275753 First-Principles Multiscale Modeling of Materials for Energy and Environmental Applications

Sunday, October 28, 2012
Hall B (Convention Center )
Giannis Mpourmpakis, Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA

The rapid increase in global energy demand, in conjunction with the declining fossil fuel reserves make it necessary to adopt new strategies for energy production and utilization. In addition, emissions from combustion processes, pose serious environmental and health challenges. Future energy production and storage will employ a diverse suite of technologies, including renewables, such as biomass and processes with improved energy efficiency. Heterogeneous nanocatalysts will play a keyrole in these technologies. Increased precision in molecular architecture over multiple length scales, and/or tailored multi-functionality will often be needed in designing such catalysts. Computational methods have and will continue to play an important role in overcoming these challenges, as the demand for a fundamental understanding of realistic catalyst structures necessitates novel simulation methodologies and multiscale theoretical approaches.

My research addresses these challenges by following a bottom-up approach. Using quantum chemical methods in my core research, I elucidate the underlying pathways for chemistries of practical interest, calculate reaction energies and barriers with high accuracy, and provide insights into complicated physicochemical processes (i.e. charge transfer from support-vacancies to nanoparticles, “magic number” stability of nanoparticles). In addition, I integrate this molecular-scale information into larger scale simulation frameworks to model the behavior of complex materials under realistic reaction conditions. In this poster, I will give an overview of examples which i) reveal the mechanisms of colloidal metal nanoparticle growth (combining quantum with molecular dynamics), ii) unravel complex catalytic phenomena on the CO oxidation reaction on metal oxide supported Au nanocatalysts (combining quantum with Kinetic Monte Carlo simulations) and iii) predict novel materials for Hydrogen storage applications (combining quantum with Grand Canonical Monte Carlo Simulations).

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