Estimating experimentally realized nanoparticle surfaces

Determine which crystalline surface terminations of catalyst nanoparticles are realized under experimental synthesis and reaction conditions, so that surface-level adsorption-energy descriptors can be reliably aggregated into material-level predictions of performance in electrochemical reactions.

Background

The paper’s predictive framework combines surface-level adsorption energies with bulk material descriptors to estimate experimental performance of nanoparticle catalysts. However, mapping from enumerated computational surfaces to the actual surfaces present in experimentally synthesized nanoparticles is nontrivial. The authors explore simple averaging, Boltzmann weighting, and Wulff constructions, but emphasize that knowing which surfaces are realized experimentally is a prerequisite to principled aggregation.

They cite in situ studies of reactive environments and alloy segregation phenomena to highlight that surface structure can evolve under operating conditions, making ex ante estimation difficult. This uncertainty directly limits the fidelity of material-level predictions derived from surface-level computational descriptors.