Poster Title (Current Submission)

Correcting Systematic Error in DFT Modeling of NO-Metal Interactions

Major(s)

Chemistry

Minor(s)

Mathematics

Mentor Name

Sara E. Mason

Mentor Department

Chemistry

Presentation Date

March 2011

Abstract

In order to better control combustion emissions, new catalysts are required. Computationally simulating catalytic reactivity is faster and cheaper than analogous experiments. Density functional theory (DFT) is a computationally efficient method for modeling the interactions between reactants and catalysts. NO (nitric oxide) is a problematic pollutant which demands new and improved catalytic surfaces for capture. However, DFT inaccuracies in modeling the localized NO electron density pose an obstacle to quantitative predictions. Modeling the chemisorption of NO on surfaces and comparing these results with experimental data will allow the construction of a correction function for DFT systematic error in NO modeling.

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Mar 26th, 12:00 AM

Correcting Systematic Error in DFT Modeling of NO-Metal Interactions

In order to better control combustion emissions, new catalysts are required. Computationally simulating catalytic reactivity is faster and cheaper than analogous experiments. Density functional theory (DFT) is a computationally efficient method for modeling the interactions between reactants and catalysts. NO (nitric oxide) is a problematic pollutant which demands new and improved catalytic surfaces for capture. However, DFT inaccuracies in modeling the localized NO electron density pose an obstacle to quantitative predictions. Modeling the chemisorption of NO on surfaces and comparing these results with experimental data will allow the construction of a correction function for DFT systematic error in NO modeling.