| FitSNAP: Atomistic machine learning with LAMMPS A Rohskopf, C Sievers, N Lubbers, MA Cusentino, J Goff, J Janssen, ... Journal of Open Source Software 8 (84), 5118, 2023 | 56 | 2023 |
| Single-step direct laser writing of multimetal oxygen evolution catalysts from liquid precursors S McGee, Y Lei, J Goff, CJ Wilkinson, NN Nova, CM Kindle, F Zhang, ... ACS nano 15 (6), 9796-9807, 2021 | 19 | 2021 |
| Predicting the pseudocapacitive windows for MXene electrodes with voltage-dependent cluster expansion models JM Goff, F Marques dos Santos Vieira, ND Keilbart, Y Okada, I Dabo ACS Applied Energy Materials 4 (4), 3151-3159, 2021 | 17 | 2021 |
| MXene electrode materials for electrochemical energy storage: First-principles and grand canonical Monte Carlo Simulations Y Okada, N Keilbart, JM Goff, S Higai, K Shiratsuyu, I Dabo MRS Advances 4 (33-34), 1833-1841, 2019 | 14 | 2019 |
| Permutation-adapted complete and independent basis for atomic cluster expansion descriptors JM Goff, C Sievers, MA Wood, AP Thompson Journal of Computational Physics 510, 113073, 2024 | 11 | 2024 |
| Exploring model complexity in machine learned potentials for simulated properties A Rohskopf, J Goff, D Sema, K Gordiz, NC Nguyen, A Henry, ... Journal of Materials Research 38 (24), 5136-5150, 2023 | 10 | 2023 |
| Shadow molecular dynamics and atomic cluster expansions for flexible charge models J Goff, Y Zhang, C Negre, A Rohskopf, AMN Niklasson Journal of chemical theory and computation 19 (13), 4255-4272, 2023 | 10 | 2023 |
| Direct laser writing of multimetal bifunctional catalysts for overall water splitting S McGee, A Fest, C Chandler, NN Nova, Y Lei, J Goff, SB Sinnott, I Dabo, ... ACS Applied Energy Materials 6 (7), 3756-3768, 2023 | 7 | 2023 |
| Quantifying multipoint ordering in alloys JM Goff, BY Li, SB Sinnott, I Dabo Physical Review B 104 (5), 054109, 2021 | 7 | 2021 |
| Effects of surface charge and cluster size on the electrochemical dissolution of platinum nanoparticles using COMB3 and continuum electrolyte models JM Goff, SB Sinnott, I Dabo The Journal of Chemical Physics 152 (6), 2020 | 6 | 2020 |
| Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations A Cangi, L Fiedler, B Brzoza, K Shah, TJ Callow, D Kotik, S Schmerler, ... Computer Physics Communications, 109654, 2025 | 5 | 2025 |
| Generalized representative structures for atomistic systems JM Goff, C Mullen, S Yang, ON Starovoytov, MA Wood Journal of Physics: Condensed Matter 37 (7), 075901, 2024 | 2 | 2024 |
| Modeling and experimentation of imperfections in materials W Xu, CLA Leung, M Malaki, E Guo, Y Yang, JM Goff Frontiers in Materials 11, 1473420, 2024 | 1 | 2024 |
| Progress Towards a Quantum-Accurate Classical SNAP ML Interaction Potential for Gold T Boese, I Anderson, J Schiffbauer, J Goff Bulletin of the American Physical Society, 2025 | | 2025 |
| Transforming Legacy Equation of State Databases into Interatomic Potentials via Machine Learning ES Salas, S Moore, JM Goff, MJ McCarthy, MK Lentz, NA Modine, ... SCCM 2025, 2025 | | 2025 |
| Data Standards for Machine Learned Interatomic Potentials of Plasma Facing Materials MA Wood, JM Goff SMT 2025, 2025 | | 2025 |
| Tuning the electrocatalytic perfomance of mixed transition-metal hydroxides for hydrogen production C Chandler, S McGee, A Fest, N Nova, Y Lei, J Goff, S Sinnott, I Dabo, ... Bulletin of the American Physical Society, 2024 | | 2024 |
| Charge Dependent Atomic Cluster Expansions JM Goff Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States), 2024 | | 2024 |
| Machine-learned ACE models with charge equilibration in LAMMPS (workshop) JM Goff Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States), 2023 | | 2023 |
| Recent Developments in Machine Learning Interatomic Potentials for Molecular Dynamics ES Salas, AD Rohskopf, JM Goff, MJ McCarthy, MA Cusentino, MA Wood, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2023 | | 2023 |
