377 New Developments in Computational Catalysis II


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
Co-Sponsor(s):
Computational Molecular Science and Engineering Forum (21)


Chair:
Heather J. Kulik
Assistant Professor
Massachusetts Institute of Technology
Chemical Engineering
Cambridge, MA
02139
Email: hjkulik@mit.edu

Co-chairs:
Eric Walker
University of South Carolina
Department of Chemical Engineering
301 South Main Street
Columbia, SC
29208
Email: ericwalk@umich.edu

Shaama Mallikarjun Sharada
Stanford University
Chemical Engineering
Stanford, CA
94720
Email: ssharada@usc.edu

Bin Liu
Assistant Professor
Kansas State University
Chemical Engineering
1005 Durland
Manhattan, KS
66506
Fax Number: (785) 532-7372
Email: binliu@ksu.edu


Papers:
Simulating Solvent Effects in Catalytic Systems
Matthew Neurock, University of Minnesota; Peng Bai, University of Minnesota; Chotitath Sanpitaksere, University of Minnesota
Electronic Excitations in Thermal Heterogeneous Catalysis
Matthew M. Montemore, Harvard University; Robert Hoyt, Harvard University; Grigory Kolesov, Harvard University; Efthimios Kaxiras, Harvard University
Large-Scale Nonadiabatic Molecular Dynamics Enabled By Machine Learning
Jiamin Wang, Virginia Polytechnic Institute and State University; Hongliang Xin, Virginia Polytechnic Institute and State University
Modeling of Segregation on Au-Pd (111) Surfaces with Monte Carlo Simulations and Neural Network Atomic Potentials
Jacob R. Boes, Stanford University; John R. Kitchin, Carnegie Mellon University
Accelerating Electronic Structure Calculations with Machine Learning
Andrew A. Peterson, Brown University; Alireza Khorshidi, Brown University
Overcoming the Compromise between Accuracy and Efficiency in Modelling Catalytic Kinetics
Miguel Pineda, University College London; Michail Stamatakis, University College London
CO Adsorption on Platinum and Cobalt: Site Preference and Coverage Effects
G. T. Kasun Kalhara Gunasooriya, Ghent University; Mark Saeys, Ghent University
Abstract Submissions Closed
See more of this Group/Topical: Catalysis and Reaction Engineering Division