Resolving the "CO puzzle": Disentangling electronic structure and dynamic effects via an operando dynamics framework

Area of Science:

• Surface Science
• Computational Chemistry
• Catalysis

Background:

• Carbon monoxide (CO) adsorption on catalytic surfaces is crucial for energy and chemical processes.
• The
• CO puzzle
• highlights discrepancies between theoretical predictions and experimental observations of CO adsorption sites on Pt(111).

Purpose of the Study:

• To investigate the interplay between electronic structure and dynamical effects in CO adsorption site preference on Pt(111).
• To resolve the theoretical challenge posed by the
• CO puzzle
• using advanced computational methods.

Main Methods:

• Development and application of high-dimensional neural network potential energy surfaces (NN-PESs).
• Integration of NN-PESs with molecular dynamics simulations using PBE and vdW-DF functionals.
• Comparison with lower-dimensional rigid PES simulations to assess adsorbate-surface coupling.

Main Results:

• Dynamical effects, particularly entropy, are critical for accurately predicting temperature-dependent CO adsorption.
• PBE-based simulations show a temperature-driven shift from hollow to top site preference, matching experimental data.
• vdW-DF-based simulations consistently predict top-site preference, while adsorbate-surface coupling is vital for thermodynamic accuracy.

Conclusions:

• This study successfully disentangles the contributions of electronic structure and dynamics to the CO adsorption site preference.
• The findings provide a robust framework for modeling catalytic processes under realistic operating conditions (operando).
• Accurate modeling of catalytic systems requires consideration of both electronic properties and dynamic effects, especially temperature dependence.