|About this Abstract
||2017 TMS Annual Meeting & Exhibition
||Computational Methods and Experimental Approaches for Uncertainty Quantification and Propagation, Model Validation, and Stochastic Predictions
||Advancements in Parameterization and Validation of Empirical Potentials
||Tao Liang, Kamal Choudhary, Susan B Sinnott
|On-Site Speaker (Planned)
Molecular dynamics (MD) simulations are often used in conjunction with experimental data, theory, and simulations at other length scales to address problems in materials science and engineering. The most challenging question that MD simulations have faced is: “What is the confidence level associated with the simulation predictions?” The answer to this requires improvement in the transferability of empirical potentials as well as developing the toolbox to quantify the uncertainty of these potentials. Coupling classical MD simulations with existing materials databases and cyberinfrastructures, we are building a toolbox to validate the potentials that are available in LAMMPS. In particular, we have started with validating selected compounds, such as Al2O3, and molecules, such as of hydrocarbons. The results are used to identify the origin of errors associated with the empirical potentials and to propose solutions to ultimately improve the transferability and design of empirical potentials.