472588 Pushing the Frontiers of Atomistic Modeling Towards Predictive Design of Materials

Monday, November 14, 2016: 1:36 PM
Yosemite A (Hilton San Francisco Union Square)
Subramanian Sankaranarayanan, Center for Nanoscale Materials, Argonne National Laboratory, Argonne, IL, Badri Narayanan, Argonne National Lab, Lemont, IL and Mathew Cherukara, X-ray Sciences Division, Argonne National Lab, Lemont, IL

The ability to perform accurate calculations efficiently is crucial for computational materials design. In this talk, we will discuss our stream-lined approach to force field development using first principles density functional theory training data and machine learning algorithms. Our objective has been to develop new, first-principles based, more accurate and more robust inter-atomic potentials for accurate simulations of dynamical processes at reactive interfaces and low dimensional systems such as clusters and molecules. The procedure involves several steps including (a) generation and manipulation of extensive fitting data sets through electronic structure calculations, (b) defining functional forms, (c) formulating novel highly optimized fitting procedures, (d) dual-Hamiltonian optimization to leverage classical FFs with more accurate approaches, and (d) subsequently coding and implementing these algorithms on high performance computers (HPCs). We will also discuss the validation of this approach on several diverse material systems ranging from precious metal nanocatalysts to newly discovered two dimensional materials such as stanene and silicene.

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