Publications

Training Data Selection for Accuracy and Transferability of Interatomic Potentials

npj Computational Materials

David Montes de Oca Zapiain, Mitchell Wood, Nicholas Lubbers, Carlos Z. Pereyra, Aidan P. Thompson, Danny Perez4

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

James Michael Goff, Charles Sievers, Mitchell Wood, Aidan P. Thompson

https://www.osti.gov/search/identifier:1879613

FitSNAP: Machine Learned Potentials for LAMMPS

Gordon Research Conference (Computational Materials Science and Engineering)

Andrew Dale Rohskopf, Charlie Sievers, Megan Jeanne McCarthy, James Michael Goff, Ember Layne Sikorski, Aidan P. Thompson, Mitchell Wood

Large-Scale Atomistic Simulations Investigate Expansion of Molten Metal 

Stan Gerald Moore, Mitchell Wood, Aidan P. Thompson

Permutation-Adapted Atomic Cluster Expansion Models

Gordon Research Conference on Comparing Theories, Algorithms and Computation Protocols in Materials Science and Engineering

James Michael Goff, Mitchell Wood, Aidan P. Thompson, Charles Sievers

Machine-Learned Interatomic Potential Development for W-ZrC for Nuclear Fusion

Gordon Research ConferenceComputational Materials Science and Engineering

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Sandia Update on SNAP Potential Development for Mixed Materials at the Divertor Surface

SciDAC-PSI Project Meeting

Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson

Molecular Dynamics of High Pressure Tin Phases I: Strength and deformation evaluations of empirical potentials

APS SCCM Conference

James Matthew Doyle Lane, Mary Alice Cusentino, Ben NebgenBen Nebgen, Kipton M Barros, John Shimanek, Alice Allen, Aidan P. Thompson, Saryu Fensin

Molecular Dynamics of High Pressure Tin Phases II: Machine Learned Interatomic Potential Development

22nd Biennial Conference of the APS Topical Group on Shock Compression of Condensed Matter

Mary Alice Cusentino, Ben Nebgen, Kipton M. Barros, John D. Shimanek, Alice Allen, Aidan P. Thompson, Saryu J. Fensin, James Matthew Doyle Lane

Training Machine Learned Interatomic Potentials for Chemical Complexity - Application to Refractory CCAs

The Minerals, Metals, and Materials Society (TMS) 2023 Annual Meeting and Exhibition

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Aidan P. Thompson, Mitchell Wood

Building a new generation of multiscale materials models with machine-learned interatomic potentials

Machine Learning Deep Learning Workshop

Megan Jeanne McCarthy, Aidan P. Thompson, Mitchell Wood

Machine-Learned Interatomic Potential Development for H Trapping in ZrC strengthened W

Tms 2023

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Molecular Dynamics Simulations of Mixed Materials Effects in Tungsten

Tms 2023

Mary Alice Cusentino, Megan Jeanne McCarthy, Ember Layne Sikorski, Mitchell Wood, Aidan P. Thompson

How nitrogen affects hydrogen adsorption on tungsten surfaces

25th International Conference on Plasma Surface Interactions in Controlled Fusion Devices

Chun-Shang Wong, Robert Kolasinski, Josh Whaley, Mary Alice Cusentino, Mitchell Wood, Brian Wirth, Aidan P. Thompson

Development of SNAP potential for ZrC strengthened W

25th International Conference on Plasma Surface Interaction in Controlled Fusion Devices

Ember Layne Sikorski, Julien Tranchida, Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson

Development of SNAP Potentials for Molecular Dynamics Modeling of Hydrogen and Nitrogen Interactions in Tungsten

25th International Conference on Plasma Surface Interaction in Controlled Fusion Devices

Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson

A machine learning surrogate for density functional theory based on the local density of state

2022 Workshop on Recent Developments in Electronic Structure (ES22)

Normand A. Modine, Lenz Fiedler, Dayton Jonathan Vogel, Aidan P. Thompson, Austin Ellis, John Adam Stephens, Gabe Popoola, Attila Cangi, Sivasankaran Rajamanickam

LAMMPS - A flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

Computer Physics Communications

Aidan P. Thompson, Metin Aktulga, Richard Berger, Dan Stefan Bolintineanu, Michael W. Brown, Paul Crozier, Pieter J. in't Veld, Axel Kohlmeyer, Stan Gerald Moore, Trung Nguyen, Tzu-ray Shan, Mark J. Stevens, Julien Tranchida, Christian Robert Trott, Steven J. Plimpton

https://www.osti.gov/search/identifier:1872034

A machine learning surrogate for density functional theory based on the local density of states

2022 Workshop on Recent Developments in Electronic Structure (ES22)

Normand A. Modine, Lenz Fiedler, Dayton Jonathan Vogel, Aidan P. Thompson, Austin Ellis, John Adam Stephens, Gabe Popoola, Attila Cangi, Sivasankaran Rajamanickam

Machine-Learned Interatomic Potential Development for W-ZrC for Nuclear Fusion

Gordon Research ConferenceComputational Materials Science and Engineering

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Machine Learned Interatomic Potential Development of W-ZrC for Fusion Divertor Microstructure and Thermomechanical Properties

Multiscale Materials Modeling

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Training Machine Learned Interatomic Potentials for Chemical Complexity - Application to Refractory CCAs

Gordon Research Conference - Computational Materials Science and Engineering

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Aidan P. Thompson, Mitchell Wood

Exploring the behavior of MoNbTaTi refractory CCAs across composition space using a machine learned interatomic potential

The 10th International Conference on Multiscale Materials Modeling

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Aidan P. Thompson, Mitchell Wood

Molecular Dynamics Modeling of Hydrogen and Nitrogen Implantation in Tungsten Using Machine Learned Interatomic Potentials

The 10th International Conference on Multiscale Materials Modeling

Mary Alice Cusentino, Megan Jeanne McCarthy, Ember Layne Sikorski, Mitchell Wood, Aidan P. Thompson

Representations and Models of Substitutional Atomic Systems: Applications to Clean Energy (abstract)

Colorado Mesa University Physics Seminar

James Michael Goff, Mitchell Wood, Aidan P. Thompson