370 New Developments in Computational Catalysis II

Tuesday, November 15, 2016: 12:30 PM - 3:00 PM
Franciscan D (Hilton San Francisco Union Square)
Description:
Electronic structure theory has matured as a widely employed tool for predicting and characterizing properties of materials and enhancing mechanistic understanding of chemical reactions. Nevertheless, typically employed approaches, such as local or semi-local density functional theory, often fail for key systems of interest in catalysis. In particular, correlated electrons in transition-metal complexes are difficult to describe without careful consideration of correlation and localization (e.g. as reintroduced in DFT+U or in correlated wavefunction theory). Equally importantly, physisorption events are often dominated by non-covalent interactions that are not directly treated in standard semi-local DFT and instead necessitate reincorporation through nonlocal descriptions of correlation. This session solicits contributions that develop or utilize methods that aim to go beyond standard semi-local DFT.

Sponsor:
Catalysis and Reaction Engineering Division

Chair:
Ye Xu
Email: yexu@lsu.edu

Co-Chair:
Bin Liu
Email: binliu@ksu.edu


12:30 PM
(370a) Development of Bayesian Error Estimation Density Functionals with Range-Separated Exchange
Shaama Mallikarjun Sharada, Keld T Lundgaard, Johannes Voss, Jess Wellendorff, Thomas Bligaard and Jens K. Norskov

12:45 PM
(370b) Uncertainty Quantification of the Water-Gas Shift Reaction By Pt/CeO2 Catalyst
Eric Walker, Salai C. Ammal, Gabriel Terejanu and Andreas Heyden

1:15 PM
(370d) Interpreting Functional-Sensitivity in Catalysis: Exchange-Tuning Vs. DFT+U
Qing Zhao, Efthymios Ioannidis, Jon Paul Janet and Heather J. Kulik

1:30 PM
(370e) Determining the Pd Dopant Effect on the Reducibility of Fe2O3: DFT+U or Hybrid Functionals?
Alyssa Hensley, Yongchun Hong, Yong Wang and Jean-Sabin McEwen

1:45 PM
(370f) Neural Network and Reaxff Comparison for Au Properties
Jacob R. Boes, Mitchell Groenenboom, John A. Keith and John R. Kitchin

2:00 PM
(370g) Machine Learning Based Interatomic Potentials for Electrocatalysts
Badri Narayanan, Fatih Sen, Alper Kinaci, Stephen Gray, Maria K. Y. Chan and Subramanian K.R.S. Sankaranarayanan
See more of this Group/Topical: Catalysis and Reaction Engineering Division