(107g) Accurate and Low-Cost Predictions of Complex Solvation and Reactivity Phenomena in Chemistry and Catalysis

The transition from fossil fuels to renewable energy calls for discoveries of new catalytic materials and reaction mechanisms that will enable novel transformations linking renewable energy sources (biomass, water, carbon dioxide, solar light) and high-quality fuels and value-added chemicals. Modern computational methods provide unique atomic-level insights into chemical processes, often invisible to experimental techniques, and promise to reduce the reliance on tedious “trial-and-error” experimentation in catalyst design. The challenge lies in the high complexity of realistic computational models that comes with a steep increase in computational cost. In this talk, I describe two case studies showcasing the power of current and emerging computational methods to describe complex phenomena in heterogeneous catalysis and chemistry at low computational cost and with near-quantitative accuracy.

First, I describe a multiscale protocol for making reliable predictions of adsorption enthalpies of up to 55-atom molecules in hydrophilic (defected) and hydrophobic (pristine) microporous Lewis-acidic zeolites from dilute liquid solvent mixtures in complete agreement with calorimetry measurements. The structure of the complex environment inside the pores, observed with an atomistic resolution, is shown to influence the rates of zeolite-catalyzed reactions, such as alkene epoxidation by H₂O₂ and epoxide ring opening.

Second, I discuss how applying ideas from thermodynamics to quantum chemistry leads to a simple, highly accurate, and non-empirical tight binding-type method for making predictions of chemical reactivity at a low cost with broad implications across chemistry, catalysis, and materials science.