Review of the Synergies Between Computational Modeling and Experimental Characterization of Materials Across Length Scales

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends where predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure-properties relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to "simply" support experimental work. This is illustrated by examples from several application areas on structural materials. This manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.Comment: 25 pages, 11 figures, review article accepted for publication in J. Mater. Sc

Experimental evidence of ground albedo neutron impact on Soft Error Rate for nanoscale devices

International audienceThis work demonstrates the experimental evidence of ground albedo neutron impact on Soft Error Rate (SER) for nanoscale devices. The SER of a 45 nm technology was measured according to an experimental protocol using a californium sealed source and several scenes based on material blocks. High density polyethylene and concrete materials were considered to investigate the intrinsic role in albedo neutron productions and their effect on devices. Results show the impact in the spectrum concern mainly energies below 5 MeV. Devices are characterized by a sensitivity which varies according to the presence or not of thethe material block. Simulations using GEANT4 and MUSCA SEP3 tool were performed to extend analyses. A final part is devoted to investigate the impact of ground albedo neutrons on SER by considering realistic terrestrial neutron field

Statics and dynamics of magnetocapillary bonds

When ferromagnetic particles are suspended at an interface under magnetic fields, dipole-dipole interactions compete with capillary attraction. This combination of forces has recently given promising results towards controllable self-assemblies, as well as low Reynolds swimming systems. The elementary unit of these assemblies is a pair of particles. Although equilibrium properties of this interaction are well described, dynamics remain unclear. In this letter, the properties of magnetocapillary bonds are determined by probing them with magnetic perturbations. Two deformation modes are evidenced and discussed. These modes exhibit resonances whose frequencies can be detuned to generate non-reciprocal motion. A model is proposed which can become the basis for elaborate collective behaviours

Remote control of self-assembled microswimmers

Physics governing the locomotion of microorganisms and other microsystems is dominated by viscous damping. An effective swimming strategy involves the non-reciprocal and periodic deformations of the considered body. Here, we show that a magnetocapillary-driven self-assembly, composed of three soft ferromagnetic beads, is able to swim along a liquid-air interface when powered by an external magnetic field. More importantly, we demonstrate that trajectories can be fully controlled, opening ways to explore low Reynolds number swimming. This magnetocapillary system spontaneously forms by self-assembly, allowing miniaturization and other possible applications such as cargo transport or solvent flows.Comment: 5 pages, 5 figures articl

Cadre d'évaluation de systèmes de recherche d'information géographique Apport de la combinaison des dimensions spatiale, temporelle et thématique

National audienceCommon search engines process users' queries, i.e., information needs, by extracting terms from documents. Such approaches are limited regarding particular contexts, such as specialized collections (e.g., cultural heritage collections) or specific retrieval criteria (e.g., multidimensional criteria). In this paper, we consider Geographic Information Retrieval Systems (GIRS) exploiting the spatial, temporal, and topical dimensions. Our contribution is twofold as we propose a GIRS evaluation framework for testing the following assumption: combining spatial and temporal dimensions along with the topical dimension improves GIRS effectiveness

Progressive Neural Networks

Learning to solve complex sequences of tasks--while both leveraging transfer and avoiding catastrophic forgetting--remains a key obstacle to achieving human-level intelligence. The progressive networks approach represents a step forward in this direction: they are immune to forgetting and can leverage prior knowledge via lateral connections to previously learned features. We evaluate this architecture extensively on a wide variety of reinforcement learning tasks (Atari and 3D maze games), and show that it outperforms common baselines based on pretraining and finetuning. Using a novel sensitivity measure, we demonstrate that transfer occurs at both low-level sensory and high-level control layers of the learned policy