|About this Abstract
||2017 TMS Annual Meeting & Exhibition
||Computational Materials Discovery and Optimization – From Bulk to Materials Interfaces and 2D Materials
||Design of Experiments Approach to Optimizing Complex Bond Order and Reactive Potentials
||Efrain Hernandez-Rivera, Souma Chowdhury, Mark Tschopp, Shawn Coleman
|On-Site Speaker (Planned)
Molecular dynamics (MD) is a popular approach for understanding fundamental materials' behavior since it can be extended to larger length and time scales than first principles methods. However, MD simulations are adversely limited by the the interatomic potentials' accuracy. Parameterization and optimization of complex potentials can become a severe bottleneck. Furthermore, optimization can become prohibitively expensive for complex potentials that contain hundreds of fitting parameters, e.g. ReaxFF. We have developed a systematic approach that relies on computational experimental designs to overcome these optimization barriers. To counter the expense associated of optimizing large domain spaces, we perform a sensitivity analysis to efficiently identify ``essential'' parameters. With this reduced domain, experimental designs (using LHS) are used to develop surrogate models. These are then employed in multiobjective optimization schemes, which yield optimized domain sets. We validate the surrogate models to assure high fidelity from the resulting optimized parameterizations.
||Definite: None Selected