NOMAD-E-CAM workshop on Modeling materials at realistic space and time scales via optimal exploitation of exascale computers and AI
CECAM-HQ-EPFL, Lausanne, Switzerland
While the electronic structure and the nature of the chemical bond ultimately determine the properties of real materials, the femto-second- and nano-meter-scale information has to be linked to the statistical mechanics addressing the larger time and length scales that govern real-life situations. In fact, real materials are not necessarily at thermal equilibrium, and the microstructure of the material (in solids materials these are grains and grain boundaries) are crucial for the materials properties and functions. Thus, quantum mechanics (QM) has to be connected to molecular mechanics (MM), large-scale molecular dynamics (MD), kinetic Monte Carlo (kMC), and computational fluid dynamics (CFD), just to name a few methodologies. Very importantly, we need robust, error-controlled links with knowledge of uncertainty between the various simulation methodologies. And, for the analysis of results and achieving understanding we also need reverse mapping, not just going from small to large scales but also backwards. These issues have been discussed in several workshops, e.g. the long-term program at IPAM in 20051, or at the CECAM/Psi-k Research Conference on Multi-scale Modeling from First-Principles in 20132. Obviously, there are many more, and the organizers of the proposed workshop had been active in several of them.
The Handbook of Materials Modeling (2005) was a classical reference , and the 2nd edition appeared earlier this year . This is now a six-volume major reference reflecting the significant developments in all aspects of computational materials research over the past decade, featuring progress in simulations at multiple scales and increasingly more realistic materials models. The chapters of this book series were essentially finished in late 2018. Consequently, two aspects come short, namely exascale computing and related artificial intelligence (AI) methods. Though some AI contributions are there, exascale is hardly mentioned.
1. Bridging Time and Length Scales in Materials Science and Bio-Physics, September 12 - December 16, 2005, Russel Caflisch, Cecilia Clementi, Weinan E, Michael Klein, Christian Ratsch, Karsten Reuter, Matthias Scheffler, Klaus Schulten, Annabella Selloni, http://www.ipam.ucla.edu/programs/long-programs/bridging-time-and-length-scales-in-materials-science-and-bio-physics.
2.~CECAM/Psi-k Research Conference on Multi-scale Modeling from First-Principles, September 08-13, 2013, Michel Mareschal, Matthias Scheffler, https://www.cecam.org/workshop-details/666
Claudia Draxl (Humboldt-Universität zu Berlin) - Organiser
Matthias Scheffler (Fritz-Haber-Institut der Max-Planck-Gesellschaft) - Organiser
Sara Bonella (CECAM HQ) - Organiser
Ignacio Pagonabarraga (CECAM HQ) - Organiser