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Doyl E. Dickel

Doyl E. Dickel

Assistant Professor 

Office: 215 Carpenter Hall
Email: doyl@me.msstate.edu
Phone: 662.325.5454

Download Curriculum Vitae
Link to Google Scholar

Education

  • Ph.D., Physics, Clemson University, 2011
  • B.S., Physics, California Institute of Technology, 2007

Experience Record

  • Assistant Professor, Michael W. Hall School of Mechanical Engineering, Mississippi State University, 2020-Present 
  • Assistant Research Professor, Center for Advanced Vehicular Systems, Mississippi State University, 2018-2020 
  • Postdoctoral Research, Center for Advanced Vehicular Systems, Mississippi State University, 2014-2018 
  • Postdoctoral Associate, Institute for Applied Materials, Karlsruhe Institute of Technology, 2012-2014

Research Overview

Our group works to understand the fundamental behavior of materials at the level of individual atoms. While quantum mechanics can tell us a great deal about how very small numbers of atoms (1-100) interact, the equations are far too slow and complicated to solve to answer interesting questions that involve the interaction of millions or billions of atoms. We use machine learning to connect these quantum mechanical results to models, which can more efficiently predict material behavior and use these to study material properties. Our current focus is on magnetic materials, which includes iron and steel alloys, and shape memory alloys like nitinol. 

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Selected Publications

For all publications, download my curriculum vitae

  • Dickel, D. E., Baskes, M. I., Aslam, I., & Barrett, C. D. (2018). New interatomic potential for Mg–Al–Zn alloys with specific application to dilute Mg-based alloys. Modelling and Simulation in Materials Science and Engineering, 26(4), 045010
  • Dickel, D., Barrett, C. D., Carino, R. L., Baskes, M. I., & Horstemeyer, M. F. (2018). Mechanical instabilities in the modeling of phase transitions of titanium. Modelling and Simulation in Materials Science and Engineering, 26(6), 065002
  • Dickel, D., Nitol, M., & Barrett, C. D. (2021). LAMMPS implementation of rapid artificial neural network derived interatomic potentials. Computational Materials Science, 196, 110481
  • Nitol, M. S., Dickel, D. E., & Barrett, C. D. (2022). Machine learning models for predictive materials science from fundamental physics: An application to titanium and zirconium. Acta Materialia, 224, 117347
  • Nitol, M. S., Dang, K., Fensin, S. J., Baskes, M. I., Dickel, D. E., & Barrett, C. D. (2023). Hybrid interatomic potential for Sn. Physical Review Materials, 7(4), 043601

Honors and Awards

  • 2021 Outstanding Junior Faculty Research Award, Department of Mechanical Engineering, Mississippi State University