Direct methane conversion to more useful chemicals is a catalysis problem that has challenged researchers for many years; methanol is one such desired product because of its potential use in a wide range of industrial applications, including methanol-to-olefin (MTO) processes to form ethylene and propylene, which then may be used as raw material in production of other chemicals. Nanoscale bimetallic catalytic particles have the potential to improve upon existing monometallic micro- and macroscale catalysts by introducing unique electronic and geometric structure effects to selectively convert methane to methanol while avoiding the undesired overreaction of methane to complete oxidation products. Quantum mechanical calculation methods are used to study the binding energies of methane-derived intermediates on monometallic and bimetallic transition metal surfaces. Rate parameter estimation methods are then employed to calculate intrinsic activation energy barriers of the elementary reactions involved in methane oxidation, providing for detailed reaction pathway analysis to identify the most promising transition metal candidates for the bimetallic catalysts.
Selective oxidation of alkenes to epoxides or cis-diol products is an important organic chemical transformation utilized in many industrial processes. Novel heterogeneous Mn 1,4,7-trimethyl-1,4,7-triazacyclononane (Mn-tmtacn) catalytic structures have been shown to selectively oxidize cis-cyclooctene with H2O2; however, the precise reaction mechanism is unknown. Detailed understanding of the kinetics involved in both the self-assembly of the heterogeneous structure and the surface reaction mechanisms will assist with catalyst development and optimization of the reaction conditions to tune product selectivity. Microkinetic modeling is a powerful computational analysis tool used to analyze complex catalytic reaction systems; this technique is used in collaboration with experimental observations to elucidate the reaction mechanisms and identify relevant reaction rate parameters of the system.