collaborators

6 papers

cond-mat.mtrl-sci2026

Atomistic modeling of uranium monocarbide with a machine learning interatomic potential

Lorena Alzate-Vargas, Kashi N. Subedi, Roxanne M. Tutchton +3

Uranium monocarbide (UC) is an advanced ceramic fuel candidate due to its superior uranium density and thermal conductivity compared to traditional fuels. To accurately model UC at…

cond-mat.mtrl-sci2026

Going beyond density functional theory accuracy: Leveraging experimental data to refine pre-trained machine learning interatomic potentials

Shriya Gumber, Lorena Alzate-Vargas, Benjamin T. Nebgen +4

Machine learning interatomic potentials (MLIPs) are inherently limited by the accuracy of the training data, usually consisting of energies and forces obtained from quantum mechani…

physics.comp-ph2025

Multi-fidelity learning for interatomic potentials: Low-level forces and high-level energies are all you need

Mitchell Messerly, Sakib Matin, Alice E. A. Allen +5

The promise of machine learning interatomic potentials (MLIPs) has led to an abundance of public quantum mechanical (QM) training datasets. The quality of an MLIP is directly limit…

physics.chem-ph2025

Reactive Chemistry at Unrestricted Coupled Cluster Level: High-throughput Calculations for Training Machine Learning Potentials

Alice E. A. Allen, Rui Li, Sakib Matin +8

Accurately modeling chemical reactions at the atomistic level requires high-level electronic structure theory due to the presence of unpaired electrons and the need to properly des…

physics.chem-ph2025

Teacher-student training improves accuracy and efficiency of machine learning interatomic potentials

Sakib Matin, Alice E. A. Allen, Emily Shinkle +9

Machine learning interatomic potentials (MLIPs) are revolutionizing the field of molecular dynamics (MD) simulations. Recent MLIPs have tended towards more complex architectures tr…

cond-mat.mtrl-sci2025

Toward machine learning interatomic potentials for modeling uranium mononitride

Lorena Alzate-Vargas, Kashi N. Subedi, Nicholas Lubbers +4

Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine lear…