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Mitchell A. Wood
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Performance and cost assessment of machine learning interatomic potentials
Y Zuo, C Chen, X Li, Z Deng, Y Chen, J Behler, G Csányi, AV Shapeev, ...
The Journal of Physical Chemistry A 124 (4), 731-745, 2020
5852020
Extending the accuracy of the SNAP interatomic potential form
MA Wood, AP Thompson
The Journal of chemical physics 148 (24), 2018
1802018
Coupled thermal and electromagnetic induced decomposition in the molecular explosive αHMX; a reactive molecular dynamics study
MA Wood, ACT Van Duin, A Strachan
The Journal of Physical Chemistry A 118 (5), 885-895, 2014
1342014
Ultrafast chemistry under nonequilibrium conditions and the shock to deflagration transition at the nanoscale
MA Wood, MJ Cherukara, EM Kober, A Strachan
The Journal of Physical Chemistry C 119 (38), 22008-22015, 2015
1282015
Thermodynamically consistent physics-informed neural networks for hyperbolic systems
RG Patel, I Manickam, NA Trask, MA Wood, M Lee, I Tomas, EC Cyr
Journal of Computational Physics 449, 110754, 2022
1012022
Multiscale modeling of shock wave localization in porous energetic material
MA Wood, DE Kittell, CD Yarrington, AP Thompson
Physical Review B 97 (1), 014109, 2018
982018
A physics-informed operator regression framework for extracting data-driven continuum models
RG Patel, NA Trask, MA Wood, EC Cyr
Computer Methods in Applied Mechanics and Engineering 373, 113500, 2021
872021
Data-driven material models for atomistic simulation
MA Wood, MA Cusentino, BD Wirth, AP Thompson
Physical Review B 99 (18), 184305, 2019
612019
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
482020
Billion atom molecular dynamics simulations of carbon at extreme conditions and experimental time and length scales
K Nguyen-Cong, JT Willman, SG Moore, AB Belonoshko, R Gayatri, ...
Proceedings of the International Conference for High Performance Computing …, 2021
292021
Data-driven magneto-elastic predictions with scalable classical spin-lattice dynamics
S Nikolov, MA Wood, A Cangi, JB Maillet, MC Marinica, AP Thompson, ...
npj Computational Materials 7 (1), 153, 2021
272021
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
262020
Machine learning interatomic potential for simulations of carbon at extreme conditions
JT Willman, K Nguyen-Cong, AS Williams, AB Belonoshko, SG Moore, ...
Physical Review B 106 (18), L180101, 2022
232022
Sub-picosecond to sub-nanosecond vibrational energy transfer dynamics in pentaerythritol tetranitrate
NC Cole-Filipiak, R Knepper, M Wood, K Ramasesha
The Journal of Physical Chemistry Letters 11 (16), 6664-6669, 2020
192020
Training data selection for accuracy and transferability of interatomic potentials
D Montes de Oca Zapiain, MA Wood, N Lubbers, CZ Pereyra, ...
npj Computational Materials 8 (1), 189, 2022
182022
Quantum-accurate molecular dynamics potential for tungsten
MA Wood, AP Thompson
arXiv preprint arXiv:1702.07042, 2017
182017
Nonequilibrium reaction kinetics in molecular solids
MA Wood, A Strachan
The Journal of Physical Chemistry C 120 (1), 542-552, 2016
182016
Molecular dynamics simulations of shock loading of materials: a review and tutorial
MA Wood, MJ Cherukara, E Antillon, A Strachan
Reviews in computational chemistry 30, 43-92, 2017
172017
Efficacy of the radial pair potential approximation for molecular dynamics simulations of dense plasmas
LJ Stanek, RC Clay, MWC Dharma-Wardana, MA Wood, KRC Beckwith, ...
Physics of Plasmas 28 (3), 2021
152021
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
142023
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