Presenter(s)

Aaron Winget

Comments

Presentation: 1:15-2:30 p.m., Kennedy Union Ballroom

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Description

Molecular simulations can be used to gain a better understanding of the exact mechanisms of many physical and chemical reactions. As such, it is important that these simulations be based on models that are as accurate as possible. Unfortunately, the rare earth series of elements are difficult to model due to many of their forcefield parameters being unknown or otherwise inaccurate. This work explores finding these parameters utilizing intelligent Bayesian optimization. Rather than a linear “guess-and-check” search pattern, Bayesian optimization utilizes parallel search patterns to search many potential points simultaneously. As such, search time is drastically reduced, and the parallel nature of the optimization allows for parameters of different elements to be discovered concurrently.

Publication Date

4-19-2023

Project Designation

Graduate Research

Primary Advisor

Kevin Hinkle

Primary Advisor's Department

Chemical and Materials Engineering

Keywords

Stander Symposium, School of Engineering

Institutional Learning Goals

Scholarship

Intelligent Algorithms for the Optimization of Rare-Earth Metal Cation Forcefield Parameters

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