Exploring Computational Design of Size-Specific Subnanometer Clusters Catalysts

Abstract

Computational design of catalysts is currently an area of significant interest. While this area has made great strides in recent years, these methods have mainly been applied to solid heterogeneous catalysts. An emerging class of catalysts with very promising properties is that constructed from clusters of atoms at or below the nanoscale. The use of computational catalyst design methods for the construction and optimization of subnanometer clusters, however, has not yet been extensively explored. In this review, we discuss recent work on subnanometer catalysts in our group and discuss how computational catalyst design principles are being explored for this class of materials. Specifically, the origin of activity and selectivity for supported metal clusters that catalyze the production of propene and propylene oxide are discussed along with the implications of these studies for implementing a descriptor-based catalyst optimization. The extension of these ideas for designing a catalyst for methanol decomposition is then discussed and an application of a descriptor-based scheme for the optimization of methanol decomposition by subnanometer catalyst is shown.