Johannes Voss is staff scientist at SLAC National Accelerator Laboratory. He leads the data science and electronic structure method efforts at the SUNCAT Center for Interface Science and Catalysis. The team develops machine learning models for the accurate and efficient prediction of catalytic reaction energies and materials properties. These developments include exchange-correlation functionals for computational surface science and efficient beyond density functional theory approaches.
Within the Ultrafast Catalysis FWP at SLAC, he leads the efforts of X-ray spectra simulations for understanding of ultrafast surface chemistry as observed using free-electron lasers.

• Data-driven and constrained optimization of semi-local exchange and nonlocal correlation functionals for materials and surface chemistry
  K. Trepte, J. Voss
  J. Comput. Chem. 43, 1104 (2022)

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• Hubbard-corrected oxide formation enthalpies without adjustable parameters
  J. Voss
  J. Phys. Commun. 6, 035009 (2022)

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• MCML: Combining physical constraints with experimental data for a multi-purpose meta-generalized gradient approximation
  K. Brown, Y. Maimaiti, K. Trepte, T. Bligaard, J. Voss
  J. Comput. Chem. 42, 2004 (2021)

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• Accuracy of XAS theory for unraveling structural changes of adsorbates: CO on Ni(100)
  E. Diesen, G.L.S. Rodrigues, A.C. Luntz, F. Abild-Pedersen, L.G.M. Pettersson, J. Voss
  AIP Advances 10, 115014 (2020)

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• High-Throughput Screening of Solid-State Li-Ion Conductors Using Lattice-Dynamics Descriptors
  S. Muy, J. Voss, R. Schlem, R. Koerver, S.J. Sedlmaier, F. Maglia, P. Lamp, W.G. Zeier, Y. Shao-Horn
  ISCIENCE 16, 270 (2019)

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Google Scholar Profile

Johannes Voss is regular guest lecturer at Stanford in electronic structure and heterogeneous catalysis classes (CHEMENG-444-01/ENERGY-256-01 and CHEMENG 142/242).

Topics covered include the basics of density functional theory & beyond and how this method can be applied to predict reaction rates, thermodynamic stabilities, and other materials properties.

For information on the accompanying exercises see the TA-maintained website http://chemeng444.github.io (initiated by Charlie Tsai).

• vossj@slac.stanford.edu
• +1 (650) 926-2156
• SLAC National Accelerator Laboratory
  2575 Sand Hill Road MS 31
  Menlo Park, CA 94025
  USA