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Publication	Type	Year
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
Multiscale modeling of CL20 and HNS ? Atomistic to Continuum JOWOG 9 Energetic Materials Plenary Meeting 2022 David Lee Damm, James Allen Stewart, Robert Knepper, Mitchell Wood, Judith Alice Brown, Julia Marilyn Hartig, Michael Neil Sakano	Abstract – 2022 Abstract	2022
Representations and Models of Substitutional Atomic Systems: Applications to Clean Energy (abstract) Colorado Mesa University Physics Seminar James Michael Goff, Mitchell Wood, Aidan P. Thompson	Abstract – 2022 Abstract	2022
Evaluating microstructure features for shock sensitivity at the mesoscale 22nd Biennial Conference of the APS Topical Group on Shock Compression of Condensed Matter Judith Alice Brown, Michael Neil Sakano, Julia Marilyn Hartig, Dan Stefan Bolintineanu, Mitchell Wood	Abstract – 2022 Abstract	2022
Data Mining the Mesoscale to Study Shock Ignition and Reaction Growth in Pressed Energetic Materials TMS 2022 Annual Meeting and Exhibition Judith Alice Brown, Julia Marilyn Hartig, Michael Neil Sakano, Dan Stefan Bolintineanu, Mitchell Wood	Conference Presentation – 2022 Conference Presentation	2022
Molecular Dynamics Simulations of Hydrogen and Nitrogen Implantation in Tungsten TMS Annual Meeting Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson	Conference Poster – 2022 Conference Poster	2022
Elucidating size effects on the yield strength of single-crystal Cu via the Richtmyer-Meshkov instability Journal of Applied Physics James Allen Stewart, Mitchell Wood, Joseph Olles	Journal Article – 2022 Journal Article	2022
Interatomic Potentials for Materials Science and Beyond; Advances in Machine Learned Spectral Neighborhood Analysis Potentials TMS Annual Meeting (Virtual) Mitchell Wood, Mary Alice Cusentino, Ivan Oleynik, Aidan P. Thompson	Conference Presentation – 2022 Conference Presentation	2022
Scalable Solutions for Training Machine Learned Interatomic Potentials American Physical Society Mitchell Wood, Charles Andrew Sievers, Danny Perez, Nicholas Lubbers, Aidan P. Thompson	Conference Presentation – 2022 Conference Presentation	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
Training Atomic Cluster Expansion Potentials using LAMMPS and FitSNAP APS March Meeting 2022 James Michael Goff, Mitchell Wood, Aidan P. Thompson	Conference Presentation – 2022 Conference Presentation	2022
Data-driven Magnetic Materials Modeling; Advances in Classical Molecular Dynamics 2022 TMS Annual Meeting & Exhibition Svetoslav Valeriev Nikolov, Julien Tranchida, Aidan P. Thompson, Mitchell Wood	Conference Presentation – 2022 Conference Presentation	2022
Scalable Solutions for Training Machine Learned Interatomic Potentials American Physical Society March Meeting Mitchell Wood, Charles Andrew Sievers, Danny Perez, Nicholas Lubbers, Aidan P. Thompson	Conference Presentation – 2022 Conference Presentation	2022
Probing Structural and Magnetic Phase Changes in the Shock Response of Iron with Molecular Dynamics APS March Meeting Svetoslav Valeriev Nikolov, Julien Tranchida, Attila Cangi, Kushal Ramakrishna, Mani Lokamani, Mitchell Wood	Conference Presentation – 2022 Conference Presentation	2022
Machine Learned Interatomic Potential Development for W-ZrC American Physical Society March Meeting Ember Layne Sikorski, Julien Tranchida, Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson	Conference Presentation – 2022 Conference Presentation	2022
Development of SNAP Interatomic Potentials for Gas-Metal Interactions for Fusion Energy Materials APS March Meeting Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson	Conference Presentation – 2022 Conference Presentation	2022
Development of Predictive Multiscale Constitutive Models for Pressed Energetic Materials to Resolve the Shock to Detonation Transition APS March Meeting 2022 Michael Neil Sakano, Judith Alice Brown, Mitchell Wood	Conference Presentation – 2022 Conference Presentation	2022
Dissociating the phononic, magnetic and electronic contributions to thermal conductivity: a computational study in alpha-iron The Journal of Materials Science Svetoslav Valeriev Nikolov, Julien Tranchida, Kushal Ramakrishna, Mani Lokamani, Attila Cangi, Mitchell Wood	Journal Article – 2021 Journal Article	2021
Development of SNAP potential for ZrC strengthened W 25th International Conference on Plasma Surface Interaction Ember Layne Sikorski, Julien Tranchida, Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson	Abstract – 2021 Abstract	2021
How nitrogen affects hydrogen adsorption on tungsten surfaces 25th International Conference on Plasma Surface Interactions in Controlled Fusion Devices Chun-Shang Wong, Robert Kolasinski, Josh A. Whaley, Mary Alice Cusentino, Mitchell Wood, Brian Wirth, Aidan P. Thompson	Abstract – 2021 Abstract	2021
Development of SNAP Potentials for Molecular Dynamics Modeling of Hydrogen and Nitrogen Interactions in Tungsten 25th International Conference on Plasma Surface Interactions in Controlled Fusion Devices Mary Alice Cusentino, Mitchell Wood, Aidan P. Thompson	Abstract – 2021 Abstract	2021
Document Title	Type	Year

Results 26–50 of 153

Publications

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

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

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

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

Multiscale modeling of CL20 and HNS ? Atomistic to Continuum

Representations and Models of Substitutional Atomic Systems: Applications to Clean Energy (abstract)

Evaluating microstructure features for shock sensitivity at the mesoscale

Data Mining the Mesoscale to Study Shock Ignition and Reaction Growth in Pressed Energetic Materials

Molecular Dynamics Simulations of Hydrogen and Nitrogen Implantation in Tungsten

Elucidating size effects on the yield strength of single-crystal Cu via the Richtmyer-Meshkov instability

Interatomic Potentials for Materials Science and Beyond; Advances in Machine Learned Spectral Neighborhood Analysis Potentials

Scalable Solutions for Training Machine Learned Interatomic Potentials

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

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

Training Atomic Cluster Expansion Potentials using LAMMPS and FitSNAP

Data-driven Magnetic Materials Modeling; Advances in Classical Molecular Dynamics

Scalable Solutions for Training Machine Learned Interatomic Potentials

Probing Structural and Magnetic Phase Changes in the Shock Response of Iron with Molecular Dynamics

Machine Learned Interatomic Potential Development for W-ZrC

Development of SNAP Interatomic Potentials for Gas-Metal Interactions for Fusion Energy Materials

Development of Predictive Multiscale Constitutive Models for Pressed Energetic Materials to Resolve the Shock to Detonation Transition

Dissociating the phononic, magnetic and electronic contributions to thermal conductivity: a computational study in alpha-iron

Development of SNAP potential for ZrC strengthened W

How nitrogen affects hydrogen adsorption on tungsten surfaces

Development of SNAP Potentials for Molecular Dynamics Modeling of Hydrogen and Nitrogen Interactions in Tungsten