Research Interests

We are a computational research group working to accelerate the discovery and design of solid-state materials of critical importance to sustainable energy technologies (batteries, photovoltaics, catalysts, ceramics, and more).

Our work lies at the intersection of quantum chemistry and machine learning, where these tools are used together to develop predictive theories for solid-state reactivity. In doing so, we can design synthetic pathways to novel materials and understand how materials may degrade when implemented in devices, bridging the gap between computational models and commercial technologies.

We approach the design of inorganic crystalline solids by integrating electronic structure theory, applied thermodynamics, solid-state chemistry, and data science. The predictions we make are developed and tested through close collaboration with experimental groups as we work to improve our understanding of fundamental chemical and materials engineering challenges.

Research Areas


  • Outstanding Reviewer for Materials Horizons, 2020
  • Max S. Peters Outstanding Graduate Award at the University of Colorado, 2019
  • Department of Energy EFRC Team Science Competition Winner, 2019
  • University of Washington Distinguished Young Scholars Seminar Speaker, 2019
  • National Science Foundation Graduate Research Fellowship, 2014-2017

Selected Publications

  • C. Bartel, Review of computational approaches to predict the thermodynamic stability of inorganic solids, Journal of Materials Science, 2022,
  • N. Szymanski, C. Bartel, Y. Zeng, Q. Tu, G. Ceder, Probabilistic deep learning approach to automate the interpretation of multi-phase diffraction spectra, Chemistry of Materials, 2021,
  • A. Miura, C. Bartel, Y. Goto, Y. Mizuguchi, C. Moriyoshi, Y. Kuroiwa, Y. Wang, T. Yaguchi, M. Shirai, M. Nagao, N. Rosero-Navarro, K. Tadanaga, G. Ceder, W. Sun, Observing and modeling the sequential pairwise reactions that drive solid-state ceramic synthesis, Advanced Materials, 2021,
  • C. Bartel, A. Trewartha, Q. Wang, A. Dunn, A. Jain, G. Ceder, A critical examination of compound stability predictions from machine-learned formation energies, npj Computational Materials, 2021,
  • C. Bartel, J. Clary, C. Sutton, D. Vigil-Fowler, B. Goldsmith, A. Holder, C. Musgrave, Inorganic halide double perovskites with optoelectronic properties modulated by sublattice mixing, Journal of the American Chemical Society, 2020,
  • W. Sun, C. Bartel, E. Arca, S. Bauers, B. Matthews, B. Orvañanos, J. Tate, W. Tumas, A. Zakutayev, S. Lany, A. Holder, G. Ceder, A map of the inorganic ternary metal nitrides, Nature Materials, 2019,
  • C. Bartel, C. Sutton, B. Goldsmith, R. Ouyang, C. Musgrave, L. Ghiringhelli, M. Scheffler, New tolerance factor to predict the stability of perovskite oxides and halides, Science Advances, 2019,
  • C. Bartel, S. Millican, A. Deml, J. Rumptz, W. Tumas, A. Weimer, S. Lany, V. Stevanović, C. Musgrave, A. Holder, Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry, Nature Communications, 2018,
Chris Bartel Headshot


Phone: 612/625 6345

Office: 485 Amundson Hall

Research Group


  • B.S. Chemical Engineering, Auburn University, 2010-2014
  • Ph.D. Chemical Engineering, University of Colorado Boulder, 2014-2018
  • Postdoctoral Scholar, Materials Science and Engineering, University of California Berkeley, 2019-2022