Title:

Enhancement of Plasmonic Gold Catalysts for Photocatalytic Methane Conversion

Reutilizing methane to synthesize high value fuels and chemicals for energy generation or pharmaceuticals has profound economic and environmental incentives. However, the broader impact of sustainably converting methane is presently limited by the thermodynamic challenges required for its activation. Photocatalytic methane conversion offers a promising route to utilize solar energy at ambient conditions to selectively form desirable products. Experimental studies were conducted to synthesize, characterize, and test a novel photocatalyst design comprised of gold-decorated tungstophosphoric acids (a class of polyoxometalates) supported on titanium dioxide to selectively convert methane to methanol and syngas using hydrogen peroxide as an oxidative species. Failure to selectively produce these compounds prompted mechanistic studies of the nanocomposite photocatalyst to optimize localized surface plasmon resonance using analytical and computational methods. Ultraviolet-visible spectroscopy was used to quantify the optical activity of each photocatalyst; machine learning (ML) was utilized to predict the optimal material properties; ab initio density functional theory (DFT) calculations were applied to predict electronic properties and material behavior; kinetic Monte Carlo simulations were proposed to develop probabilistic models for methane adsorption and product diffusion on the surface of the catalyst. Thus, a powerful combined experimental and computational approach was designed to synthesize the optimal photocatalyst for methane conversion while enhancing the understanding of the relationship between material properties and their catalytic activity, selectivity, and stability.

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