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Utilization of First-Principles Based Models in the Mechanistic Studies of Thermocatalytic and Photocatalytic Processes on Transition Metal Surfaces


In this work we utilized quantum chemical calculations coupled with numerical and analytical models to predict macroscopic observables associated with catalytic and photocatalytic processes on transition metal surfaces. All the predicted macroscopic observables were validated based on experimental measurements. The theoretical models developed here provide atomic scale insights into the mechanisms of catalytic and photocatalytic processes and suggest areas for future research in the design of novel catalysts.

In the first part of this dissertation, we focused on understanding characteristics that control performance of late transition metals for the catalytic reduction of CO2 by H2. By coupling Density Functional Theory (DFT) calculations with mean-field microkinetic models we found that on Ru-based catalysts CHO* dissociation to CH* and O* is the rate determining step (RDS) for CH4 formation, while CO* desorption is the RDS for CO production. The affinity of late transition metals for O* adsorption was identified as an effective predictor of selectivity between CO and CH4 production on late transition metals, which matches well with previous experimental observations. We extended this study by developing an analytical approach, called the “scaled degree of rate control” (S-DoRC), to systematically identify rate and selectivity determining steps for reactions on late transition metals.

In the second part of this dissertation we coupled ΔSCF-DFT calculations with a Hamiltonian-based inelastic scattering model to understand the detailed mechanisms of photocatalysis on metal surfaces. We focused on understanding experimentally observed behaviors of photon-driven CO and NO desorption and O diffusion reactions on the Pt(111) surface. The developed models that accurately predicted previous wavelength-dependent and time-resolved measurements and suggested approaches to control selectivity in photon driven reactions on metal surfaces.

In the last part of this dissertation we coupled extensive DFT calculations with Wulff constructions to understand the process of CO-induced reconstruction of Pt nanoparticle catalysts, which is critical to catalytic converters. By correlating atom-resolved imaging via in-situ scanning transmission electron microscopy (STEM), with in-situ quantitative, site-specific infrared (IR) spectroscopy and DFT based Wulff-constructions we demonstrated that at high CO coverage, Pt nanoparticles undergo a facet selective reconstruction where (100) facets reconstruct to stepped vicinal surfaces, while (111) facets are stable. This is the first example of an atomic scale and quantitative view of adsorbate induced metal nanoparticle surface reconstruction at realistic conditions.

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