| Data-driven material models for atomistic simulation MA Wood, MA Cusentino, BD Wirth, AP Thompson Physical Review B 99 (18), 184305, 2019 | 61 | 2019 |
| Explicit multielement extension of the spectral neighbor analysis potential for chemically complex systems MA Cusentino, MA Wood, AP Thompson The Journal of Physical Chemistry A 124 (26), 5456-5464, 2020 | 49 | 2020 |
| A molecular dynamics study of subsurface hydrogen-helium bubbles in tungsten ZJ Bergstrom, MA Cusentino, BD Wirth Fusion Science and Technology 71 (1), 122-135, 2017 | 39 | 2017 |
| Molecular statics calculations of the biases and point defect capture volumes of small cavities AA Kohnert, MA Cusentino, BD Wirth Journal of Nuclear Materials 499, 480-489, 2018 | 29 | 2018 |
| A comparison of interatomic potentials for modeling tungsten–hydrogen–helium plasma–surface interactions MA Cusentino, KD Hammond, F Sefta, N Juslin, BD Wirth Journal of Nuclear Materials 463, 347-350, 2015 | 29 | 2015 |
| Compositional and structural origins of radiation damage mitigation in high-entropy alloys MA Cusentino, MA Wood, R Dingreville Journal of Applied Physics 128 (12), 2020 | 26 | 2020 |
| 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 | 14 | 2023 |
| Suppression of helium bubble nucleation in beryllium exposed tungsten surfaces MA Cusentino, MA Wood, AP Thompson Nuclear Fusion 60 (12), 126018, 2020 | 8 | 2020 |
| 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 | 7 | 2023 |
| Beryllium-driven structural evolution at the divertor surface MA Cusentino, MA Wood, AP Thompson Nuclear fusion 61 (4), 046049, 2021 | 7 | 2021 |
| Helium diffusion and bubble evolution in tungsten nanotendrils MA Cusentino, BD Wirth Computational Materials Science 183, 109875, 2020 | 6 | 2020 |
| Discovering key unknowns for tungsten-hydrogen-helium plasma material interactions using molecular dynamics MA Cusentino | 2 | 2018 |
| Assessment of the literature about Be-W mixed material layer formation in the fusion reactor environment A Lasa, D Dasgupta, MJ Baldwin, MA Cusentino, P Hatton, D Perez, ... Materials Research Express, 2024 | 1 | 2024 |
| 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 |
| Development of multi-scale computational frameworks to solve fusion materials science challenges A Lasa, S Blondel, MA Cusentino, D Dasgupta, P Hatton, J Marian, ... Journal of Nuclear Materials 594, 155011, 2024 | | 2024 |
| Large-scale quantum-accurate atomistic simulation of plasma-facing materials for fusion energy MA Cusentino Bulletin of the American Physical Society, 2024 | | 2024 |
| Molecular dynamics of high pressure tin phases: Empirical and machine learned interatomic potentials MA Cusentino, B Nebgen, KM Barros, JS Smith, JD Shimanek, A Allen, ... AIP Conference Proceedings 2844 (1), 2023 | | 2023 |
| 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 |
| 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 of High Pressure Tin Phases II: Machine Learned Interatomic Potential Development. MA Cusentino, B Nebgen, KM Barros, JD Shimanek, A Allen, A Thompson, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
