Quantum-accurate multiscale modeling in highly compressed metals  

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Lasers are used to align diagnostics and hardware prior to shooting on Sandia’s Z machine, the world’s most powerful and efficient laboratory radiation source.

The development of equations-of-state and transport models in areas such as shock compression and fusion energy science is critical to DOE programs. Notable shortcomings in these activities are phase transitions in highly compressed metals. Fully characterizing high energy density phenomena using pulsed power facilities is possible only with complementary numerical modeling for design, diagnostics, and data interpretation.  

This team constructed a multiscale simulation framework based on a combination of high-fidelity electronic structure data, ML, and molecular dynamics enabling quantum-accurate, computationally efficient predictions. This provides kinetics of magneto-structural phase transitions along shock Hugoniots and ramp compression paths in the equations of state, and transport properties such as viscosity, electrical and thermal conductivities. Findings from this project were published in the Journal of Material Science and npj Computational Materials. 

Sandia researchers linked to work 

  • Mitchell Wood  
  • Julien Tranchida 
  • Michael Desjarlais 

Sponsored by 

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Associated Publications

  • Goff, J.M., Sievers, C., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2024). Permutation-adapted complete and independent basis for atomic cluster expansion descriptors. Journal of Computational Physics. https://doi.org/10.2172/1879613 Publication ID: 80036
  • Dingreville, R.P.M., Startt, J.K., Wood, M.A., McCarthy, M.J., Donegan, S., & Donegan, S. (2024). Bayesian blacksmithing: discovering thermomechanical properties and deformation mechanisms in high-entropy refractory alloys. npj Computational Materials, 10(1). https://doi.org/10.1038/s41524-024-01353-z Publication ID: 124980
  • Cusentino, M.A., Bachman, W.B., McCarthy, M.J., Thompson, A.P., Wood, M.A., & Wood, M.A. (2023). Dynamic formation of preferentially lattice oriented, self trapped hydrogen clusters. Materials Research Express (Online), 10(10). https://doi.org/10.1088/2053-1591/acfae7 Publication ID: 122404
  • Nikolov, S.V., Carpenter, J.H., Wood, M.A., Tranchida, J., Cochrane, K.R., Modine, N.A., Thompson, A.P., Cangi, A., Ramakrishna, K., Rohskopf, A.D., & Rohskopf, A.D. (2023). Leveraging Data Driven Frameworks to Build Transferable Interatomic Potentials [Conference Presenation]. https://doi.org/10.2172/2430436 Publication ID: 125500
  • Bachman, W.B., Cusentino, M.A., McCarthy, M.J., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2023). Developing machine learned potentials for high temperature applications [Conference Presenation]. https://doi.org/10.2172/2430457 Publication ID: 125572
  • Bachman, W.B., Rohskopf, A.D., Goff, J.M., McCarthy, M.J., Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2023). Recent Developments in Machine Learning Interatomic Potentials for Molecular Dynamics [Conference Presenation]. https://doi.org/10.2172/2430609 Publication ID: 126088
  • Wood, M.A. (2023). Exascale Ready Molecular Dynamics Simulations With LAMMPS; Application to Fluid Instabilities at Liquid-Vapor Coexistence [Conference Presenation]. https://doi.org/10.2172/2430619 Publication ID: 126128
  • Mullen, C.M., Bachman, W.B., Bachman, W.B., Furrick, I., Hensley, A., Corral Arreola, V., Wood, M.A., & Wood, M.A. (2023). Collected Posters for Sandia Intern Program from Sustainable Research Pathways / Exascale Computing [Conference Poster]. https://doi.org/10.2172/2430700 Publication ID: 126408
  • McCoy, C.A., Kalita, P., Knudson, M.D., Desjarlais, M.P., Duwal, S., Root, S., & Root, S. (2023). Hugoniot, sound speed, and phase transitions of single-crystal sapphire for pressures 0.2–2.1 TPa. Physical Review. B, 107(21). https://doi.org/10.1103/physrevb.107.214102 Publication ID: 123488
  • Stewart, J.A., Sakano, M.N., Brown, J.A., Wood, M.A., Kittell, D.E., Knepper, R., Damm, D., & Damm, D. (2023). Mesoscale Simulations on the Effects of Rate-Dependent Strength and the Shock-to-Detonation Behavior of Explosive Materials [Poster]. https://doi.org/10.2172/2430964 Publication ID: 127328
  • Bassett, W.P., Knepper, R., Marquez, M.P., Quinn, J.L., Ramasesha, K., Rohskopf, A.D., Tappan, A.S., Wood, M.A., & Wood, M.A. (2023). High Throughput Initiation Threshold Characterization of BNFF [Conference Presenation]. https://doi.org/10.2172/2430989 Publication ID: 127416
  • Cusentino, M.A., McCarthy, M.J., Bachman, W.B., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2023). Development of Machine Learned Interatomic Potentials for Modeling the Effect of Mixed Material Layers on Hydrogen Retention [Conference Poster]. https://doi.org/10.2172/2431214 Publication ID: 128224
  • Cusentino, M.A., Bachman, W.B., McCarthy, M.J., Goff, J.M., Rohskopf, A.D., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2023). Atomistic modeling of plasma material interactions using SNAP machine learned interatomic potentials [Conference Presenation]. https://doi.org/10.2172/2431239 Publication ID: 128312
  • Nikolov, S.V., Nieves, P., Thompson, A.P., Wood, M.A., Tranchida, J., & Tranchida, J. (2023). Temperature dependence of magnetic anisotropy and magnetoelasticity from classical spin-lattice calculations. Physical Review. B, 107(9). https://doi.org/10.1103/physrevb.107.094426 Publication ID: 123424
  • Bachman, W.B., Cusentino, M.A., McCarthy, M.J., Tranchida, J., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2023). Machine learned interatomic potential for dispersion strengthened plasma facing components. Journal of Chemical Physics, 158(11). https://doi.org/10.1063/5.0135269 Publication ID: 123584
  • Nikolov, S.V., Tranchida, J., Thompson, A.P., Cangi, A., Ramakrishna, K., Rohskopf, A.D., Wood, M.A., & Wood, M.A. (2023). Examining the Alpha-Epsilon Transition in Iron Using Molecular-spin Dynamics [Conference Presenation]. https://doi.org/10.2172/2431651 Publication ID: 129668
  • McCarthy, M.J., Startt, J.K., Dingreville, R.P.M., Thompson, A.P., Wood, M.A., & Wood, M.A. (2023). Training machine-learned interatomic potentials for chemical complexity – application to refractory CCAs [Conference Presenation]. https://doi.org/10.2172/2431658 Publication ID: 129696
  • Bachman, W.B., Cusentino, M.A., McCarthy, M.J., Tranchida, J., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2023). Machine-learned Interatomic Potential Development for H Trapping in ZrC Strengthened W [Conference Presenation]. https://doi.org/10.2172/2431685 Publication ID: 129784
  • McCarthy, M.J., Startt, J.K., Dingreville, R.P.M., Thompson, A.P., Wood, M.A., & Wood, M.A. (2023). Investigating the influence of local composition on properties in complex alloys using machine learned interatomic potentials [Conference Presenation]. https://doi.org/10.2172/2431768 Publication ID: 130080
  • Wood, M.A. (2023). Modular and Scalable Solutions of Machine Learned Models (for Material Science and Beyond) [Conference Presenation]. https://doi.org/10.2172/2431784 Publication ID: 130140
  • Montes de Zapiain, D., Wood, M.A., Sema, D., Thompson, A.P., & Thompson, A.P. (2023). Optimal Development of Transferable Machine Learning Interatomic Potentials using Active Learning [Poster]. https://doi.org/10.2172/2431809 Publication ID: 130236
  • Montes de Zapiain, D., Wood, M.A., Lubbers, N., Pereyra, C.Z., Thompson, A.P., Perez, D., & Perez, D. (2022). Training data selection for accuracy and transferability of interatomic potentials. npj Computational Materials, 8(1). https://doi.org/10.1038/s41524-022-00872-x Publication ID: 106592
  • Moore, S.G., Wood, M.A., Cochrane, K.R., Thompson, A.P., & Thompson, A.P. (2022). Extreme-Scale Atomistic Simulations of Molten Metal Expansion [Conference Presenation]. https://doi.org/10.2172/2006153 Publication ID: 121328
  • Bachman, W.B., Cusentino, M.A., McCarthy, M.J., Tranchida, J., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Machine Learned Interatomic Potential Development of W-ZrC for Fusion Divertor Microstructure and Thermomechanical Properties [Conference Presenation]. https://doi.org/10.2172/2005312 Publication ID: 118696
  • McCarthy, M.J., Startt, J.K., Dingreville, R.P.M., Thompson, A.P., Wood, M.A., & Wood, M.A. (2022). Exploring refractory complex concentrated alloy behavior in the fusion reactor environment with a machine-learned interatomic potential [Conference Presenation]. https://doi.org/10.2172/2005320 Publication ID: 118728
  • Moore, S.G., Wood, M.A., Cochrane, K.R., Thompson, A.P., & Thompson, A.P. (2022). Extreme-Scale Atomistic Simulations of Molten Metal Expansion [Conference Poster]. https://doi.org/10.2172/2005326 Publication ID: 118752
  • Cusentino, M.A., McCarthy, M.J., Bachman, W.B., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Molecular Dynamics Modeling of Hydrogen and Nitrogen Implantation in Tungsten Using Machine Learned Interatomic Potentials [Conference Presenation]. https://doi.org/10.2172/2005386 Publication ID: 118984
  • Wood, M.A., Nikolov, S.V., Rohskopf, A.D., Desjarlais, M.P., Cangi, A., Tranchida, J., & Tranchida, J. (2022). Quantum-Accurate Multiscale Modeling of Shock Hugoniots, Ramp Compression Paths, Structural and Magnetic Phase Transitions, and Transport Properties in Highly Compressed Metals. https://doi.org/10.2172/1898251 Publication ID: 80244
  • McCarthy, M.J., Thompson, A.P., Wood, M.A., & Wood, M.A. (2022). Building a new generation of multiscale materials models with machine-learned interatomic potentials [Conference Presenation]. https://doi.org/10.2172/2003841 Publication ID: 114648
  • Nikolov, S.V., Tranchida, J., Cangi, A., Ramakrishna, K., Lokamani, M., Wood, M.A., & Wood, M.A. (2022). Examining the shock response of iron using molecular-spin dynamics [Conference Presenation]. https://doi.org/10.2172/2003857 Publication ID: 114712
  • Wood, M.A., Stewart, J.A., Olles, J., & Olles, J. (2022). Elucidating size effects on the yield strength of single-crystal Cu via the Richtmyer-Meshkov instability [Conference Presenation]. https://doi.org/10.2172/2003960 Publication ID: 115112
  • Sakano, M.N., Brown, J.A., Hartig, J.M., Bolintineanu, D.S., Wood, M.A., & Wood, M.A. (2022). Evaluating critical microstructure features for shock sensitivity at the mesoscale [Conference Presenation]. https://doi.org/10.2172/2003982 Publication ID: 115192
  • Bachman, W.B., Cusentino, M.A., McCarthy, M.J., Tranchida, J., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Machine-Learned Interatomic Potential Development for W-ZrC for Nuclear Fusion [Conference Poster]. https://doi.org/10.2172/2004135 Publication ID: 115792
  • Goff, J.M., Wood, M.A., Thompson, A.P., Sievers, C., & Sievers, C. (2022). Permutation-Adapted Atomic Cluster Expansion Models [Conference Poster]. https://doi.org/10.2172/2004172 Publication ID: 115924
  • Rohskopf, A.D., Sievers, C., McCarthy, M.J., Goff, J.M., Bachman, W.B., Thompson, A.P., Wood, M.A., & Wood, M.A. (2022). FitSNAP: Machine Learned Potentials for LAMMPS [Conference Poster]. https://doi.org/10.2172/2004206 Publication ID: 116060
  • Sakano, M.N., Brown, J.A., Hartig, J.M., Bolintineanu, D.S., Wood, M.A., & Wood, M.A. (2022). Evaluating critical microstructure features for shock sensitivity at the mesoscale [Conference Presenation]. https://www.osti.gov/biblio/2004208 Publication ID: 116068
  • McCarthy, M.J., Startt, J.K., Dingreville, R.P.M., Wood, M.A., & Wood, M.A. (2022). Training Machine Learned Interatomic Potentials for Chemical Complexity – Application to Refractory Complex Concentrated Alloys [Conference Poster]. https://doi.org/10.2172/2004234 Publication ID: 116168
  • McCarthy, M.J., Startt, J.K., Dingreville, R.P.M., Wood, M.A., & Wood, M.A. (2022). Exploring refractory complex concentrated alloy behavior in the fusion reactor environment with a machine-learned interatomic potential [Conference Presenation]. https://doi.org/10.2172/2003431 Publication ID: 113052
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Development of SNAP Potentials for Molecular Dynamics Modeling of Hydrogen and Nitrogen Interactions in Tungsten [Conference Presenation]. https://doi.org/10.2172/2003436 Publication ID: 113072
  • Bachman, W.B., Tranchida, J., Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Development of SNAP potential for ZrC strengthened W [Conference Presenation]. https://doi.org/10.2172/2003450 Publication ID: 113124
  • Wong, C., Kolasinski, R., Whaley, J., Cusentino, M.A., Wood, M.A., Wirth, B., Thompson, A.P., & Thompson, A.P. (2022). How nitrogen affects hydrogen adsorption on tungsten surfaces [Conference Poster]. https://doi.org/10.2172/2003479 Publication ID: 113240
  • Wood, M.A., Cole-Filipiak, N.C., Knepper, R., Ramasesha, K., & Ramasesha, K. (2022). Mode-Selective Vibrational Energy Transfer Dynamics [Conference Poster]. https://doi.org/10.2172/2003654 Publication ID: 113920
  • Sakano, M.N., Brown, J.A., Wood, M.A., & Wood, M.A. (2022). Multiscale development of predictive constitutive models to assess critical hotspots and microstructure sensitivity [Conference Poster]. https://doi.org/10.2172/2003711 Publication ID: 114136
  • Wood, M.A. (2022). FitSNAP : Scalable Solutions for Training Machine Learned Interatomic Potentials [Conference Presenation]. https://doi.org/10.2172/2003344 Publication ID: 112744
  • Stewart, J.A., Wood, M.A., Olles, J.D., & Olles, J.D. (2022). Elucidating size effects on the yield strength of single-crystal Cu via the Richtmyer-Meshkov instability. Journal of Applied Physics, 131(11). https://doi.org/10.1063/5.0082495 Publication ID: 80505
  • Wood, M.A., Sievers, C., Perez, D., Lubbers, N., Thompson, A.P., & Thompson, A.P. (2022). Scalable Solutions for Training Machine Learned Interatomic Potentials [Conference Presenation]. https://doi.org/10.2172/2001910 Publication ID: 108656
  • Wood, M.A., Cusentino, M.A., Oleynik, I., Thompson, A.P., & Thompson, A.P. (2022). Interatomic Potentials for Materials Science and Beyond; Advances in Machine Learned Spectral Neighborhood Analysis Potentials [Conference Presenation]. https://doi.org/10.2172/2001917 Publication ID: 108680
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Molecular Dynamics Simulations of Hydrogen and Nitrogen Implantation in Tungsten [Conference Poster]. https://doi.org/10.2172/2001960 Publication ID: 108840
  • Brown, J.A., Hartig, J., Sakano, M.N., Bolintineanu, D.S., Wood, M.A., & Wood, M.A. (2022). Data Mining the Mesoscale to Study Shock Ignition and Reaction Growth in Pressed Energetic Materials [Conference Presenation]. https://doi.org/10.2172/2002060 Publication ID: 109216
  • Nikolov, S.V., Tranchida, J., Ramakrishna, K., Lokamani, M., Cangi, A., Wood, M.A., & Wood, M.A. (2022). Dissociating the phononic, magnetic and electronic contributions to thermal conductivity: a computational study in alpha-iron. Journal of Materials Science, 57(23), pp. 10535-10548. https://doi.org/10.1007/s10853-021-06865-3 Publication ID: 77086
  • Sakano, M.N., Brown, J.A., Wood, M.A., & Wood, M.A. (2022). Development of predictive multiscale constitutive models for pressed energetic materials to resolve the shock to detonation transition [Conference Presenation]. https://doi.org/10.2172/2001781 Publication ID: 108208
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Development of SNAP Interatomic Potentials for Gas-Metal Interactions for Fusion Energy Materials [Conference Presenation]. https://doi.org/10.2172/2001794 Publication ID: 108256
  • Bachman, W.B., Tranchida, J., Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Machine Learned Interatomic Potential Development for W-ZrC [Conference Presenation]. https://doi.org/10.2172/2001815 Publication ID: 108312
  • Nikolov, S.V., Tranchida, J., Thompson, A.P., Wood, M.A., & Wood, M.A. (2022). Data-driven Magnetic Materials Modeling; Advances in Classical Molecular Dynamics [Conference Presenation]. https://doi.org/10.2172/2001816 Publication ID: 108316
  • Wood, M.A., Sievers, C., Perez, D., Lubbers, N., Thompson, A.P., & Thompson, A.P. (2022). Scalable Solutions for Training Machine Learned Interatomic Potentials [Conference Presenation]. https://doi.org/10.2172/2001823 Publication ID: 108340
  • Goff, J.M., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2022). Training Atomic Cluster Expansion Potentials using LAMMPS and FitSNAP [Conference Presenation]. https://doi.org/10.2172/2001842 Publication ID: 108404
  • McCarthy, M.J., Startt, J.K., Dingreville, R.P.M., Wood, M.A., & Wood, M.A. (2022). Training Machine Learned Interatomic Potentials for Chemical Complexity – Application to Refractory CCAs [Conference Presenation]. https://doi.org/10.2172/2001878 Publication ID: 108532
  • Nikolov, S.V., Tranchida, J., Cangi, A., Ramakrishna, K., Lokamani, M., Wood, M.A., & Wood, M.A. (2022). Probing Structural and Magnetic Phase Changes in the Shock Response of Iron with Molecular Dynamics [Conference Presenation]. https://doi.org/10.2172/2002085 Publication ID: 109316
  • Startt, J.K., Wood, M.A., McCarthy, M.J., Kustas, A.B., Donegan, S., Dingreville, R.P.M., & Dingreville, R.P.M. (2022). Expediting the materials discovery process of MPEAs through atomistic modeling and machine learning techniques [Conference Presenation]. https://doi.org/10.2172/2002104 Publication ID: 109392
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2021). Development of SNASP Machine Learned Interatomic Potentials for Materials in Extreme Environments [Conference Presenation]. https://doi.org/10.2172/1899237 Publication ID: 76870
  • Littlewood, D.J., Wood, M.A., Montes de Zapiain, D., Rajamanickam, S., Trask, N.A., & Trask, N.A. (2021). Sandia / IBM Discussion on Machine Learning for Materials Applications [Slides]. https://doi.org/10.2172/1828106 Publication ID: 76348
  • Cole-Filipiak, N.C., Knepper, R., Wood, M.A., Ramasesha, K., & Ramasesha, K. (2021). Mode-Selective Vibrational Energy Transfer Dynamics in 1,3,5-Trinitroperhydro-1,3,5-triazine (RDX) Thin Films. Journal of Physical Chemistry A, 125(36), pp. 7788-7802. https://doi.org/10.1021/acs.jpca.1c04800 Publication ID: 75464
  • Cusentino, M.A., Bobbitt, N.S., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2021). Development of SNAP Interatomic Potentials for Studying Mixed Materials Effects at the Tungsten Divertor [Conference Presenation]. https://doi.org/10.2172/1890848 Publication ID: 75965
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2021). Development of SNAP Potentials for Fusion Reactor Materials [Conference Presenation]. https://doi.org/10.2172/1882069 Publication ID: 79641
  • Tranchida, J. (2021). Large-scale theroretical predictions of pressure and temperature ramps in iron [Conference Presenation]. https://doi.org/10.2172/1888143 Publication ID: 79712
  • Wood, M.A., Thompson, A.P., Cusentino, M.A., Montes de Zapiain, D., Oleynik, I., & Oleynik, I. (2021). Interatomic Potentials for Materials Science and Beyond; Advances in Machine Learned Spectral Neighborhood Analysis Potentials [Conference Presenation]. https://doi.org/10.2172/1883516 Publication ID: 79748
  • Wood, M.A. (2021). LAMMPS Users Meeting 2021: Visualization Tutorial [Conference Presenation]. https://doi.org/10.2172/1891069 Publication ID: 79749
  • Tranchida, J. (2021). Magneto-elastic predictions with LAMMPS and the SPIN package [Conference Presenation]. https://doi.org/10.2172/1884091 Publication ID: 79847
  • dos Santos, G., Meyer, R., Aparicio, R., Tranchida, J., Bringa, E.M., Urbassek, H.M., & Urbassek, H.M. (2021). Spin-lattice dynamics of surface vs core magnetization in Fe nanoparticles. Applied Physics Letters, 119(1). https://doi.org/10.1063/5.0055606 Publication ID: 79484
  • Patel, R., Trask, N.A., Wood, M.A., Cyr, E.C., & Cyr, E.C. (2021). Modal Operator Regression for Extracting Nonlocal Continuum Models [Conference Presenation]. https://doi.org/10.2172/1881690 Publication ID: 79600
  • Tranchida, J. (2021). LAMMPS, a brief overview and examples of modifications [Presentation]. https://www.osti.gov/biblio/1884410 Publication ID: 78919
  • Tranchida, J., Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2021). First-principles and classical computational study of W/ZrC interfaces [Conference Poster]. https://doi.org/10.2172/1866898 Publication ID: 78336
  • Tranchida, J., Nikolov, S.V., Wood, M.A., Cangi, A., Desjarlais, M.P., Thompson, A.P., & Thompson, A.P. (2021). Data-Driven Magneto-Elastic Predictions with Scalable Classical Spin-Lattice Dynamics [Presentation]. https://www.osti.gov/biblio/1870099 Publication ID: 78587
  • Cusentino, M.A., Wood, M.A., Wong, C., Kolasinski, R., Wirth, B., Thompson, A.P., & Thompson, A.P. (2021). Molecular Dynamics Simulations of Hydrogen and Nitrogen on Tungsten Surfaces [Conference Poster]. https://doi.org/10.2172/1866199 Publication ID: 78291
  • Wong, C., Kolasinski, R., Whaley, J.A., Cusentino, M.A., Wood, M.A., Wirth, B., Thompson, A.P., & Thompson, A.P. (2021). Nitrogen effects on hydrogen adsorption at tungsten surfaces [Conference Poster]. https://doi.org/10.2172/1866560 Publication ID: 78328
  • Nieves, P., Tranchida, J., Arapan, S., Legut, D., & Legut, D. (2021). Spin-lattice model for cubic crystals. Physical Review B, 103(9). https://doi.org/10.1103/physrevb.103.094437 Publication ID: 77994
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2021). Beryllium-driven structural evolution at the divertor surface. Nuclear Fusion, 61(4). https://doi.org/10.1088/1741-4326/abe7bd Publication ID: 77317
  • Bachman, W.B., Tranchida, J., Wildey, T., Thompson, A.P., & Thompson, A.P. (2021). Multi-fidelity ML/UQ and Bayesian Optimization for Materials Design: Application to Ternary Random Alloys [Conference Poster]. https://doi.org/10.2172/1853874 Publication ID: 77392
  • Patel, R., Trask, N.A., Wood, M.A., Cyr, E.C., & Cyr, E.C. (2021). A Physics-Informed Operator Regression Framework for Extracting Data-Driven Continuum Models [Conference Presenation]. https://doi.org/10.2172/1853856 Publication ID: 77404
  • Wood, M.A., Sievers, C., Thompson, A.P., Lubbers, N., Danny, P., & Danny, P. (2021). Building a Better Database to Learn From; Application to Interatomic Potentials [Conference Presenation]. https://doi.org/10.2172/1853859 Publication ID: 77408
  • Stanek, L.J., Clay, R.C., Dharma-Wardana, M.W.C., Wood, M.A., Beckwith, K., Murillo, M.S., & Murillo, M.S. (2021). Efficacy of the radial pair potential approximation for molecular dynamics simulations of dense plasmas. Physics of Plasmas, 28(3). https://doi.org/10.1063/5.0040062 Publication ID: 77470
  • Stanek, L.J., Clay, R.C., Dharma-Wardana, M.W.C., Wood, M.A., Beckwith, K., Murillo, M.S., & Murillo, M.S. (2021). Efficacy of the radial pair potential approximation for molecular dynamics simulations in warm dense plasmas [Conference Presenation]. https://doi.org/10.2172/1856473 Publication ID: 77724
  • Knudson, M.D., Desjarlais, M.P., Redmer, R., Preising, M., & Preising, M. (2021). Coupling the Sandia Z Machine and Condensed Matter Theory to Understand Extreme Dynamic Compression Experiments [Presentation]. https://www.osti.gov/biblio/1845620 Publication ID: 76840
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2021). Development of Machine Learned SNAP Potentials for Studying Radiation Damage in Materials [Conference Presenation]. https://doi.org/10.2172/1847209 Publication ID: 77316
  • Manickam, I., Patel, R., Trask, N.A., Wood, M.A., Lee, M., Tomas, I., Cyr, E.C., & Cyr, E.C. (2021). Thermodynamically consistent physics-informed neural networks for hyperbolic systems [Conference Presenation]. https://doi.org/10.2172/1847572 Publication ID: 77371
  • Laity, G., Robinson, A.C., Cuneo, M.E., Alam, K.M., Beckwith, K., Bennett, N.L., Bettencourt, M.T., Bond, S.D., Cochrane, K.R., Criscenti, L., Cyr, E.C., Bachman, W.B., Drake, R.R., Evstatiev, E.G., Fierro, A.S., Gardiner, T.A., Bachman, W.B., Goeke, R.S., Hamlin, N.D., … McBride, R. (2021). Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report). https://doi.org/10.2172/1813907 Publication ID: 75144
  • Stanek, L.J., Clay, R.C., Beckwith, K., Wood, M.A., Dharma-Wardana, C., Murillo, M., & Murillo, M. (2020). Effective Pair Potentials for Dense Plasma Applications [Conference Presenation]. https://doi.org/10.2172/1836178 Publication ID: 72224
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2020). Machine Learned SNAP Potentials for Materials Modeling [Presentation]. https://www.osti.gov/biblio/1837138 Publication ID: 72253
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2020). Suppression of helium bubble nucleation in beryllium exposed tungsten surfaces. Nuclear Fusion, 60(12). https://doi.org/10.1088/1741-4326/abb148 Publication ID: 74702
  • Tranchida, J., dos Santos, G., Aparicio, R., Linares, D., Miranda, E.N., Pastor, G.M., Bringa, E.M., & Bringa, E.M. (2020). Size- and temperature-dependent magnetization of iron nanoclusters. Physical Review B, 102(18). https://doi.org/10.1103/physrevb.102.184426 Publication ID: 72118
  • Patel, R., Trask, N.A., Wood, M.A., Cyr, E.C., & Cyr, E.C. (2020). A physics-informed operator regression framework for extracting data-driven continuum models. Computer Methods in Applied Mechanics and Engineering, 373. https://doi.org/10.1016/j.cma.2020.113500 Publication ID: 73586
  • Patel, R., Trask, N.A., Wood, M.A., Cyr, E.C., & Cyr, E.C. (2020). Learning continuum-scale models from micro-scale dynamics via Operator Regression [Conference Presenation]. https://doi.org/10.2172/1834283 Publication ID: 71999
  • Pan, W., Reno, J.L., Tranchida, J., & Tranchida, J. (2020). Enhance coherence time in intensely driven quantum systems. https://doi.org/10.2172/1670245 Publication ID: 99976
  • Ramasesha, K., Wood, M.A., Cole-Filipiak, N.C., Knepper, R., & Knepper, R. (2020). Experimental and Theoretical Studies of Ultrafast Vibrational Energy Transfer Dynamics in Energetic Materials. https://doi.org/10.2172/1671386 Publication ID: 100184
  • Bachman, W.B., Wildey, T., Tranchida, J., Thompson, A.P., & Thompson, A.P. (2020). Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys. Journal of Chemical Physics, 153(7). https://doi.org/10.1063/5.0015672 Publication ID: 73589
  • Rose, D., Waisman, E.M., Desjarlais, M.P., Cuneo, M.E., Hutsel, B.T., Welch, D., Bennett, N.L., Laity, G., & Laity, G. (2020). Numerical simulations of enhanced ion current losses in the inner magnetically insulated transmission line of the Z accelerator. Physical Review Accelerators and Beams, 23(8). https://doi.org/10.1103/physrevaccelbeams.23.080401 Publication ID: 99300
  • Tranchida, J., Ivanov, A.V., Dagbartsson, D., Uzdin, V.M., Jonsson, H., & Jonsson, H. (2020). Efficient optimization method for finding minimum energy paths of magnetic transitions. Journal of Physics Condensed Matter, 32(34). https://doi.org/10.1088/1361-648x/ab8b9c Publication ID: 74568
  • Seagle, C.T., Desjarlais, M.P., Porwitzky, A., Jensen, B.J., & Jensen, B.J. (2020). Compression-induced solidification of shock-melted cerium. Physical Review B, 102(5). https://doi.org/10.1103/physrevb.102.054102 Publication ID: 99396
  • Thompson, A.P., Wood, M.A., Cangi, A., Desjarlais, M.P., Tranchida, J., & Tranchida, J. (2020). Improving the accuracy of spin-lattice simulations with machine-learning interatomic potentials [Conference Poster]. https://www.osti.gov/biblio/1778150 Publication ID: 73267
  • Desjarlais, M.P., Knudson, M.D., Redmer, R., & Redmer, R. (2020). Thermodynamics of the insulator-metal transition in dense liquid deuterium. Physical Review B, 101(10). https://doi.org/10.1103/PhysRevB.101.104101 Publication ID: 66522
  • Wood, M.A., Stewart, J.A., & Stewart, J.A. (2020). Coupled Experiment and Theory to Explore the Limits of Material Strength at High Strain Rates [Conference Poster]. https://www.osti.gov/biblio/1771448 Publication ID: 73066
  • Bailly-Grandvaux, M., Kim, J., Krauland, C.M., Zhang, S., Dozieres, M., Wei, M.S., Theobald, W., Grabowski, P.E., Santos, J.J., Nicolai, P., McKenna, P., Desjarlais, M.P., Beg, F.N., & Beg, F.N. (2020). Transport of kJ-laser-driven relativistic electron beams in cold and shock-heated vitreous carbon and diamond. New Journal of Physics, 22(3). https://doi.org/10.1088/1367-2630/ab7a06 Publication ID: 106140
  • Wood, M.A., Cusentino, M.A., Thompson, A.P., & Thompson, A.P. (2020). Scale-Bridging From DFT to MD with Machine Learning [Conference Poster]. https://www.osti.gov/biblio/1766923 Publication ID: 72603
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2020). Molecular Dynamics Simulations of Mixed Materials in Tungsten [Conference Poster]. https://www.osti.gov/biblio/1766750 Publication ID: 72638
  • Brown, J.A., Kittell, D.E., Wood, M.A., Thompson, A.P., Bolintineanu, D.S., & Bolintineanu, D.S. (2020). Multiscale modeling to study effects of microstructure in shocked hexanitrostilbene [Conference Poster]. https://www.osti.gov/biblio/1767897 Publication ID: 72758
  • Wood, M.A., Plimpton, S.J., Thompson, A.P., Perez, D., Niklasson, A., & Niklasson, A. (2020). A Path to the Exascale for Atomistic Simulations with Improved Accuracy Length and Time Scales [Conference Poster]. https://www.osti.gov/biblio/1783582 Publication ID: 72854
  • Zuo, Y., Chen, C., Li, X., Deng, Z., Chen, Y., Behler, J., Csanyi, G., Shapeev, A.V., Thompson, A.P., Wood, M.A., Ong, S.P., & Ong, S.P. (2020). A Performance and Cost Assessment of Machine Learning Interatomic Potentials. Journal of Physical Chemistry. A, Molecules, Spectroscopy, Kinetics, Environment, and General Theory, 124(4), pp. 731-745. https://doi.org/10.1021/acs.jpca.9b08723 Publication ID: 69740
  • Tranchida, J., Cangi, A., Wood, M.A., Thompson, A.P., Desjarlais, M.P., & Desjarlais, M.P. (2020). Improving the accuracy of spin-lattice calculations with machine-learned interatomic potentials [Conference Poster]. https://www.osti.gov/biblio/1763622 Publication ID: 70897
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2019). Machine Learned Interatomic Potentials for Studying Plasma Material Interactions [Presentation]. https://www.osti.gov/biblio/1761053 Publication ID: 66806
  • Schultz, P.A., Tranchida, J., Chandross, M., Thompson, A.P., & Thompson, A.P. (2019). From First-Principles toward atomistic understanding of mechanical properties in High-Entropy Alloys [Conference Poster]. https://www.osti.gov/biblio/1643633 Publication ID: 66463
  • Knudson, M.D., Desjarlais, M.P., Redmer, R., Preising, M., & Preising, M. (2019). Dynamic compression experiments on deuterium and their implications for first-principles theory [Conference Poster]. https://www.osti.gov/biblio/1642658 Publication ID: 65433
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2019). Machine Learned Interatomic Potentials for Modeling Plasma Material Interactions [Conference Poster]. https://www.osti.gov/biblio/1642843 Publication ID: 65685
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2019). Molecular Dynamics Modeling of Mixed Materials in Tungsten Using Machine Learned Interatomic Potentials [Conference Poster]. https://www.osti.gov/biblio/1642931 Publication ID: 65686
  • Cochrane, K.R., Bachman, W.B., Ao, T., Root, S., Kaushagen, J., Jones, K., Magyar, R., Mattsson, T., Desjarlais, M.P., & Desjarlais, M.P. (2019). Shock Compression of Hydrocarbons to Mbar Pressures; Successes Challenges and Lessons Learned [Conference Poster]. https://www.osti.gov/biblio/1643017 Publication ID: 65962
  • Thompson, A.P., Wood, M.A., Cusentino, M.A., Tranchida, J., & Tranchida, J. (2019). Scale Bridging with SNAP Machine-Learning Interatomic Potentials [Conference Poster]. https://www.osti.gov/biblio/1641919 Publication ID: 64748
  • McCoy, C.A., Knudson, M.D., Desjarlais, M.P., & Desjarlais, M.P. (2019). Sound velocity, shear modulus, and shock melting of beryllium along the Hugoniot. Physical Review B, 100(5). https://doi.org/10.1103/PhysRevB.100.054107 Publication ID: 70554
  • Tranchida, J., Thompson, A.P., Schultz, P.A., & Schultz, P.A. (2019). Machine-learned interatomic potentials and data analysis for quantum accurate multiscale simulations of high-entropy alloys [Conference Poster]. https://www.osti.gov/biblio/1641511 Publication ID: 70302
  • Wood, M.A. (2019). Extending ab initio Calculations with Machine Learned Potentials for Molecular Dynamics [Conference Poster]. https://www.osti.gov/biblio/1641617 Publication ID: 70430
  • Cusentino, M.A., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2019). Machine Learned Interatomic Potentials for Modeling Plasma Material Interactions [Conference Poster]. https://www.osti.gov/biblio/1641622 Publication ID: 70433
  • Clay, R.C., Desjarlais, M.P., Shulenburger, L., & Shulenburger, L. (2019). Deuterium Hugoniot: Pitfalls of thermodynamic sampling beyond density functional theory. Physical Review B, 100(7). https://doi.org/10.1103/PhysRevB.100.075103 Publication ID: 70524
  • Cole-Filipiak, N.C., Marquez, M.P., Knepper, R., Harmon, R.A., Wiese-Smith, D., Schrader, P., Wood, M.A., Ramasesha, K., & Ramasesha, K. (2019). Ultrafast Spectroscopic Studies of Vibrational Energy Transfer in Energetic Materials [Conference Poster]. https://www.osti.gov/biblio/1640776 Publication ID: 69151
  • Cole-Filipiak, N.C., Marquez, M.P., Knepper, R., Harmon, R.A., Wiese-Smith, D., Schrader, P., Wood, M.A., Ramasesha, K., & Ramasesha, K. (2019). Ultrafast Spectroscopic Studies of Vibrational Energy Transfer in Energetic Materials [Conference Poster]. https://www.osti.gov/biblio/1640777 Publication ID: 69152
  • Knudson, M.D., Desjarlais, M.P., Preising, M., Redmer, R., & Redmer, R. (2019). First-principles calculations of multiple-shock conductivity measurements in hydrogen and deuterium [Conference Poster]. https://www.osti.gov/biblio/1640818 Publication ID: 69210
  • Desjarlais, M.P., Seagle, C.T., Porwitzky, A., Jensen, B., & Jensen, B. (2019). Dynamic Freezing of Liquid Cerium Under Shock-Ramp Compression [Conference Poster]. https://www.osti.gov/biblio/1640833 Publication ID: 69235
  • Wood, M.A. (2019). Multi-scale Modeling of Shock Sensitivity in Energetic Materials [Conference Poster]. https://www.osti.gov/biblio/1640855 Publication ID: 69273
  • Root, S., Desjarlais, M.P., Bachman, W.B., McCoy, C.A., Alexander, C.S., & Alexander, C.S. (2019). Shock Compression Response of Calcium Fluoride (CaF2) [Conference Poster]. https://www.osti.gov/biblio/1640949 Publication ID: 69386
  • Wood, M.A., Thompson, A.P., Cusentino, M.A., Wirth, B.D., & Wirth, B.D. (2019). Data-driven material models for atomistic simulation. Physical Review B, 99(18). https://doi.org/10.1103/PhysRevB.99.184305 Publication ID: 64420
  • Brown, J.A., Kittell, D.E., Wood, M.A., Thompson, A.P., Bolintineanu, D.S., & Bolintineanu, D.S. (2019). Multiscale modeling to determine the effect of porosity distribution on shocked hexanitrostilbene [Conference Poster]. https://www.osti.gov/biblio/1640149 Publication ID: 68747
  • Brown, J.A., Kittell, D.E., Wood, M.A., Thompson, A.P., Bolintineanu, D.S., & Bolintineanu, D.S. (2019). Multiscale modeling to determine the effect of porosity distribution on shocked hexanitrostilbene [Conference Poster]. https://www.osti.gov/biblio/1639905 Publication ID: 68356
  • Desjarlais, M.P., Knudson, M.D., Redmer, R., & Redmer, R. (2019). Comment on “Insulator-metal transition in dense fluid deuterium”. Science, 363(6433). https://doi.org/10.1126/science.aaw0969 Publication ID: 65693
  • Waisman, E.M., Desjarlais, M.P., Cuneo, M.E., & Cuneo, M.E. (2019). Ion current losses in the convolute and inner magnetically insulated transmission line of the Z machine. Physical Review Accelerators and Beams, 22(3). https://doi.org/10.1103/PhysRevAccelBeams.22.030402 Publication ID: 64196
  • Mattsson, T., Shohet, G., Townsend, J.P., Shulenburger, L., Desjarlais, M.P., & Desjarlais, M.P. (2019). Critical point liquid-vapor coexistence and melting of Mg2SiO4 from ab-initio simulations [Conference Poster]. https://www.osti.gov/biblio/1639280 Publication ID: 67304
  • Wood, M.A., Cusentino, M.A., Thompson, A.P., & Thompson, A.P. (2019). Scale-bridging From the Atoms Up; Employing Machine Learning for Molecular Dynamics [Conference Poster]. https://www.osti.gov/biblio/1639357 Publication ID: 67402
  • Townsend, J.P., Shohet, G., Shulenburger, L., Desjarlais, M.P., & Desjarlais, M.P. (2019). Critical point liquid-vapor coexistence and melting of Mg2SiO4 from ab-initio simulations [Conference Poster]. https://www.osti.gov/biblio/1639238 Publication ID: 67231
  • Thompson, A.P., Wood, M.A., Cusentino, M.A., & Cusentino, M.A. (2019). Large-scale Atomistic Simulations of Materials using SNAP Potentials [Conference Poster]. https://www.osti.gov/biblio/1639262 Publication ID: 67255
  • Tranchida, J., Thompson, A.P., Plimpton, S.J., Thibaudeau, P., & Thibaudeau, P. (2019). Coupled Magnetic Spin Dynamics and Molecular Dynamics in a Massively Parallel Framework [Presentation]. https://www.osti.gov/biblio/1582121 Publication ID: 64159
  • Tranchida, J., Cea, P.T., Nicolis, S., & Nicolis, S. (2018). Hierarchies of Landau-Lifshitz-Bloch equations for nanomagnets: A functional integral framework. Physical Review E, 98(4). https://doi.org/10.1103/PhysRevE.98.042101 Publication ID: 59012
  • Seagle, C.T., Desjarlais, M.P., Porwitzky, A., Jensen, B., & Jensen, B. (2018). Compressive Solidification of Shock Melted Cerium [Conference Poster]. https://www.osti.gov/biblio/1806915 Publication ID: 59532
  • Mattsson, T., Shohet, G., Townsend, J.P., Shulenburger, L., Desjarlais, M.P., & Desjarlais, M.P. (2018). Critical point liquid-vapor coexistence and melting of Mg$_{2}$SiO$_{4}$ from \textit{ab-initio} simulations [Conference Poster]. https://www.osti.gov/biblio/1592671 Publication ID: 59878
  • Wood, M.A., Cusentino, M.A., Thompson, A.P., & Thompson, A.P. (2018). Scale-bridging from the Atoms Up; Employing Machine Learning to Improve the Accuracy and Scalability of MD Mitchell Wood Mary Alice Cusentino and Aidan Thompson Center for Computing Research Sandia National Labs [Conference Poster]. https://www.osti.gov/biblio/1592653 Publication ID: 59885
  • Clay, R.C., Shulenburger, L., Desjarlais, M.P., & Desjarlais, M.P. (2018). The Principal Hugoniot of Deuterium: Potential Pitfalls of Beyond-DFT Thermodynamic Sampling [Conference Poster]. https://www.osti.gov/biblio/1592075 Publication ID: 58922
  • Kittell, D.E., Yarrington, C.D., Bolintineanu, D.S., Lechman, J.B., Wood, M.A., Knepper, R., Olles, J.D., Thompson, A.P., Wixom, R.R., & Wixom, R.R. (2018). Mesoscale Modeling of Explosives at Sandia National Laboratories: Past and Future Directions a GA Tech Graduate Seminar Series Lecture [Presentation]. https://www.osti.gov/biblio/1592241 Publication ID: 58971
  • Tranchida, J., Wood, M.A., Moore, S.G., & Moore, S.G. (2018). Coupled Magnetic Spin Dynamics and Molecular Dynamics in a Massively Parallel Framework (LDRD Final Report). https://doi.org/10.2172/1493836 Publication ID: 59237
  • Tranchida, J. (2018). Coupled Magnetic Spin Dynamics and Molecular Dynamics in a Massively Parallel Framework [Conference Poster]. https://www.osti.gov/biblio/1581553 Publication ID: 63635
  • Tranchida, J., Wood, M.A., Moore, S.G., Plimpton, S.J., Thompson, A.P., Thibaudeau, P., & Thibaudeau, P. (2018). Spin-orbit coupling and magnetic long-range dipolar interaction for coupled spin-lattice dynamics [Conference Poster]. https://www.osti.gov/biblio/1581554 Publication ID: 63636
  • Cochrane, K.R., Desjarlais, M.P., Lane, J.M.D., Leung, K., Thompson, A.P., Wright, A.F., & Wright, A.F. (2018). Desorption Source Modeling: from Electronic Structure Molecular Dynamics Temkin Isotherm to Finite Element Calculations [Conference Poster]. https://www.osti.gov/biblio/1581555 Publication ID: 63637
  • Wood, M.A., Cusentino, M.A., Thompson, A.P., & Thompson, A.P. (2018). Scalable Machine Learned Interatomic Potentials With SNAP [Conference Poster]. https://www.osti.gov/biblio/1582188 Publication ID: 63750
  • Yarrington, C.D., Kittell, D.E., Bolintineanu, D.S., Lechman, J.B., Wood, M.A., Knepper, R., Olles, J.D., Thompson, A.P., Wixom, R.R., & Wixom, R.R. (2018). Mesoscale Modeling of Explosives at Sandia National Laboratories: Past and Future Directions [Conference Poster]. https://www.osti.gov/biblio/1532456 Publication ID: 62935
  • Yarrington, C.D., Kittell, D.E., Bolintineanu, D.S., Lechman, J.B., Wood, M.A., Knepper, R., Olles, J.D., Thompson, A.P., Wixom, R.R., & Wixom, R.R. (2018). Mesoscale Modeling of Explosives at Sandia National Laboratories: Past and Future Directions [Conference Poster]. https://www.osti.gov/biblio/1532457 Publication ID: 62936
  • Clay, R.C., Shulenburger, L., Desjarlais, M.P., & Desjarlais, M.P. (2018). The Principal Hugoniot of Deuterium: Potential Pitfalls of Beyond-DFT Thermodynamic Sampling [Conference Poster]. https://www.osti.gov/biblio/1574267 Publication ID: 63468
  • Thompson, A.P., Wood, M.A., & Wood, M.A. (2018). Extending the accuracy of the SNAP interatomic potential form. Journal of Chemical Physics, 148(24). https://doi.org/10.1063/1.5017641 Publication ID: 54748
  • Tranchida, J., Thompson, A.P., Plimpton, S.J., Thibaudeau, P., & Thibaudeau, P. (2018). Coupled Magnetic Spin Dynamics and Molecular Dynamics in a Massively Parallel Framework [Presentation]. https://www.osti.gov/biblio/1523704 Publication ID: 62277
  • Wood, M.A., Kittell, D.E., Yarrington, C.D., Thompson, A.P., & Thompson, A.P. (2018). Shock Initiation at the Mesoscale: Bridging Atomistic and Continuum Simulation [Conference Poster]. https://www.osti.gov/biblio/1524823 Publication ID: 62333
  • Baczewski, A.D., Cangi, A., Desjarlais, M.P., Hansen, S.B., Jensen, D.S., Magyar, R.J., Shulenburger, L., & Shulenburger, L. (2018). Real-time dynamics of warm dense matter [Presentation]. https://www.osti.gov/biblio/1524696 Publication ID: 62347
  • Tranchida, J., Thompson, A.P., Plimpton, S.J., Pillars, J., Monson, T.C., Langlois, E., Cangi, A., Thibaudeau, P., & Thibaudeau, P. (2018). Coupled Magnetic Spin Dynamics and Molecular Dynamics in a Massively Parallel Framework [Conference Poster]. https://www.osti.gov/biblio/1508692 Publication ID: 61617
  • Tranchida, J. (2018). Coupled Magnetic Spin Dynamics and Molecular Dynamics in a Massively Parallel Framework [Conference Poster]. https://www.osti.gov/biblio/1508693 Publication ID: 61618
  • Clay, R.C., Shulenburger, L., Desjarlais, M.P., & Desjarlais, M.P. (2018). Anharmonicity in Equation of State Calculations: A Cross-Validation Study [Conference Poster]. https://www.osti.gov/biblio/1499857 Publication ID: 61020
  • Clay, R.C., Shulenburger, L., Desjarlais, M.P., & Desjarlais, M.P. (2018). The Principal Hugoniot of Deuterium: Potential Pitfalls of Beyond-DFT Thermodynamic Sampling [Conference Poster]. https://www.osti.gov/biblio/1512362 Publication ID: 60772
  • Wood, M.A., Thompson, A.P., & Thompson, A.P. (2018). Linear Scaling Quantum-Accurate Interatomic Potentials with SNAP; Accessing those ?hard-to-reach? places in Classical Molecular Dynamics [Conference Poster]. https://www.osti.gov/biblio/1498602 Publication ID: 60914
  • Wood, M.A., Kittell, D.E., Yarrington, C.D., Thompson, A.P., & Thompson, A.P. (2018). Multiscale modeling of shock wave localization in porous energetic material. Physical Review B, 97(1). https://doi.org/10.1103/physrevb.97.014109 Publication ID: 54145
  • Root, S., Desjarlais, M.P., Lemke, R., Bachman, W.B., Alexander, C.S., & Alexander, C.S. (2018). Shock Compression Response of Calcium Fluoride [Conference Poster]. https://www.osti.gov/biblio/1512647 Publication ID: 58586
  • Scipioni, R., Stixrude, L., Desjarlais, M.P., & Desjarlais, M.P. (2017). Electrical conductivity of SiO2 at extreme conditions and planetary dynamos. Proceedings of the National Academy of Sciences of the United States of America, 114(34), pp. 9009-9013. https://doi.org/10.1073/pnas.1704762114 Publication ID: 55985
  • Wood, M.A., Kittell, D.E., Yarrington, C.D., Thompson, A.P., & Thompson, A.P. (2017). Multiscale Analysis of Cavity Collapse in High Explosives [Presentation]. https://www.osti.gov/biblio/1508720 Publication ID: 58022
  • Desjarlais, M.P., Knudson, M.D., Cochrane, K.R., & Cochrane, K.R. (2017). Extension of the Hugoniot and analytical release model of α -quartz to 0.2-3 TPa. Journal of Applied Physics, 122(3). https://doi.org/10.1063/1.4991814 Publication ID: 56270
  • Wood, M.A., Kittell, D.E., Yarrington, C.D., Thompson, A.P., & Thompson, A.P. (2017). Shock Waves and Defects in Energetic Materials a Match Made in MD Heaven [Conference Poster]. https://www.osti.gov/biblio/1460153 Publication ID: 57159
  • Furnish, M.D., Shulenburger, L., Desjarlais, M.P., Fei, Y., & Fei, Y. (2017). Recent research on stishovite: Hugoniot and partial release Z experiments and DFT EOS calculations [Conference Poster]. https://www.osti.gov/biblio/1506598 Publication ID: 57257
  • Desjarlais, M.P. (2017). Density Functional Methods for Shock Physics and High Energy Density Science [Conference Poster]. https://www.osti.gov/biblio/1506883 Publication ID: 57296
  • Tranchida, J., Thompson, A.P., Plimpton, S.J., & Plimpton, S.J. (2017). Spin–lattice simulations with LAMMPS [Conference Poster]. https://www.osti.gov/biblio/1462618 Publication ID: 57621
  • Tranchida, J., Thompson, A.P., Plimpton, S.J., & Plimpton, S.J. (2017). Spin–lattice simulations with LAMMPS [Conference Poster]. https://www.osti.gov/biblio/1462619 Publication ID: 57622
  • McCoy, C.A., Knudson, M.D., Desjarlais, M.P., & Desjarlais, M.P. (2017). Sound velocity and strength of beryllium along the principal Hugoniot [Conference Poster]. https://www.osti.gov/biblio/1513617 Publication ID: 57116
  • Flicker, D., Bachman, W.B., Desjarlais, M.P., Knudson, M.D., Leifeste, G.T., Lemke, R.W., Mattsson, T., Wise, J.L., & Wise, J.L. (2017). Sandia Dynamic Materials Program Strategic Plan. https://doi.org/10.2172/1367395 Publication ID: 56133
  • Knudson, M.D., Desjarlais, M.P., Becker, A., Lemke, R.W., Cochrane, K.R., Savage, M.E., Bliss, D.E., Mattsson, T., Redmer, R., & Redmer, R. (2017). Dynamic compression experiments on deuterium and their implications for first-principles theory [Conference Poster]. https://www.osti.gov/biblio/1457851 Publication ID: 56149
  • Kittell, D.E., Yarrington, C.D., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2017). Multiscale Analysis and Comparison of Cavity Collapse in High Explosives [Presentation]. https://www.osti.gov/biblio/1367289 Publication ID: 56444
  • Desjarlais, M.P. (2017). Development of a wide-range electrical and thermal conductivity model for ICF applications [Conference Poster]. https://www.osti.gov/biblio/1456437 Publication ID: 55662
  • Baczewski, A.D., Jensen, D.S., Cangi, A., Desjarlais, M.P., Hansen, S.B., Shulenburger, L., & Shulenburger, L. (2017). Real-time TDDFT beyond the linear response regime [Conference Poster]. https://www.osti.gov/biblio/1456444 Publication ID: 55671
  • Ao, T., Harding, E.C., Schollmeier, M., Bailey, J.E., Lemke, R.W., Desjarlais, M.P., Hansen, S.B., Smith, I.C., Rambo, P., Bachman, W.B., & Bachman, W.B. (2017). X-ray diagnostics for warm dense matter experiments on the Z-Accelerator [Conference Poster]. https://www.osti.gov/biblio/1456430 Publication ID: 55679
  • Shulenburger, L., Clay, R.C., Mattsson, T., Desjarlais, M.P., & Desjarlais, M.P. (2017). Understanding quantum Monte Carlo applied to Warm Dense Matter [Conference Poster]. https://www.osti.gov/biblio/1456475 Publication ID: 55684
  • Baczewski, A.D., Cangi, A., Desjarlais, M.P., Hansen, S.B., Jensen, D.S., Shulenburger, L., & Shulenburger, L. (2017). Real-Time TDDFT of Warm Dense Matter: Linear Response and Beyond [Conference Poster]. https://www.osti.gov/biblio/1456517 Publication ID: 55814
  • Shulenburger, L., Cochrane, K.R., Mattsson, T., Lane, J.M.D., Weck, P.F., Vogler, T.J., Desjarlais, M.P., & Desjarlais, M.P. (2017). Combining experiments on porous materials with DFT to access and quantify warm dense matter conditions [Conference Poster]. https://www.osti.gov/biblio/1456585 Publication ID: 55846
  • Cochrane, K.R., Shulenburger, L., Mattsson, T., Lane, J.M.D., Weck, P.F., Vogler, T.J., Desjarlais, M.P., & Desjarlais, M.P. (2017). Modeling the shock hugoniot in porous materials [Conference Poster]. https://www.osti.gov/biblio/1456591 Publication ID: 55886
  • Cochrane, K.R., Shulenburger, L., Mattsson, T., Lane, J.M.D., Weck, P.F., Vogler, T.J., Desjarlais, M.P., & Desjarlais, M.P. (2017). Modeling the Shock Hugoniot in Porous Materials [Conference Poster]. https://www.osti.gov/biblio/1456592 Publication ID: 55887
  • Desjarlais, M.P., Scullard, C.R., Benedict, L.X., Whitley, H.D., Redmer, R., & Redmer, R. (2017). Density-functional calculations of transport properties in the nondegenerate limit and the role of electron-electron scattering. Physical Review E, 95(3). https://doi.org/10.1103/physreve.95.033203 Publication ID: 106396
  • Thompson, A.P., Wood, M.A., & Wood, M.A. (2017). SNAP: Automated Generation of High-Accuracy Interatomic Potentials using Quantum Data [Conference Poster]. https://www.osti.gov/biblio/1507630 Publication ID: 55265
  • Wood, M.A., Kittell, D.E., Yarrington, C.D., Thompson, A.P., & Thompson, A.P. (2017). Shock Waves and Defects in Energetic Materials a Match Made in MD Heaven [Conference Poster]. https://www.osti.gov/biblio/1507631 Publication ID: 55321
  • Yarrington, C.D., Thompson, A.P., Kittell, D.E., Wood, M.A., & Wood, M.A. (2017). L2 Milestone: Multiscale Analysis and Comparisons of Cavity Collapse in High Explosives [Presentation]. https://www.osti.gov/biblio/1456388 Publication ID: 55550
  • Wood, M.A., Thompson, A.P., & Thompson, A.P. (2017). Quantum-Accurate Molecular Dynamics Potential for Tungsten. https://doi.org/10.2172/1365473 Publication ID: 55572
  • Knudson, M.D., Desjarlais, M.P., Lemke, R.W., & Lemke, R.W. (2016). Shock compression experiments on Lithium Deuteride (LiD) single crystals. Journal of Applied Physics, 120(23). https://doi.org/10.1063/1.4972553 Publication ID: 47557
  • Narkis, J., Rahman, H.U., Ney, P., Desjarlais, M.P., Wessel, F.J., Conti, F., Valenzuela, J.C., Beg, F.N., & Beg, F.N. (2016). Shock formation in Ne, Ar, Kr, and Xe on deuterium gas puff implosions. Physics of Plasmas, 23(12). https://doi.org/10.1063/1.4972547 Publication ID: 52684
  • Hmiel, A., Winey, J.M., Gupta, Y.M., Desjarlais, M.P., & Desjarlais, M.P. (2016). Nonlinear elastic response of strong solids: First-principles calculations of the third-order elastic constants of diamond. Physical Review B, 93(17). https://doi.org/10.1103/PhysRevB.93.174113 Publication ID: 52685
  • Knudson, M.D., Desjarlais, M.P., Becker, A., Lemke, R.W., Cochrane, K.R., Savage, M.E., Bliss, D.E., Mattsson, T., Redmer, R., & Redmer, R. (2016). Hydrogen Metallization [Conference Poster]. https://www.osti.gov/biblio/1368789 Publication ID: 50142
  • Ao, T., Harding, E.C., Bailey, J.E., Lemke, R.W., Desjarlais, M.P., Hansen, S.B., Smith, I.C., Geissel, M., Maurer, A.J., Reneker, J., Romero, D.H., Sinars, D., Rochau, G.A., Bachman, W.B., & Bachman, W.B. (2016). Demonstration of space-resolved x-ray Thomson scattering capability for warm dense matter experiments on the Z accelerator. High Energy Density Physics, 18, pp. 26-37. https://doi.org/10.1016/j.hedp.2016.01.002 Publication ID: 45761
  • Shulenburger, L., Baczewski, A.D., Desjarlais, M.P., Seagle, C.T., & Seagle, C.T. (2016). Highly Accurate Calculations of the Phase Diagram of Cold Lithium [Conference Poster]. https://www.osti.gov/biblio/1364813 Publication ID: 49023
  • French, M., Desjarlais, M.P., Redmer, R., & Redmer, R. (2016). Ab initio calculation of thermodynamic potentials and entropies for superionic water. Physical Review E, 93(2). https://doi.org/10.1103/PhysRevE.93.022140 Publication ID: 51013
  • Baczewski, A.D., Shulenburger, L., Desjarlais, M.P., Hansen, S.B., Magyar, R.J., & Magyar, R.J. (2016). X-Ray Thomson Scattering without the Chihara Decomposition [Conference Poster]. https://www.osti.gov/biblio/1345891 Publication ID: 48637
  • Baczewski, A.D., Shulenburger, L., Desjarlais, M.P., Hansen, S.B., Magyar, R.J., & Magyar, R.J. (2016). Recent Developments in TDDFT of Warm Dense Matter [Conference Poster]. https://www.osti.gov/biblio/1342464 Publication ID: 46903
  • Bachman, W.B., Knudson, M.D., Desjarlais, M.P., & Desjarlais, M.P. (2015). High precision Hugoniot measurements of D2 near maximum compression [Conference Poster]. https://www.osti.gov/biblio/1339198 Publication ID: 41987
  • Root, S., Shulenburger, L., Lemke, R.W., Bachman, W.B., Mattsson, T., Desjarlais, M.P., & Desjarlais, M.P. (2015). Shock Response and Phase Transitions of MgO at Planetary Impact Conditions. Physical Review Letters, 115(19). https://doi.org/10.1103/PhysRevLett.115.198501 Publication ID: 97320
  • Knudson, M.D., Desjarlais, M.P., Becker, A., Lemke, R.W., Cochrane, K.R., Savage, M.E., Bliss, D.E., Mattsson, T., Redmer, R., & Redmer, R. (2015). Direct observation of an abrupt insulator-to-metal transition in dense liquid deuterium [Presentation]. https://doi.org/10.1126/science.aaa7471 Publication ID: 44280
  • Knudson, M.D., Desjarlais, M.P., Pribram-Jones, A., & Pribram-Jones, A. (2015). Adiabatic release measurements in aluminum between 400 and 1200 GPa: Characterization of aluminum as a shock standard in the multimegabar regime. Physical Review B – Condensed Matter and Materials Physics, 91(22). https://doi.org/10.1103/PhysRevB.91.224105 Publication ID: 42345
  • Knudson, M.D., Desjarlais, M.P., Becker, A., Lemke, R.W., Cochrane, K.R., Savage, M.E., Bliss, D.E., Mattsson, T., Redmer, R., & Redmer, R. (2015). Direct Observation of an Abrupt Insulator-to-Metal Transition in Dense Liquid Deuterium [Conference Poster]. https://www.osti.gov/biblio/1256547 Publication ID: 43719
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June 22, 2023