Computational Catalysis

The focus of Asthagiri's research group is in developing and applying multi-scale modeling methods to predict material properties entirely from atomistic simulations. Specific topics of focus include the atomic-scale studies of catalyst reactivity, electromechanical properties of ceramic materials, growth of metal and semiconductor nanostructures, and atomistic modeling of the aqueous-solid interface. Asthagiri has organized symposia on catalysis and surface science for the centennial AIChE meeting in Philadelphia, PA (2008). He has been active in the area of computational catalysis for the last 5 years and has funding from National Science Foundation, American Chemical Society Petroleum Research Fund, and Department of Energy for catalysis-related projects. Prof. Michael Janik's research uses computational, atomistic modeling methods to investigate and design catalysts for alternative energy conversion systems. Janik earned his Ph.D. (2006, U. Virginia) in the field of heterogeneous catalysis under the joint-supervision of Prof. Robert J. Davis and Prof. Matthew Neurock. His thesis work used experimental and computational methods to examine acid catalysis of alkylation reactions. He completed post-doctoral study examining electrocatalyst design for direct methanol fuel cells under the advisement of Matthew Neurock. He began his appointment as an Assistant Professor of Chemical Engineering at PSU in August, 2006. Current research activities focus on fuel cells and electrochemical systems as well as fuel processing for hydrogen and synthesis gas production. Recent research activities are funded by the Department of Energy, National Science Foundation, and the American Chemical Society Petroleum Research Fund. Janik is affiliated with the PSU Electrochemical Engine Center, PSU Institutes of Energy and the Environment, and the PSU Energy Institute. He has published 28 articles in peer reviewed journals.

Computational Catalyst Screening
First-principles Thermodynamic Models in Heterogeneous Catalysis
Kinetic Monte Carlo
Modelling Solvent Effects in Catalysis
Density Functional Theory Methods for Electrocatalysis
Machine Learning Techniques in Computational Catalysis
ReaxFF Reactive Force-field for Heterogeneous Catalysis
Modelling Complex Structures in Heterogeneous Catalysis