(679d) Probing the Influence of Adsorbate-Adsorbate Interactions on H* and O* Coverage over Pt and Ni Nanoparticles

Biofuels are a promising alternative to fossil fuels because of their abundant supply and net carbon-neutral byproducts. Catalytic hydrodeoxygenation (HDO) is used to produce biofuels by eliminating oxygen from bio-oils derived from lignocellulosic biomass. However, it is critical to utilize catalysts that can efficiently use costly hydrogen during HDO. The design of HDO catalysts is challenging because of the complex interplay between factors such as adsorbate coverage, temperature, pressure, and crystal structure. Many theoretical studies concentrate on low coverages, and the findings for adsorbates with significant lateral interactions deviate from the reality of near-saturation coverages. To address these challenges, a multi-scale modeling approach involving density functional theory and microkinetic models was used to investigate the coverage-dependent adsorption of hydrogen and oxygen (adsorbates representative of many surface species during HDO) on Pt and Ni nanoparticles (Figure 1). The coverage-dependent adsorption energies of O* and H* on multiple facets showed that both species experienced repulsive interactions, with (111) having the strongest repulsions due to the tightly packed nature of the facet. These adsorption energies were parameterized via mean-field polynomial models, revealing that O* has nearly twice the repulsive adsorbate-adsorbate interactions as H*. By approximating multi-faceted nanoparticles as paraboloids, we calculated the equilibrium coverages of O* and H* over Pt and Ni nanoparticles at various temperatures and pressures. For H*, the predicted coverages with and without adsorbate-adsorbate interactions are nearly identical, indicating that H* sees very weak lateral interactions. For O*, the difference in predicted coverages for both cases shows the importance of accounting for nanoscale effects in correctly modeling catalyst materials. Overall, the study establishes an approach to capturing the contributions of adsorbate-surface and adsorbate-adsorbate interactions simultaneously over multi-faceted nanoparticles. The strong influence of lateral interactions on adsorbate coverages highlights the importance of accurately accounting for nanoscale effects in modeling catalyst materials.