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Computational Materials Group

Overview

The Computational Materials (CM) Group provides expertise in multiscale modeling, theory and simulation of materials, devices, and biosystems. Our goal is to develop new materials and biosystems for NASA’s high-performance applications.

Our approach is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME) and the NASA Vision 2040 Roadmap for Integrated, Multiscale Modeling and Simulations of Materials and Systems.

We participate in multi-disciplinary teams (chemists, physicists, material scientists, engineers) working on both experimental and computational issues. A combination of fundamental modeling, computational high-throughput screening and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Our methods range from first principles, ab initio computations (e.g., density functional theory), to computational chemistry to molecular dynamics simulations to multiphysics modeling.

Applications of interest are wide ranging. Advanced energy storage systems, e.g., batteries, are a long standing focus area to support NASA’s goal in green aviation and electric aircraft development. “Beyond Li-ion” battery chemistries such as Li-Air, Li-S, etc., have been considered. Battery activities include computational chemistry of electrolyte decomposition and interfacial processes, molecular dynamics simulations of electrolytes, high-throughput screening and machine learning for novel cathode materials and electrolyte formulations, multiphysics simulations of cells and packs, etc.

Novel metal alloys are a significant focus area including shape memory alloys (actuators), Ni superalloys (high temperature applications), high entropy alloys (additive manufacturing), and magnetic systems. DFT computations, interatomic potential development and MD simulations of thermodynamic and mechanical process are pursued.

We have extensive expertise in polymer simulations and multiscale modeling for ablative materials (phenolic) and structural composites and interfaces (epoxies).

We collaborate widely with researchers at other NASA Centers, other government Agencies, universities, industry, and internationally. Discussions with researchers with common interests are welcome and encouraged.

We frequently have open positions for researchers, visitors, postdocs, and interns.

Recent Publications

  • M. Khasin, M.R. Mehta, C. Kulkarni, J.W. Lawson. Dynamical model reduction for long horizon thermal prognostics for Li-ion batteries. J. Power Sources, 604 (2024), p 234442
  • O. Benafan, G.S. Gigelow, A. Garg, L.G. Wilson, R.B. Rogers, E.J. Young-Dohe, D.F. Johnson, D.A. Sheiman, J.W. Lawson, Z. Wu. Ultra-high temperature shape memory behavior in Ni-Ti-Hf alloys. Shap. Mem. Superelasticity, (2024), p 2199
  • A. Ravichandran, S. Honrao, S.R. Xie, E. Fonseca, J.W. Lawson. Computational design of low melting eutectics of molten salts: a combined machine learning and thermodynamic modeling approach. J. Phys. Chem Lett., 15 (2024), p 121
  • A. Ravichandran, J.C. Araque, J.W. Lawson. Interpretable graph neural networks for predicting the functional state of protein kinases. Proteins: Structure, Function, and Bioinformatics, (2023), p 1
  • Z. Wu, H. Malmir, O. Benafan, J.W. Lawson. Predicting the martensitic transition temperatures in ternary shape memory alloys Ni0.5Ti0.5-xHfx from first-principles calculations. Acta Mater., 261 (2023), p 119362
  • Z. Wu, O. Benafan, J.W. Lawson. Origin of the asymmetry in martensitic phase transitions in off-stoichiometric NiTi near equiatomic composition. Phys. Rev. B, 108 (2023), p L140103
  • G. Plummer, M.I. Mendelev, J.W. Lawson. Microstructural mechanisms of hysteresis and transformation width in NiTi alloys from molecular dynamics simulations. J. Phys.: Condens. Matter, 35 (2023), p 495404
  • N.A. Zarkevich, T.M. Smith, J.W. Lawson. Energy landscape in NiCoCr-based middle entropy alloys. J. Alloys Compd, 963 (2023), p 171150
  • N.A. Zarkevich, T.M. Smith, J.W. Lawson. Energy-composition relation in Ni3(Al(1-x) Xx) phases. Crystal, 13(6) (2023), p. 943
  • T.M. Smith, C.A. Kantzos, N.A. Zarkevich, P. Gradl, A.C. Thompson, T.P. Gabb, J.W. Lawson. GRX-810: a 3D printable alloy designed for extreme environments. Nature, 617 (2023), p 513-518
  • V.V. Borovikov, M.I. Mendelev, T.M. Smith, J.W. Lawson. Molecular dynamics simulation of twin nucleation and growth in Ni-based superalloys. Int. J. Plastic., 166 (2023), p 103645
  • V.V. Borovikov, M.I. Mendelev, T.M. Smith, J.W. Lawson. Dislocation-assisted diffusion-mediated atomic reshuffling in the Kolbe mechanism for micro-twinning in Ni-based superalloys. Scr. Mater., 232 (2023), p 115475
  • K.B. Knudsen, P.L. Arrechea, R.P. Viggiano, D.A. Dornbusch, J.W. Mullinax, C.W. Bauschlicher, J.B. Haskins, B. Nguyen, J.W. Lawson, B.D. McCloskey. Amide and urea based solvents for Li-O2 batteries. Part I: experimental evaluation. J. Phys. Chem. C, 127 (2023), p 7037
  • J.W. Mullinax, C.W. Bauschlicher, K.B. Knudsen, P.L. Arrechea, R.P. Viggiano, D.A. Dornbusch, J.B. Haskins, B. Nguyen, B.D. McCloskey, J.W. Lawson. Amide and urea based solvents for Li-O2 batteries. Part II: evaluation of decomposition pathways using density functional theory. J. Phys. Chem. C, 127 (2023), p 7043
  • J.P. Tavenner, M.I. Mendelev, J.W. Lawson. Molecular dynamics based kinetic Monte Carlo simulations for accelerated diffusion. Comput. Mater. Sci., 218 (2023), p 111929
  • S.R. Honrao, O. Benafan, J.W. Lawson. Data-driven study of shape memory behavior in multi-component Ni-Ti alloys in large compositional and processing spaces. Shap. Mem. Superelasticity, 9 (2023), p 144
  • G. Plummer, M.I. Mendelev, J.W. Lawson. Molecular dynamics simulations of austenite-martensite interface migration in NiTi alloy. Phys. Rev. Mat., 6 (2022), p 123601
  • Park, Z. Wu, J.W. Lawson. Mixed-domain charge transport in the S-Se system from first principles. ACS Mater. Lett., 4 (2022), p 2579
  • J.W. Mulllinax, C.W. Bauschlicher, J.W. Lawson. Modeling singlet oxygen induced degradation pathways of 1,2-dimethoxyethane in Li–O2 batteries through density functional theory. J. Phys. Chem. A, 126 (2022), p 7997
  • Z. Wu, J.W. Lawson. Theory of phase transitions in shape memory alloys NiTi. Phys. Rev. B Lett., 106 (2022), p L140102
  • C.W. Jang, J.W. Mullinax, J.H. Kang, F.L. Palmieri, T.B. Hudson, J.W. Lawson.  Microscopic deformation and failure modes of high-functionality epoxy resins from bond breaking molecular dynamics simulations and experimental investigations. Polym. Eng. Sci., 62:12 (2022), p 3952
  • C.W. Jang, J.W. Mullinax, J.W. Lawson. Mechanical properties and failure of aerospace grade epoxy resins from reactive molecular dynamics simulations with nanoscale defects. ACS Appl. Polym. Mater., 4 (2022), p 5269
  • S. Yang, X. Zhao, Y.H. Lu, E. Barnard, P. Yang, A. Baskin, J.W. Lawson, D. Prendergast, M. Salmeron. The nature of the electrical double layer on suspended graphene electrodes. J. Am. Soc. Chem., 144 (2022), p 13327
  • J. Holoubek, A. Baskin, J.W. Lawson, H. Khemchandani, T.A. Pascal, P. Liu, Z. Chen. Predicting the ion desolvation pathway of lithium electrolytes and their dependence on chemistry and temperature. ACS Energy Lett., 13 (2022), p 4426
  • T.D. Stoffel, J.B. Haskins, J.W. Lawson, S. Markutsya. Coarse-grained dynamically accurate simulations of ionic liquids at vacuum interfaces. J. Chem. Phys. B, 126 (2022), p 1819

Team

Group Lead
John Lawson

Group Members

Valery Borovikov

Michael DeLyser

Kevin Ly

Mohit Mehta

Mikhail Mendelev

Wayne Mullinax

Junsoo Park

Gabriel Plummer

Tyler Quarton

Ashwin Ravichandran

Emmanuel Skountzos

Joakim Halldin Stenlid

Jacob Tavenner

Zhigang Wu

Stephen Xie

Alumni

Juan Carlos Araque

Pedro Arrechea

Artem Baskin

Eric Bucholz

Jonathan Grunewald

Shreyas Honrao

Chang Woon Jang

Thilanga Liyana-Arachchi

Hessam Malmir

Hieu Pham

Bala Radhakrishnan

Luis Sandoval

Alex Thompson

Handan Yildirim

External Collaborators

Argonne National Lab

Army Research Lab

Brown University

Clemson University

Deakin University, Australia

ETH-Zurich, Switzerland

IBM Almaden Research Center

Lawrence Berkeley National Laboratory

Massachusetts Institute of Technology

New Mexico State University

Nissan Silicon Valley Center

Northeastern University

Purdue University

San Jose State University

Stanford University

University of California at Berkeley

University of California at San Diego

University of Florida

University of Kentucky

West Virginia University