New publication on segregation in ternary alloy surfaces

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In this paper we combine density functional theory, machine learning, Monte Carlo simulations and experimental data to study segregation in a ternary alloy Cu-Pd-Au surface across the composition space. We found varying agreement and disagreement between tehe simulated and experimental results, and discuss the origins of these. Overall, Au segregates significantly across the composition space, and we learned a lot about the contributions to the discrepancies observed in Cu-Pd segregation and Au-Cu segregration.

Find the paper at

  author =       {Yilin Yang and Zhitao Guo and Andrew J. Gellman and John R.
  title =        {Simulating Segregation in a Ternary Cu-Pd-Au Alloy With
                  Density Functional Theory, Machine Learning, and Monte Carlo
  journal =      {The Journal of Physical Chemistry C},
  volume =       {nil},
  number =       {nil},
  pages =        {acs.jpcc.1c09647},
  year =         2022,
  doi =          {10.1021/acs.jpcc.1c09647},
  url =          {},
  DATE_ADDED =   {Thu Jan 20 12:39:49 2022},

Copyright (C) 2022 by John Kitchin. See the License for information about copying.

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