Le cloud computing est un concept de déportation sur des serveurs distants des traitements informatiques traditionnellement localisés sur le poste utilisateur Le concept d'informatique dans le nuage est comparable à celui de la distribution de l'énergie électrique. La puissance de calcul et de stockage de l'information est proposée à la consommation par des compagnies spécialisées. De ce fait, les entreprises n'ont plus besoin de serveurs propres, mais confient cette ressource à une entreprise qui leur garantit une puissance de calcul et de stockage à la demande.

[i] Cloud computing :

http://www.droit-technologie.org/actuality-1528/cloud-computing-la-cnil-se-prononce.html