Mary Alice Cusentino

Sandia National Laboratories — United States

Materials Science · Physical Sciences

9h-index386citations64works0.82yr avg
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Research Topics

Fusion materials and technologies(29), Nuclear Materials and Properties(25), Machine Learning in Materials Science(14), Advanced materials and composites(12), Advanced Materials Characterization Techniques(10)

Publications64 total

The effect of composition on helium bubble nucleation in complex concentrated alloys
Journal of Applied Physics·2025· 1 citedOpen Access
Compositionally-driven surface nanostructuring on refractory compositionally complex alloys under low energy helium bombardment
Nuclear Materials and Energy·2025Open Access
Advancing Multiscale Simulation of Plasma-Surface Interfaces
2025
The Role of Composition on Radiation Tolerance of Multicomponent Alloys for Plasma-Facing Materials
2024Open Access
Development of Machine Learned Interatomic Potentials for Modeling Plasma-Material Interactions
2024Open Access
Development of multi-scale computational frameworks to solve fusion materials science challenges
Journal of Nuclear Materials·2024· 4 citedOpen Access
Large-scale Quantum-accurate Atomistic Simulation of Plasma-facing Materials for Fusion Energy
2024Open Access
Assessment of the literature about Be-W mixed material layer formation in the fusion reactor environment
2024Open Access
Assessment of the literature about Be-W mixed material layer formation in the fusion reactor environment
Materials Research Express·2024· 2 citedOpen Access
Dynamic formation of preferentially lattice oriented, self trapped hydrogen clusters
Materials Research Express·2023· 3 citedOpen Access
Developing machine learned potentials for high temperature applications
2023Open Access
Dynamic Formation of Preferentially Lattice Oriented, Self Trapped Hydrogen Clusters
arXiv (Cornell University)·2023Open Access
Recent Developments in Machine Learning Interatomic Potentials for Molecular Dynamics
2023Open Access
Development of Machine Learned Interatomic Potentials for Modeling the Effect of Mixed Material Layers on Hydrogen Retention
2023Open Access
Atomistic modeling of plasma material interactions using SNAP machine learned interatomic potentials
2023Open Access
FitSNAP: Atomistic machine learning with LAMMPS
The Journal of Open Source Software·2023· 46 citedOpen Access
Machine learned interatomic potential for dispersion strengthened plasma facing components
The Journal of Chemical Physics·2023· 19 citedOpen Access
Machine-learned Interatomic Potential Development for H Trapping in ZrC Strengthened W
2023Open Access
Molecular dynamics of high pressure tin phases: Empirical and machine learned interatomic potentials
AIP conference proceedings·2023· 1 cited
Machine Learned Interatomic Potential for Dispersion Strengthened Plasma Facing Components
arXiv (Cornell University)·2022Open Access
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Frequent Co-authors

Mitchell Wood(29), Aidan P. Thompson(16), Megan McCarthy(15), Aidan Thompson(13), Brian D. Wirth(9), Ember Sikorski(6), Julien Tranchida(4), Ember Salas(4), Andrew Rohskopf(3), James Goff(3), Danny Pérez(3), Blas P. Uberuaga(3), Benjamin Nebgen(3), Kipton Barros(3), John D. Shimanek(3), Alice E. A. Allen(3), Saryu Fensin(3), J. Matthew D. Lane(3), E. Salas(3), A. Lasa(2)