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  • ICMS 2019
  • The 5th International Conference on Molecular Simulation
  • November 3-6, 2019 / Lotte Hotel Jeju, Korea

Program

Important Dates
Abstract Submission
March 1 ~ July 31, 2019
Acceptance Notification
August 14, 2019
Early Registration
June 5 ~ September 30, 2019
Final Program Announcement
October 2, 2019
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Plenary Speaker



  • Matthias Scheffler
  • Fritz-Haber-Institut der Max-Planck-Gesellschaft, Germary
  • Title: "Big-Data-Driven Materials Science and its FAIR Data Infrastructure"
    Biography and Abstract
Biography
Matthias Scheffler is a Director at the FHI. He is known for his pioneering work linking density-functional theory with thermodynamics and statistical mechanics. Currently he leads the pan-European NOMAD project, which is a European Centre of Excellence that provides a central data repository for materials modelling as well as pioneering in the field of big data analytics for the advancement of materials design and engineering. He is honorary professor at all three universities of Berlin and “distinguished visiting professor for materials science and engineering” at UC Santa Barbara.
Abstract
This talk addresses the forth paradigm of materials research ˗ big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are addressed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR ˗ Findable, Accessible, Interoperable and Re-purposable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even from high-throughput studies. Recent progress is reviewed and demonstrated, and we conclude with a forward-looking perspective, addressing important not yet solved challenges.
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  • Berend Smit
  • Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
  • Title: "The Nanoporous Materials Genome in Action"
    Biography and Abstract
Biography

Berend Smit received an MSc in Chemical Engineering in 1987 and an MSc in Physics both from the Technical University in Delft (the Netherlands). He received in 1990 cum laude PhD in Chemistry from Utrecht University (the Netherlands). He was a (senior) Research Physicists at Shell Research from 1988-1997, Professor of Computational Chemistry at the University of Amsterdam (the Netherlands) 1997-2007. In 2004 Berend Smit was elected Director of the European Center of Atomic and Molecular Computations (CECAM) Lyon France. Since 2007 he is Professor of Chemical Engineering and Chemistry at U.C. Berkeley and Faculty Chemist at Materials Sciences Division, Lawrence Berkeley National Laboratory. Since 2014 he is director of the laboratory for molecular simulations (LSMO) at EPFL.

Berend Smit's research focuses on the application and development of novel molecular simulation techniques, with emphasis on energy related applications. Together with Daan Frenkel he wrote the textbook Understanding Molecular Simulations and together with Jeff Reimer, Curt Oldenburg, and Ian Bourg the textbook Introduction to Carbon Capture and Sequestration.

Abstract

The attractive feature of Metal Organic Frameworks (MOFs) is that by changing the ligand and/or metal, they can be chemically tuned to perform optimally for a given application. This unique chemical tunability allows us to tailor-make materials that are optimal for a given application. The promise of finding just the right material seems remote however: because of practical limitations we can only ever synthesize, characterize, and test a tiny fraction of all possible materials. To take full advantage of this development, therefore, we need to develop alternative techniques, collectively referred to as Materials Genomics, to rapidly screen large numbers of materials and obtain fundamental insights into the chemical nature of the ideal material for a given application.

These computational materials genomics initiatives have been so successful that we have created a new problem: what to do with so much data? In this presentation we will discuss different computational strategies to deal with a large amount of data. We illustrate on the use of these strategies by addressing the following questions: How the find the best material for a given application? How to find materials with similar pore shape? How to design a material that optimally binds CO2? And, what can we learn from failed experiments?

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  • Huai Sun
  • Shanghai Jiao Tong University, China
  • Title : (will be announced.)
    Biography and Abstract
[ Biography and Abstract ] will be announced
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