Publications

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Training Machine Learned Interatomic Potentials for Chemical Complexity - Application to Refractory Complex Concentrated Alloys

Gordon Research Conference - Computational Materials Science and Engineering

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Mitchell Wood

Conference Poster – 2022 Conference Poster 2022

FitSNAP: Machine Learned Potentials for LAMMPS

Gordon Research Conference (Computational Materials Science and Engineering)

Andrew Dale Rohskopf, Charlie Sievers, Megan Jeanne McCarthy, James Michael Goff, Ember Layne Sikorski, Aidan P. Thompson, Mitchell Wood

Conference Poster – 2022 Conference Poster 2022

Machine-Learned Interatomic Potential Development for W-ZrC for Nuclear Fusion

Gordon Research ConferenceComputational Materials Science and Engineering

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Conference Poster – 2022 Conference Poster 2022

Training Machine Learned Interatomic Potentials for Chemical Complexity - Application to Refractory CCAs

The Minerals, Metals, and Materials Society (TMS) 2023 Annual Meeting and Exhibition

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Aidan P. Thompson, Mitchell Wood

Abstract – 2022 Abstract 2022

Building a new generation of multiscale materials models with machine-learned interatomic potentials

Machine Learning Deep Learning Workshop

Megan Jeanne McCarthy, Aidan P. Thompson, Mitchell Wood

Conference Presentation – 2022 Conference Presentation 2022

Machine-Learned Interatomic Potential Development for H Trapping in ZrC strengthened W

Tms 2023

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Abstract – 2022 Abstract 2022

Molecular Dynamics Simulations of Mixed Materials Effects in Tungsten

Tms 2023

Mary Alice Cusentino, Megan Jeanne McCarthy, Ember Layne Sikorski, Mitchell Wood, Aidan P. Thompson

Abstract – 2022 Abstract 2022

Exploring refractory complex concentrated alloy behavior in the fusion reactor environment with a machine-learned interatomic potential

PSI-2525th International Conference on Plasma Surface Interaction in Controlled Fusion Devices

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Mitchell Wood

Conference Presentation – 2022 Conference Presentation 2022

Machine-Learned Interatomic Potential Development for W-ZrC for Nuclear Fusion

Gordon Research ConferenceComputational Materials Science and Engineering

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Abstract – 2022 Abstract 2022

Machine Learned Interatomic Potential Development of W-ZrC for Fusion Divertor Microstructure and Thermomechanical Properties

Multiscale Materials Modeling

Ember Layne Sikorski, Mary Alice Cusentino, Megan Jeanne McCarthy, Julien Tranchida, Mitchell Wood, Aidan P. Thompson

Abstract – 2022 Abstract 2022

Training Machine Learned Interatomic Potentials for Chemical Complexity - Application to Refractory CCAs

Gordon Research Conference - Computational Materials Science and Engineering

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Aidan P. Thompson, Mitchell Wood

Abstract – 2022 Abstract 2022

Exploring the behavior of MoNbTaTi refractory CCAs across composition space using a machine learned interatomic potential

The 10th International Conference on Multiscale Materials Modeling

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Aidan P. Thompson, Mitchell Wood

Abstract – 2022 Abstract 2022

Molecular Dynamics Modeling of Hydrogen and Nitrogen Implantation in Tungsten Using Machine Learned Interatomic Potentials

The 10th International Conference on Multiscale Materials Modeling

Mary Alice Cusentino, Megan Jeanne McCarthy, Ember Layne Sikorski, Mitchell Wood, Aidan P. Thompson

Abstract – 2022 Abstract 2022

Training Machine Learned Interatomic Potentials for Chemical Complexity - Application to Refractory CCAs

APS March Meeting 2022

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Mitchell Wood

Conference Presentation – 2022 Conference Presentation 2022

Expediting the materials discovery process of MPEAs through atomistic modeling and machine learning techniques

TMS 2022 Annual Meeting & Exhibition

Jacob Kyle Startt, Mitchell Wood, Megan Jeanne McCarthy, Andrew Kustas, Sean Donegan, Remi Philippe Michel Dingreville

Conference Presentation – 2022 Conference Presentation 2022

Local and Near-Boundary Environments in NbMoTaW Refractory Multi-Principal Element Alloy

2nd World Congress on High Entropy Alloys (HEA 2021)

Doruk Aksoy, Megan Jeanne McCarthy, Ian Geiger, Timothy Rupert

Conference Presentation – 2021 Conference Presentation 2021

Exploring refractory complex concentrated alloy behavior in the fusion reactor environment with a machine-learned interatomic potential

PSI-25 25th International Conference on Plasma Surface

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Mitchell Wood, Aidan P. Thompson

Abstract – 2021 Abstract 2021

Training Machine Learned Interatomic Potentials for Chemical Complexity - Application to Refractory CCAs

American Physical Society, March Meeting 2021

Megan Jeanne McCarthy, Jacob Kyle Startt, Remi Philippe Michel Dingreville, Mitchell Wood

Abstract – 2021 Abstract 2021
Document Title Type Year