Computational Catalysis with DFT

By Kevin Greenman1; Peilin Liao2

1. Department of Chemical Engineering, University of Michigan 2. School of Materials Engineering, Purdue University

DFT tool for studying heterogeneous catalysis

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Version 1.0.2 - published on 07 Aug 2018

doi:10.4231/D3PK0743B cite this

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Abstract

This tool utilizes the Atomic Simulation Environment (ASE) Python library and Quantum Espresso to calculate properties of interest for catalysis. Outputs include adsorption energy, density of states (DOS), projected density of states (PDOS), s-, p-, and d-band centers, and a visualization of the atomic structure and unit cell using the Visualization Toolkit (VTK). The tool has two modes of operation: Basic and Advanced. Basic Mode has relatively few inputs and is intended for use in educational settings, while Advanced Mode offers more customizability and is intended for use in research.

Powered by

Atomic Simulation Environment (https://wiki.fysik.dtu.dk/ase/about.html)

Quantum Espresso (http://www.quantum-espresso.org/project/manifesto)

Visualization Toolkit (VTK) (https://www.vtk.org/overview/)

Credits

This tool was developed by modifying the source code of the DFT Material Properties Simulator tool (https://nanohub.org/resources/dftmatprop).

Sponsored by

Network for Computational Nanotechnology (NCN) at Purdue University

Summer Undergraduate Research Fellowship at Purdue University

National Science Foundation, Award EEC-1227110

References

Gustavo Javier; Usama Kamran; David M Guzman; Alejandro Strachan; Peilin Liao (2017), "DFT Material Properties Simulator," https://nanohub.org/resources/dftmatprop. (DOI: 10.4231/D30G3H12Q).

Ask Hjorth Larsen, Jens Jørgen Mortensen, Jakob Blomqvist, Ivano E. Castelli, Rune Christensen, Marcin Dułak, Jesper Friis, Michael N. Groves, Bjørk Hammer, Cory Hargus, Eric D. Hermes, Paul C. Jennings, Peter Bjerre Jensen, James Kermode, John R. Kitchin, Esben Leonhard Kolsbjerg, Joseph Kubal, Kristen Kaasbjerg, Steen Lysgaard, Jón Bergmann Maronsson, Tristan Maxson, Thomas Olsen, Lars Pastewka, Andrew Peterson, Carsten Rostgaard, Jakob Schiøtz, Ole Schütt, Mikkel Strange, Kristian S. Thygesen, Tejs Vegge, Lasse Vilhelmsen, Michael Walter, Zhenhua Zeng, Karsten Wedel Jacobsen. The Atomic Simulation Environment—A Python library for working with atoms. J. Phys.: Condens. Matter Vol. 29 273002, 2017.

P. Giannozzi, S. Baroni, N. Bonini, M. Calandra, R. Car, C. Cavazzoni, D. Ceresoli, G. L. Chiarotti, M. Cococcioni, I. Dabo, A. Dal Corso, S. Fabris, G. Fratesi, S. de Gironcoli, R. Gebauer, U. Gerstmann, C. Gougoussis, A. Kokalj, M. Lazzeri, L. Martin-Samos, N. Marzari, F. Mauri, R. Mazzarello, S. Paolini, A. Pasquarello, L. Paulatto, C. Sbraccia, S. Scandolo, G. Sclauzero, A. P. Seitsonen, A. Smogunov, P. Umari, R. M. Wentzcovitch, J.Phys.:Condens.Matter, 21, 395502 (2009) http://dx.doi.org/10.1088/0953-8984/21/39/395502

Schroeder, Will; Martin, Ken; Lorensen, Bill (2006), The Visualization Toolkit (4th ed.), Kitware, ISBN 978-1-930934-19-1

Cite this work

Researchers should cite this work as follows:

  • Kevin Greenman, Peilin Liao (2018), "Computational Catalysis with DFT," https://nanohub.org/resources/compcatal. (DOI: 10.4231/D3PK0743B).

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Tags

  1. Adsorption energy
  2. catalysis
  3. density functional theory (DFT)
  4. density of states
  5. nanoelectronics
  6. Quantum ESPRESSO
  7. Surface energy