The Kitchin Research Group

@article{larsen-2017-atomic-simul,
  author =       {Ask Hjorth Larsen and Jens J{\o}rgen Mortensen and Jakob
                  Blomqvist and Ivano E Castelli and Rune Christensen and
                  Marcin Dułak and Jesper Friis and Michael N Groves and
                  Bj{\o}rk Hammer and Cory Hargus and Eric D Hermes and Paul C
                  Jennings and Peter Bjerre Jensen and James Kermode and John
                  R Kitchin and Esben Leonhard Kolsbjerg and Joseph Kubal and
                  Kristen Kaasbjerg and Steen Lysgaard and J{\'o}n Bergmann
                  Maronsson and Tristan Maxson and Thomas Olsen and Lars
                  Pastewka and Andrew Peterson and Carsten Rostgaard and Jakob
                  Schi{\o}tz and Ole Sch{\"u}tt and Mikkel Strange and Kristian
                  S Thygesen and Tejs Vegge and Lasse Vilhelmsen and Michael
                  Walter and Zhenhua Zeng and Karsten W Jacobsen},
  title =        {The Atomic Simulation Environment-A Python Library for Working
                  With Atoms},
  journal =      {Journal of Physics: Condensed Matter},
  volume =       29,
  number =       27,
  pages =        273002,
  year =         2017,
  url =          {http://stacks.iop.org/0953-8984/29/i=27/a=273002},
  abstract =     {The atomic simulation environment (ASE) is a software package
                  written in the Python programming language with the aim of
                  setting up, steering, and analyzing atomistic simulations. In
                  ASE, tasks are fully scripted in Python. The powerful syntax
                  of Python combined with the NumPy array library make it
                  possible to perform very complex simulation tasks. For
                  example, a sequence of calculations may be performed with the
                  use of a simple 'for-loop' construction. Calculations of
                  energy, forces, stresses and other quantities are performed
                  through interfaces to many external electronic structure codes
                  or force fields using a uniform interface. On top of this
                  calculator interface, ASE provides modules for performing many
                  standard simulation tasks such as structure optimization,
                  molecular dynamics, handling of constraints and performing
                  nudged elastic band calculations.},
}

@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 },
}

@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",
}

@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},
}

@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 },
}