Did you ever think about what your ideal work environment for scientific programming would be like? Here's my version of it.

Computational techniques have revolutionized many aspects of scientific research over the last few decades. Experimentalists use computation for data analysis, processing ever bigger data sets. Theoreticians compute predictions from ever more complex models. However, traditional articles do not permit the publication of big data sets or complex models. As a consequence, these crucial pieces of information no longer enter the scientific record. Moreover, they have become prisoners of scientific software: many models exist only as software implementations, and the data are often stored in proprietary formats defined by the software. In this article, I argue that this emphasis on software tools over models and data is detrimental to science in the long term, and I propose a means by which this can be reversed.

The Molecular Modeling Toolkit is a library that implements common molecular simulation techniques, with an emphasis on biomolecular simulations. It uses modern software engineering techniques (object-oriented design, a high-level language) to overcome limitations associated with the large monolithic simulation programs that are commonly used for biomolecules. Its principal advantages are (1) easy extension and combination with other libraries due to modular library design; (2) a single high-level general-purpose programming language (Python) is used for library implementation as well as for application scripts; (3) use of documented and machine-independent formats for all data files; and (4) interfaces to other simulation and visualization programs. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 79–85, 2000

Normal mode analysis has become one of the standard techniques in the study of the dynamics of biological macromolecules. It is primarily used for identifying and characterizing the slowest motions in a macromolecular system, which are inaccessible by other methods. This text explains what normal mode analysis is and what one can do with it without going beyond its limit of validity. The focus is on proteins, although normal mode analysis can equally well be applied to other macromolecules (e. g. DNA) and to macromolecular assemblies ranging in size from protein-ligand complexes to a whole ribosome. By definition, normal mode analysis is the study of harmonic potential wells by analytic means.

Adopting a functional programming style could make your programs more robust, more compact, and more easily parallelizable. However, mastering it requires some effort. This article's purpose is to explain what functional programming is and how it differs from traditional imperative programming. The author also explains how functional programming helps with concurrent and parallel programming. The language I use in the examples is Clojure, a modern dialect of Lisp.

The development of cost-effective solar cells requires on the one hand to master the elaboration techniques, and on the other hand, an adequate design to optimise the photovoltaic efficiency. These two research topics are closely linked and their association in the research work is the key in the development of novel thin film solar cells. The design associated with numerical optimisation gives the set of optimal physical and geometrical parameters, taking into account the technological feasibility. This will allow elaboration to target the most efficient structures in order to speed up the final device realisation. In this work, we used a new approach, based on rigorous multivariate mathematical global Bayesian algorithm, to optimise a Schottky based solar cell (SBSC) using InGaN as the absorber. The obtained photovoltaic efficiency is close to the conventional structures efficiency while being less complex to elaborate. In addition, the results have shown that the optimised SBSC structure exhibits high fabrication tolerances.

The challenge of switching for photovoltaic as a major source of electricity can only be fulfilled by using solar cells based on low toxicity and earth abundant materials combined with a low cost process. One of the most promising solution to achieve this goal is to use a metal oxide absorber such as cuprous oxide (Cu2O). In 2016, a Cu2O/ZnGeO solar cell was demonstrated by the Minani group and reached a record efficiency of 8.1%. A recent modeling of Cu2O solar cells by Rizi et al. confirms that ZnGeO buffer layer outperforms other buffer layers reported experimentally due to a better band alignement. However the experimental and simulated results were obtained by taking into account a solar cell based on a high demanding energy process (T>1000°C). Cuprous oxide thin films have already been developed by low cost and large area compatible processes, but currently in detriment of material quality with grain size in the range of tenth of nanometers and mobility two order of magnitude lower. In order to evaluate the impact of low cost processes on solar cell performances, we analyse the modelisation results of Cu2O/ZnGeO solar cell by carefully taking into account experimental material properties, defects and grain size of Cu2O grown by low cost processes. The conclusion of this analysis will serve as a guideline for solar cells elaboration by spray pyrolysis in our laboratory and measurements of device performances will be compared with our simulated results.

A detailed investigation on the performance of an InGaN-based double-junction solar cell was carried out. We have globally simulated the solar cell using empirical InGaN material parameters, to avoid any overestimation in the solar cell performances. In order to take into account the interdependence of the solar cell physical and geometrical parameters, ensuring the absoluteness of the optimized photovoltaic performances, the cell was optimized using a multivariate optimization algorithm that simultaneously optimizes eleven physical and geometrical parameters. We obtained an optimal efficiency of 24.4%, with a short circuit current J SC = 12.92 mA=cm 2 , an open circuit voltage V OC = 2.287 V and a fill factor FF = 82.55%. We then quantitatively investigated the impact on the solar cell performances of the internal polarization and structural defects in InGaN. We have shown that the internal polarization reduces the performance of the cell by inducing an electric field which does not favor an efficient collection of photo-generated carriers. We have also investigated the impact of structural defects in InGaN, including disorder and deep defects, and correlated their effect to the InGaN doping concentration.

On the road towards next generation high efficiency solar cells, the ternary Indium Gallium Nitride (InGaN) alloy is a good passenger since it allows to cover the whole solar spectrum through the change in its Indium composition. The choice of the main structure of the InGaN solar cell is however crucial. Obtaining a high efficiency requires to improve the light absorption and the photogenerated carriers collection that depend on the layers parameters, including the Indium composition, p-and n-doping, device geometry.. . Unfortunately, one of the main drawbacks of InGaN is linked to its p-type doping, which is very difficult to realize since it involves complex technological processes that are difficult to master and that highly impact the layer quality. In this paper, the InGaN p-n junction (PN) and p-in junction (PIN) based solar cells are numerically studied using the most realistic models, and optimized through mathematically rigorous multivariate optimization approaches. This analysis evidences optimal efficiencies of 17.8% and 19.0% for the PN and PIN structures. It also leads to propose, analyze and optimize player free InGaN Schottky-Based Solar Cells (SBSC): the Schottky structure and a new MIN structure for which the optimal efficiencies are shown to be a little higher than for the conventional structures: respectively 18.2% and 19.8%. The tolerance that is allowed on each parameter for each of the proposed cells has been studied. The new MIN structure is shown to exhibit the widest tolerances on the layers thicknesses and dopings. In addition to its being player free, this is another advantage of the MIN structure since it implies its better reliability. Therefore, these new InGaN SBSC are shown to be alternatives to the conventional structures that allow removing the p-type doping of InGaN while giving photovoltaic (PV) performances at least comparable to the standard multilayers PN or PIN structures.

The Indium Gallium Nitride III-N alloy has the required potentialities to be a material of choice used in the next generation high efficiency solar cells. Indeed, the mere change in its Indium composition allows its absorption to cover the whole solar spectrum. One of InGaN main challenges remains today its p-doping. We therefore propose a comparative study between PN and PIN thin films structures, alongside new Schottky based designs which allow the removal of the difficult p-layer. A mathematically rigorous multi-criteria structure optimization associated to a 2D simulation based on actually measured physical parameters and precise models lead to theoretical efficiencies of 17.8%, 19.0%, 18.2% and 19.8% respectively for the PN, PIN, Schottky and a new proposed Metal-IN (MIN) Schottky based structure. The tolerance that is allowed on each parameter for each of the proposed cells has been thoroughly studied. These studies have shown that the new MIN structure exhibits high fabrication tolerances. This is particularly true for the n-doping of its n-layer, which can be raised enough, without loss of efficiency, to realize good low resistance ohmic contacts. Therefore, these new InGaN Schottky Based Solar Cells (SBSC) are shown to be efficient and tolerant alternatives to the conventional structures, allowing the removal of the p-type doping of InGaN while giving photovoltaic (PV) performances comparable to the highest reported thin films Solar Cell efficiencies.

Owing to its good tolerance to radiations, its high light absorption and its Indium-composition-tuned bandgap, the Indium Gallium Nitride (InGaN) ternary alloy is a good candidate for high--efficiency--high--reliability solar cells able to operate in harsh environments. Unfortunately, InGaN p-doping is still a challenge, owing to InGaN residual n-doping, the lack of dedicated acceptors and the complex fabrication process itself. To these drawbacks can be added the uneasy fabrication of ohmic contacts and the difficulty to grow the high-quality-high-Indium-content thin films which would be needed to cover the whole solar spectrum. These drawbacks still prevent InGaN solar cells to be competitive with other well established III-V and silicon technologies. In this communication, a new Metal-IN (MIN) InGaN solar cell structure is proposed, where the InGaN p-doped layer is removed and replaced by a Schottky contact, lifting one of the above mentioned drawbacks. A set of realistic physical models based on actual measurements is used to simulate and optimize its behavior and performance using mathematically rigorous multi-criteria optimization methods, aiming to show that both efficiency and fabrication tolerances are better than the previously described simple InGaN Schottky solar cell.

The InGaN ternary alloy has the potentiality to achieve high efficiency solar cells: tunable bandgap in the whole solar spectrum, high absorption coefficient, high stability and radiation tolerance. These very promising characteristics make InGaN potentially ideal for designing and developing next-generation high-efficiency thin films solar cells. However, challenging issues remain to address: (i) the difficulty to elaborate sufficiently thick monocrystalline InGaN layers with a high Indium content; (a) the high defects density and the spontaneous and piezoelectric polarizations; (iii) the p-doping which remains difficult to master. In this report, we use rigorous optimization approach based on state-of-the-art optimization algorithms to investigate the effect of defects and polarization (spontaneous and piezoelectric) on a double junction InGaN solar cell. A better understanding of the mechanisms involved in the heterostructure has a crucial impact on the design and elaboration of high efficiency InGaN thin films solar cells which require, in particular, a precise control of the Tunnel Junction elaboration which is still very challenging.

Because of remarkable properties of InGaN, we simulated and optimized an InGaN-based dual-junction solar cell connected by a specifically designed tunnel junction. The device is simulated in the framework of a drift-diffusion model using the ATLAS device simulation framework from the Silvaco company. The optimization is done by coupling ATLAS with multivariate mathematical optimization methods based on state-of-the-art optimization algorithms. For that, we used a Python package that we developed in the SAGE software interface. The objective is to optimize the conversion efficiency of the solar cell by simultaneously optimizing several physical and geometrical parameters of the solar cell. It is an unprecedented multivariate optimization for solar cells which takes into account the correlation between these parameters. For this solar cell, we optimized simultaneously 11 parameters of the structure. An optimum conversion efficiency of 24% was predicted for this designed solar cell.