James Goff

Sandia National Laboratories — United States

Materials Science · Physical Sciences

6h-index115citations21works0.62yr avg
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Research Topics

Machine Learning in Materials Science(10), X-ray Diffraction in Crystallography(5), Electrocatalysts for Energy Conversion(4), Advanced Chemical Physics Studies(3), Supercapacitor Materials and Fabrication(3)

Publications21 total

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations
Computer Physics Communications·2025· 2 citedOpen Access
Materials Learning Algorithms (MALA): Scalable Machine Learning for Electronic Structure Calculations in Large-Scale Atomistic Simulations
arXiv (Cornell University)·2024Open Access
Generalized representative structures for atomistic systems
Journal of Physics Condensed Matter·2024· 1 citedOpen Access
Generalized Representative Structures for Atomistic Systems
arXiv (Cornell University)·2024Open Access
Charge Dependent Atomic Cluster Expansions
2024Open Access
Exploring model complexity in machine learned potentials for simulated properties
Journal of materials research/Pratt's guide to venture capital sources·2023· 10 citedOpen Access
Machine-learned ACE models with charge equilibration in LAMMPS (workshop)
2023Open Access
Recent Developments in Machine Learning Interatomic Potentials for Molecular Dynamics
2023Open Access
Shadow Molecular Dynamics and Atomic Cluster Expansions for Flexible Charge Models
Journal of Chemical Theory and Computation·2023· 8 citedOpen Access
Atomistic modeling of plasma material interactions using SNAP machine learned interatomic potentials
2023Open Access
FitSNAP: Atomistic machine learning with LAMMPS
The Journal of Open Source Software·2023· 46 citedOpen Access
Shadow molecular dynamics and atomic cluster expansions for flexible charge models
2023Open Access
Direct Laser Writing of Multimetal Bifunctional Catalysts for Overall Water Splitting
ACS Applied Energy Materials·2023· 11 citedOpen Access
FitSNAP: Machine Learned Potentials for LAMMPS.
2022Open Access
Quantifying multipoint ordering in alloys
Physical review. B./Physical review. B·2021Open Access
Single-Step Direct Laser Writing of Multimetal Oxygen Evolution Catalysts from Liquid Precursors
ACS Nano·2021· 21 citedOpen Access
Predicting the Pseudocapacitive Windows for MXene Electrodes with Voltage-Dependent Cluster Expansion Models
ACS Applied Energy Materials·2021· 1 citedOpen Access
Probing Pseudocapacitive response of MXene electrodes for energy storage from first principles
Bulletin of the American Physical Society·2020
Effects of surface charge and cluster size on the electrochemical dissolution of platinum nanoparticles using COMB3 and continuum electrolyte models
The Journal of Chemical Physics·2020· 4 citedOpen Access
MXene Electrode Materials for Electrochemical Energy Storage: First-Principles and Grand Canonical Monte Carlo Simulations
MRS Advances·2019· 11 cited
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Frequent Co-authors

Andrew Rohskopf(9), Mitchell Wood(7), Ismaïla Dabo(7), Aidan P. Thompson(6), Megan McCarthy(4), Susan B. Sinnott(4), Mary Alice Cusentino(3), Yasuaki Okada(3), Nathan Keilbart(3), Dionysios Sema(2), Ember Sikorski(2), Shannon McGee(2), Yu Lei(2), Nabila Nabi Nova(2), Mauricio Terrones(2), Lauren D. Zarzar(2), Kosuke Shiratsuyu(2), Yu Zhang(2), Anders M. N. Niklasson(2), Attila Cangi(2)