FitSNAP: Atomistic machine learning with LAMMPS A Rohskopf, C Sievers, N Lubbers, M Cusentino, J Goff, J Janssen, ... Journal of Open Source Software 8 (84), 5118, 2023 | 22 | 2023 |
Emergence of near-boundary segregation zones in face-centered cubic multiprincipal element alloys MJ McCarthy, H Zheng, D Apelian, WJ Bowman, H Hahn, J Luo, SP Ong, ... Physical Review Materials 5 (11), 113601, 2021 | 16 | 2021 |
Shuffling mode competition leads to directionally anisotropic mobility of faceted Σ11 boundaries in fcc metals MJ McCarthy, TJ Rupert Physical Review Materials 4 (11), 113402, 2020 | 13 | 2020 |
Chemical order transitions within extended interfacial segregation zones in NbMoTaW D Aksoy, MJ McCarthy, I Geiger, D Apelian, H Hahn, EJ Lavernia, J Luo, ... Journal of Applied Physics 132 (23), 2022 | 10 | 2022 |
Machine learned interatomic potential for dispersion strengthened plasma facing components EL Sikorski, MA Cusentino, MJ McCarthy, J Tranchida, MA Wood, ... The Journal of Chemical Physics 158 (11), 2023 | 9 | 2023 |
Emergence of directionally-anisotropic mobility in a faceted Ʃ11⟨ 110⟩ tilt grain boundary in Cu MJ McCarthy, TJ Rupert Modelling and Simulation in Materials Science and Engineering 28 (5), 055008, 2020 | 5 | 2020 |
Alloying induces directionally-dependent mobility and alters migration mechanisms of faceted grain boundaries MJ McCarthy, TJ Rupert Scripta Materialia 194, 113643, 2021 | 4 | 2021 |
Atomic Representations of Local and Global Chemistry in Complex Alloys MJ McCarthy, J Startt, R Dingreville, AP Thompson, MA Wood arXiv preprint arXiv:2303.04311, 2023 | 2 | 2023 |
Dynamic formation of preferentially lattice oriented, self trapped hydrogen clusters MA Cusentino, EL Sikorski, MJ McCarthy, AP Thompson, MA Wood Materials Research Express 10 (10), 106513, 2023 | 1 | 2023 |
Investigating the influence of local composition on properties in complex alloys using machine learned interatomic potentials M McCarthy, J Startt, R Dingreville, A Thompson, M Wood Bulletin of the American Physical Society, 2023 | | 2023 |
Exploring refractory complex concentrated alloy behavior in the fusion reactor environment with a machine-learned interatomic potential. M McCarthy, J Startt, R Dingreville, A Thompson, M Wood Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Machine Learned Interatomic Potential Development of W-ZrC for Fusion Divertor Microstructure and Thermomechanical Properties. E Sikorski, MA Cusentino, M McCarthy, J Tranchida, M Wood, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Molecular Dynamics Modeling of Hydrogen and Nitrogen Implantation in Tungsten Using Machine Learned Interatomic Potentials. MA Cusentino, M McCarthy, E Sikorski, M Wood, A Thompson Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
FitSNAP: Machine Learned Potentials for LAMMPS. A Rohskopf, C Sievers, M McCarthy, J Goff, E Sikorski, A Thompson, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Building a new generation of multiscale materials models with machine-learned interatomic potentials. M McCarthy, A Thompson, M Wood Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Training Machine Learned Interatomic Potentials for Chemical Complexity-Application to Refractory Complex Concentrated Alloys. M McCarthy, J Startt, R Dingreville, M Wood Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Expediting the materials discovery process of MPEAs through atomistic modeling and machine learning techniques. J Startt, M Wood, M McCarthy, A Kustas, S Donegan, R Dingreville Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Local and Near-Boundary Environments in NbMoTaW Refractory Multi-Principal Element Alloy. D Aksoy, M McCarthy, I Geiger, T Rupert Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | | 2021 |