Alloys are an important class of materials that often exhibit unique physical and chemical characteristics, such as exceptional hardness or enhanced chemical reactivity. As such, alloys show promise for many applications including heterogeneous catalysis and electro-catalysis. While the potential for the utilization of alloys in heterogeneous catalysis and electro-catalysis is significant, predictive models relating the geometric structure of alloys to the catalytic reactivity are lacking.We have developed a physically transparent model that allows us to relate easily accessible physical characteristics of the elements that form an alloy (mainly their electro-negativity, atomic radius, and the spatial extent of valence orbitals) to the catalytic performance of alloy sites. The model permits rapid screening through an enormous phase space of alloy structures and compositions using analytical expressions instead of expensive quantum-chemical calculations.We will show the utility of the model through an example aimed at designing multimetallic catalysts for the electrochemical oxygen reduction reaction (ORR). We demonstrate that: (1) the simple model allows for rapid screening through large libraries of Pt-alloys, (2) the model identifies almost all Pt alloys that have thus far been shown to exhibit enhanced ORR activity compared to pure Pt and suggests many new promising alloy compositions, and (3) since the model is grounded on validated theories of chemisorption on metal surfaces, it allows us to identify the critical physical features that characterize optimal alloy electrocatalysts for ORR and propose how these features can be engineered.

Designing catalysts based on their electronic structure fingerprints: Predictive structure-performance models for metal alloy catalysts

246th National Meeting (2013)

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