Mehdi Djafari Rouhani

Prediction of the performance of a Si-micromachined microthruster by computing the subsonic gas flow inside the thruster

MEMS-based microthrusters are now introduced and fabricated to meet micropropulsion requirements especially for the attitude control of the nanosatellites. The key to the development of these microsystems lies in the generation of extremely accurate thrust level. This is made possible by modelling tools capable of predicting the processes inside the thruster during the subsonic combustion and of computing the theoretical performance of the systems. In this paper, we present a new model based on the computation of the unsteady gas flow inside the microthruster. The results show the evolution of the gas pressure, velocity and gas volume at each section of the thruster and at each step in the propulsion process. The final aim of this study is to obtain a model package capable of predicting the level of the exhaust thrust of any subsonic microthruster for any given geometrical features. For a glycidyle azide polymer (GAP)-based microthruster, the calculations yield the best subsonic micronozzle design: the divergent length ranges from three to seven times the throat radius for a divergence angle of 12°. The chamber-to-throat section ratio must be comprised between 5 and 10. Modelling results also show that, for a 4-mm combustion diameter thruster, the thrust force ranges from 2.5 to 75 mN, depending on geometrical characteristics.

A computational chemist approach to gas sensors: Modeling the response of SnO2 to CO, O2, and H2O Gases

A general bottom‐up modeling strategy for gas sensor response to CO, O2, H2O, and related mixtures exposure is demonstrated. In a first stage, we present first principles calculations that aimed at giving an unprecedented review of basic chemical mechanisms taking place at the sensor surface. Then, simulations of an operating gas sensor are performed via a mesoscopic model derived from calculated density functional theory data into a set of differential equations. Significant presence of catalytic oxidation reaction is highlighted.

A diffusion–reaction scheme for modeling ignition and self-propagating reactions in Al/CuO multilayered thin films

Thermite multilayered films have the potential to be used as local high intensity heat sources for a variety of applications. Improving the ability of researchers to more rapidly develop Micro Electro Mechanical Systems devices based on thermite multilayer films requires predictive modeling in which an understanding of the relationship between the properties (ignition and flame propagation), the multilayer structure and composition (bilayer thicknesses, ratio of reactants, and nature of interfaces), and aspects related to integration (substrate conductivity and ignition apparatus) is achieved. Assembling all these aspects, this work proposes an original 2D diffusion-reaction modeling framework to predict the ignition threshold and reaction dynamics of Al/CuO multilayered thin films. This model takes into consideration that CuO first decomposes into Cu2O, and then, released oxygen diffuses across the Cu2O and Al2O3 layers before reacting with pure Al to form Al2O3. This model is experimentally validated fr...

General Strategy for the Design of DNA Coding Sequences Applied to Nanoparticle Assembly

The DNA-directed assembly of nano-objects has been the subject of many recent studies as a means to construct advanced nanomaterial architectures. Although much experimental in silico work has been presented and discussed, there has been no in-depth consideration of the proper design of single-strand sticky termination of DNA sequences, noted as ssST, which is important in avoiding self-folding within one DNA strand, unwanted strand-to-strand interaction, and mismatching. In this work, a new comprehensive and computationally efficient optimization algorithm is presented for the construction of all possible DNA sequences that specifically prevents these issues. This optimization procedure is also effective when a spacer section is used, typically repeated sequences of thymine or adenine placed between the ssST and the nano-object, to address the most conventional experimental protocols. We systematically discuss the fundamental statistics of DNA sequences considering complementarities limited to two (or three) adjacent pairs to avoid self-folding and hybridization of identical strands due to unwanted complements and mismatching. The optimized DNA sequences can reach maximum lengths of 9 to 34 bases depending on the level of applied constraints. The thermodynamic properties of the allowed sequences are used to develop a ranking for each design. For instance, we show that the maximum melting temperature saturates with 14 bases under typical solvation and concentration conditions. Thus, DNA ssST with optimized sequences are developed for segments ranging from 4 to 40 bases, providing a very useful guide for all technological protocols. An experimental test is presented and discussed using the aggregation of Al and CuO nanoparticles and is shown to validate and illustrate the importance of the proposed DNA coding sequence optimization.

Strained semiconductors structures: simulation of the thin films heteroepitaxial growth

We have performed an atomic-scale simulation of (100) thin films heteroepitaxial growth of semiconductors with zincblende structure by associating a Monte Carlo technique with an energy model based on the valence force field approximation. It is shown that grooves showing (111) facets are formed in the early stages of the growth owing to enhanced interlayer migrations. The strain relief can be achieved within a few atomic layers, in agreement with experimental observations.

Toward in Silico Biomolecular Manipulation through Static Modes: Atomic Scale Characterization of HIV‑1 Protease Flexibility

Probing biomolecular flexibility with atomic-scale resolution is a challenging task in current computational biology for fundamental understanding and prediction of biomolecular interactions and associated functions. This paper makes use of the static mode method to study HIV-1 protease considered as a model system to investigate the full biomolecular flexibility at the atomic scale, the screening of active site biomechanical properties, the blind prediction of allosteric sites, and the design of multisite strategies to target deformations of interest. Relying on this single calculation run of static modes, we demonstrate that in silico predictive design of an infinite set of complex excitation fields is reachable, thanks to the storage of the static modes in a data bank that can be used to mimic single or multiatom contact and efficiently anticipate conformational changes arising from external stimuli. All along this article, we compare our results to data previously published and propose a guideline for efficient, predictive, and custom in silico experiments.

Modeling of Silicon Nanodots Nucleation and Growth Deposited by LPCVD on SiO2 : From Molecule/Surface Interactions to Reactor Scale Simulations

We present first results combining models at continuum and atomistic (DFT, Density Functional Theory) levels to improve understanding of key mechanisms involved in silicon nanodots (NDs) synthesis on SiO2 silicon dioxide surface, by Low Pressure Chemical Vapor Deposition (LPCVD) from silane SiH4. In particular, by simulating an industrial LPCVD reactor using the CFD (Computational Fluid Dynamics) code Fluent, we find that deposition time could be increased and then reproducibility and uniformity of NDs deposition could be improved by highly diluting silane in a carrier gas. A consequence of this high dilution seems to be that the contribution to deposition of unsaturated species such as silylene SiH2 highly increases. This result is important since our first DFT calculations have shown that silicon chemisorption on silanol Si-OH or siloxane Si-O-Si bonds present on SiO2 substrates could only proceed from silylene (and probably from other unsaturated species). The silane saturated molecule could only contribute to NDs growth, i.e. silicon chemisorption on already deposited silicon bonds. Increasing silylene contribution to deposition in highly diluting silane could then also exalt silicon nucleation on SiO substrates and then increase NDs density.

Atomic scale simulation of the growth of CdTe layers on GaAs

The initial stages of the growth of CdTe on (100) GaAs with 14. 7 lattice mismatch has been simulated. It is shown that growth in (111) direction with the presence of twins is always preferred on perfect substrate surfaces. In the case of growth in (100) direction misfit dislocations are formed. The critical thickness is evaluated by extrapolation to be 6 - 8 atomic monolayers .