Computational Materials Science & AI
KKMaterials Properties at Finite Temperature via Atomic-Scale Modelling: Methodologies, Applications and Beyond
Atomic-scale modelling carried out to account for temperature effects is the theoretical strategy bridging the gap between microscopic evolution as a function of time and macroscopic determination of quantities of interest as statistical averages. This ansatz has been exploited over the years to build up approaches fully quantitative and highly reliable in terms of predictive power. This symposium will feature important realizations in this context, for both methodologies and applications.
Scope:
The purpose of this Symposium is to provide a forum of communication and exchange in the area of computational materials science, with a specific focus for the calculation of those properties depending explicitly on temperature. The link thereby established between computers and thermodynamics has greatly extended the impact of this discipline by providing tools that not only mimic experiments but provide information often inaccessible to measurements. Achieving these goals calls for methodologies able to account for changes in interatomic bonding at various scales, ranging from the nanometer in the case of nanomaterials (clusters for instance, either isolated or supported on surfaces) up to sizes encompassing several shells of neighbors (disordered materials or compounds made of extended parts sharing interfaces). As a revealing example, density functional theory (and related first-principles approaches) have made possible the account of the electronic structure to increase the realistic character of modelling. Its inclusion within molecular dynamics stands as the major methodological realization of the last forty years, its intrinsic limits in terms of dimensions and time trajectories being currently surmounted by the increasing impact of machine learning approaches rooted on reliable data bases. Quite often such reference data are built on the same atomic-scale first-principles calculations that are exploited to describe, on much reduced scales, the behavior of materials. Ideally but not exclusively, the symposium will host contributions focusing on systems for which the knowledge of the atomic structure, not easily accessible to experiments, is a crucial prerequisite. On the side of atomic-scale methodologies, the symposium will focus on the most recent atomic-scale theoretical strategies (later developments of density functional theory, exchange-correlation functionals, dispersion forces) and the way these advances can be exploited to produce smart interatomic potentials through the devise of machine-learning tools. Determination of structural properties will be given a special attention as the prerequisite to consider realistic situations featuring substantial evolution of chemical bonding with temperature. Also, we shall consider contributions focusing on the interplay between calculations and interpretation of experiments, with the intent of attracting experimentalists willing to broaden their perspective by including modelling in their research projects.
Hot topics to be covered by the symposium:
- Methodological advances of density functional theory and first-principles approaches in connection with the modelling of materials at finite temperatures.
- Statistical mechanics of simple models as a guide to understand generic materials properties.
- Establishment and applications of machine-learning interatomic potentials to describe large scale phenomena.
- Evolution of nanostructures with changing composition and temperature: from the cluster to the bulk.
- Disordered materials: structural, electronic and thermal properties.
- Heat transport in glasses and at interfaces.
- The future of computational materials science: can we combine sustainability and need for computational power?
- How can we strengthen the link between experiments and predictive power of computational materials science?
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300 bd Sébastien Brant - CS 10413 - F-67412 Illkirch Cedex
carlo.massobrio@cnrs.frUNT Discovery Park E132 3940 N. Elm Street, Denton, TX 76207, USA
Jincheng.du@unt.edu6-6-05 Aramaki Aza Aoba, Aoba-ku, Sendai, Miyagi 980-8579, Japan
junjie.zhao.d1@tohoku.ac.jpState Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, P. R. China
zijuandu@whut.edu.cn