The Kitchin Research Group

Usually, metal oxides grow in a single, most stable crystal structure at a particular set of conditions. For example, TiO₂ grows in the rutile structure for a large range of pressure and temperature conditions, but under some conditions it can also grow in the anatase structure. In this paper we show that epitaxial stabilization can be used to influence which crystal structures are observed for the growth of tin oxide. Tin oxide is normally only observed in the rutile structure. We grew tin oxide as an epitaxial film on a poly-crystalline substrate of CoNb₂O₆ which has an α-PbO₂ crystal structure. We found that both rutile and α-PbO₂ structures could be found in the film, and that the structure correlated with the orientation of the underlying grains. In other words, the orientation of a substrate can influence the structure of an epitaxial film, enabling one to grow films in crystal structures that may be metastable, and unobtainable in bulk samples.

@article{wittkamper-2017-compet-growt,
  author =       {Wittkamper, Julia and Xu, Zhongnan and Kombaiah, Boopathy and
                  Ram, Farangis and De Graef, Marc and Kitchin, John R. and
                  Rohrer, Gregory S. and Salvador, Paul A.},
  title =        {Competitive Growth of Scrutinyite ($\alpha$-PbO2) and Rutile
                  Polymorphs of \ce{SnO2} on All Orientations of Columbite
                  \ce{CoNb2O6} Substrates},
  journal =      {Crystal Growth \& Design},
  volume =       17,
  number =       7,
  pages =        {3929-3939},
  year =         2017,
  doi =          {10.1021/acs.cgd.7b00569},
  url =          {https://doi.org/10.1021/acs.cgd.7b00569},
  eprint =       { https://doi.org/10.1021/acs.cgd.7b00569 },
}

Copyright (C) 2017 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 9.0.7

Alloys can have rich, complex phase behavior. Cu-Pd alloys for example show an unusual behavior where a BCC lattice forms for some compositions, even though the alloy is made from two metals that are exclusively FCC in structure! Being able to model and predict this kind of behavior is a major challenge. In this work, we use cluster expansions to model the configurational degrees of freedom in the FCC and BCC lattices and show qualitatively that we can predict the region where the B2 phase (the BCC one) forms. The agreement with experiment is not quantitative though, and we show that part this disagreement is due to the lack of vibrational entropy in the cluster expansion. When we include vibrational entropy, the qualitative agreement improves.

@article{geng-2017-first-princ,
  author =       "Feiyang Geng and Jacob R. Boes and John R. Kitchin",
  title =        {First-Principles Study of the Cu-Pd Phase Diagram},
  journal =      "Calphad ",
  volume =       56,
  pages =        "224 - 229",
  year =         2017,
  doi =          {10.1016/j.calphad.2017.01.009},
  url =
                  {https://doi.org/https://doi.org/10.1016/j.calphad.2017.01.009},
  abstract =     "Abstract The equilibrium phase diagram of a Cu-Pd alloy has
                  been computed using cluster expansion and Monte Carlo
                  simulation methods combined with density functional theory.
                  The computed phase boundaries show basic features that are
                  consistent with the experimentally reported phase diagram.
                  Without vibrational free energy contributions, the
                  order-disorder transition temperature is underestimated by 100
                  K and the critical point is inconsistent with experimental
                  result. The addition of vibrational free energy contributions
                  yields a more qualitatively correct Cu-Pd phase diagram in the
                  Cu rich region. ",
  issn =         "0364-5916",
  keywords =     "Density functional theory",
}

Copyright (C) 2017 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 9.0.3

Molecules interact with each other when they adsorb on surfaces and these interactions are coverage dependent. Modeling these interactions is a challenge though, because there are many configurations of adsorbates on the surface, and the surface changes due to the interactions. To mitigate these challenges, one often simplifies the model, e.g. by using a cluster expansion or lattice gas Hamiltonian. These approaches have their own limitations though, and are not that useful for modeling dynamic processes like diffusion. Using molecular potentials enables the dynamic simulations, but not at the same level of accuracy as density functional theory. In this work we use density functional theory to train a neural network, and then use the neural network to model coverage-dependent adsorption isotherms and the dynamics of oxygen diffusion on a Pd(111) surface. We show the neural network can capture the onset of surface oxidation, and that the simulation results have comparable accuracy to the DFT calculations it was trained from.

@article{boes-2017-neural-networ,
  author =       {Jacob R. Boes and John R. Kitchin},
  title =        {Neural Network Predictions of Oxygen Interactions on a Dynamic
                  Pd Surface},
  journal =      {Molecular Simulation},
  pages =        {1-9},
  year =         2017,
  doi =          {10.1080/08927022.2016.1274984},
  url =          {https://doi.org/10.1080/08927022.2016.1274984},
  keywords =     {CBET-1506770},
}

Copyright (C) 2017 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 9.0.3

The surface composition of an alloy is rarely the same as the bulk composition due to segregation, and it changes with changing reaction conditions. Segregation is a ubiquitous issue in alloy catalysis, and makes modeling alloy surfaces a challenge, because we need to know the surface composition to model them! In this work, we take a first step in using density functional theory to build a neural network potential that we can use with Monte Carlo simulations to predict the temperature dependent surface composition of an Au-Pd bulk alloy in a vacuum. This approach yielded quantitative predictions in good agreement with experimental measurements over the entire bulk composition range.

@article{boes-2017-model-segreg,
  author =       {Jacob R. Boes and John R. Kitchin},
  title =        {Modeling Segregation on AuPd(111) Surfaces With Density
                  Functional Theory and Monte Carlo Simulations},
  journal =      {The Journal of Physical Chemistry C},
  volume =       121,
  number =       6,
  pages =        {3479-3487},
  year =         2017,
  doi =          {10.1021/acs.jpcc.6b12752},
  url =          {https://doi.org/10.1021/acs.jpcc.6b12752},
  eprint =       { https://doi.org/10.1021/acs.jpcc.6b12752 },
}

Copyright (C) 2021 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 9.4.6

Titania can be grown as an epitaxial thin film on many perovskites. The structure of the film depends on the perovskite, as well as the orientation of the surface the film grows on. In this work, we show which factors determine this, including epitaxial strain, and interface energies. In general no single factor determines all the behavior, but when considered collectively, our computational analysis correctly predicts which thin film polymorph is observed experimentally most of the time.

@article{xu-2017-first-princ,
  author =       {Xu, Zhongnan and Salvador, Paul A. and Kitchin, John R.},
  title =        {First-Principles Investigation of the Epitaxial Stabilization
                  of Oxide Polymorphs: \ce{TiO2} on \ce{(Sr,Ba)TiO3}},
  journal =      {ACS Applied Materials \& Interfaces},
  volume =       0,
  number =       {ja},
  pages =        {null},
  year =         2017,
  doi =          {10.1021/acsami.6b11791},
  url =          {https://doi.org/10.1021/acsami.6b11791},
  eprint =       { https://doi.org/10.1021/acsami.6b11791 },
  note =         {PMID: 28004912},
}

Copyright (C) 2017 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 9.0.3