Search results for: Sauvage Jean-François

Authors: T. Delval, C. Sauvage, Q. Jullien, R. Viano, T. Diallo, B. Collignan, G. Picinbono

Abstract:

In the context of the international spread of COVID-19, the Centre Scientifique et Technique du Bâtiment (CSTB) has led a joint research with the French government authorities Hauts-de-Seine department, to analyse the risk in school spaces according to their configuration, ventilation system and spatial segmentation strategy. This paper describes the main results of this joint research. A multidisciplinary team involving experts in indoor air quality/ventilation, pedestrian movements and IT domains was established to develop a COVID risk analysis tool based on Building Information Model. The work started with specific analysis on two pilot schools in order to provide for the local administration specifications to minimize the spread of the virus. Different recommendations were published to optimize/validate the use of ventilation systems and the strategy of student occupancy and student flow segmentation within the building. This COVID expertise has been digitized in order to manage a quick risk analysis on the entire building that could be used by the public administration through an easy user interface implemented in a free BIM Management software. One of the most interesting results is to enable a dynamic comparison of different ventilation system scenarios and space occupation strategy inside the BIM model. This concurrent engineering approach provides users with the optimal solution according to both ventilation and pedestrian flow expertise.

Keywords: BIM, knowledge management, system expert, risk management, indoor ventilation, pedestrian movement, integrated design

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Authors: Dumont Maxime, Correia Carlos, Sauvage Jean-François, Schwartz Noah, Gray Morgan

Abstract:

Context: The concept of the segmented telescope is unavoidable to build extremely large telescopes (ELT) in the quest for spatial resolution, but it also allows one to fit a large telescope within a reduced volume of space (JWST) or into an even smaller volume (Standard Cubesat). Cubesats have tight constraints on the computational burden available and the small payload volume allowed. At the same time, they undergo thermal gradients leading to large and evolving optical aberrations. The pupil segmentation comes nevertheless with an obvious difficulty: to co-phase the different segments. The CubeSat constraints prevent the use of a dedicated wavefront sensor (WFS), making the focal-plane images acquired by the science detector the most practical alternative. Yet, one of the challenges for the wavefront sensing is the non-linearity between the image intensity and the phase aberrations. Plus, for Earth observation, the object is unknown and unrepeatable. Recently, several studies have suggested Neural Networks (NN) for wavefront sensing; especially convolutional NN, which are well known for being non-linear and image-friendly problem solvers. Aims: We study in this paper the prospect of using NN to measure the phasing aberrations of a segmented pupil from the focal-plane image directly without a dedicated wavefront sensing. Methods: In our application, we take the case of a deployable telescope fitting in a CubeSat for Earth observations which triples the aperture size (compared to the 10cm CubeSat standard) and therefore triples the angular resolution capacity. In order to reach the diffraction-limited regime in the visible wavelength, typically, a wavefront error below lambda/50 is required. The telescope focal-plane detector, used for imaging, will be used as a wavefront-sensor. In this work, we study a point source, i.e. the Point Spread Function [PSF] of the optical system as an input of a VGG-net neural network, an architecture designed for image regression/classification. Results: This approach shows some promising results (about 2nm RMS, which is sub lambda/50 of residual WFE with 40-100nm RMS of input WFE) using a relatively fast computational time less than 30 ms which translates a small computation burder. These results allow one further study for higher aberrations and noise.

Keywords: wavefront sensing, deep learning, deployable telescope, space telescope

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Authors: Igor B. Sivaev

Abstract:

Design of molecular machines is an extraordinary growing and very important area of research that it was recognized by awarding Sauvage, Stoddart and Feringa the Nobel Prize in Chemistry in 2016 'for the design and synthesis of molecular machines'. Based on the type of motion being performed, molecular machines can be divided into two main types: molecular motors and molecular switches. Molecular switches are molecules or supramolecular complexes having bistability, i.e., the ability to exist in two or more stable forms, among which may be reversible transitions under external influence (heating, lighting, changing the medium acidity, the action of chemicals, exposure to magnetic or electric field). Molecular switches are the main structural element of any molecular electronics devices. Therefore, the design and the study of molecules and supramolecular systems capable of performing mechanical movement is an important and urgent problem of modern chemistry. There is growing interest in molecular switches and other devices of molecular electronics based on transition metal complexes; therefore choice of suitable stable organometallic unit is of great importance. An example of such unit is bis(dicarbollide) complexes of transition metals [3,3’-M(1,2-C₂B₉H₁₁)₂]ⁿ⁻. The control on the ligand rotation in such complexes can be reached by introducing substituents which could provide stabilization of certain rotamers due to specific interactions between the ligands, on the one hand, and which can participate as Lewis bases in complex formation with external metals resulting in a change in the rotation angle of the ligands, on the other hand. A series of isomeric methyl sulfide derivatives of cobalt bis(dicarbollide) complexes containing methyl sulfide substituents at boron atoms in different positions of the pentagonal face of the dicarbollide ligands [8,8’-(MeS)₂-3,3’-Co(1,2-C₂B₉H₁₀)₂]⁻, rac-[4,4’-(MeS)₂-3,3’-Co(1,2-C₂B₉H₁₀)₂]⁻ and meso-[4,7’-(MeS)₂-3,3’-Co(1,2-C₂B₉H₁₀)₂]⁻ were synthesized by the reaction of CoCl₂ with the corresponding methyl sulfide carborane derivatives [10-MeS-7,8-C₂B₉H₁₁)₂]⁻ and [10-MeS-7,8-C₂B₉H₁₁)₂]⁻. In the case of asymmetrically substituted cobalt bis(dicarbollide) complexes the corresponding rac- and meso-isomers were successfully separated by column chromatography as the tetrabutylammonium salts. The compounds obtained were studied by the methods of ¹H, ¹³C, and ¹¹B NMR spectroscopy, single crystal X-ray diffraction, cyclic voltammetry, controlled potential coulometry and quantum chemical calculations. It was found that in the solid state, the transoid- and gauche-conformations of the 8,8’- and 4,4’-isomers are stabilized by four intramolecular CH···S(Me)B hydrogen bonds each one (2.683-2.712 Å and 2.709-2.752 Å, respectively), whereas gauche-conformation of the 4,7’-isomer is stabilized by two intramolecular CH···S hydrogen bonds (2.699-2.711 Å). The existence of the intramolecular CH·S(Me)B hydrogen bonding in solutions was supported by the 1H NMR spectroscopy. These data are in a good agreement with results of the quantum chemical calculations. The corresponding iron and nickel complexes were synthesized as well. The reaction of the methyl sulfide derivatives of cobalt bis(dicarbollide) with various labile transition metal complexes results in rupture of intramolecular hydrogen bonds and complexation of the methyl sulfide groups with external metal. This results in stabilization of other rotational conformation of cobalt bis(dicarbollide) and can be used in design of molecular switches. This work was supported by the Russian Science Foundation (16-13-10331).

Keywords: molecular switches, NMR spectroscopy, single crystal X-ray diffraction, transition metal bis(dicarbollide) complexes, quantum chemical calculations

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