James Chapman
About James Chapman
James Chapman is a Postdoctoral Researcher at Lawrence Livermore National Laboratory, specializing in machine learning interfaces for molecular dynamics. He has contributed to the LAMMPS code and has a strong academic background in Materials Engineering and Physics.
Current Role at Lawrence Livermore National Laboratory
James Chapman has been serving as a Postdoctoral Researcher at Lawrence Livermore National Laboratory since 2020. In this role, he focuses on developing machine learning interfaces for the LAMMPS molecular dynamics code. His contributions include enhancing the nudged elastic band algorithm within the LAMMPS main code. He also conducts research on long time-scale molecular dynamics utilizing machine learning force fields.
Education and Expertise
James Chapman holds a Doctor of Philosophy (PhD) in Materials Engineering from the Georgia Institute of Technology, where he studied from 2018 to 2020. He also earned a Bachelor’s Degree in Physics and Mathematics, graduating Magna Cum Laude from Massachusetts College of Liberal Arts, where he studied from 2011 to 2015. Additionally, he studied Materials Science at the University of Connecticut from 2015 to 2017.
Previous Research Experience
Before his current position, James Chapman worked at the University of Connecticut as a Graduate Research Assistant from 2015 to 2017. He also served as a Chemical Graph Theory Research Assistant at Massachusetts College of Liberal Arts from 2013 to 2015. In 2018, he completed a two-month internship at Lawrence Livermore National Laboratory, focusing on computational chemistry and materials science.
Research Contributions and Publications
James Chapman has published research papers that explore atomistic diffusion mechanisms using density functional theory. His work contributes to the understanding of molecular dynamics and the application of machine learning in this field. He has developed interfaces that enhance computational modeling techniques in materials science.