Follow
Megan J. McCarthy
Title
Cited by
Cited by
Year
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
142021
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
122020
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
82023
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
62022
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
52023
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
52020
Alloying induces directionally-dependent mobility and alters migration mechanisms of faceted grain boundaries
MJ McCarthy, TJ Rupert
Scripta Materialia 194, 113643, 2021
32021
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
2023
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
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
The system can't perform the operation now. Try again later.
Articles 1–18