A multiscale theory framework predicts size- and ordering-dependent activity in Pt-Cu oxygen reduction reaction...

Area of Science:

• Materials Science
• Physical Chemistry
• Computational Chemistry

Background:

• Optimizing platinum-based alloy nanocatalysts for the oxygen reduction reaction (ORR) is crucial for catalysis.
• Understanding the influence of composition, size, and atomic ordering on ORR activity and durability is essential.

Purpose of the Study:

• To develop a multiscale theoretical framework for predicting the structural evolution and ORR activity of Pt-Cu alloy nanocatalysts.
• To investigate the impact of nanoparticle size and atomic ordering on catalytic performance under acidic conditions.

Main Methods:

• Integration of density functional theory (DFT), machine-learning-accelerated cluster expansions, and kinetic/Metropolis Monte Carlo simulations.
• Modeling of octahedral Pt-Cu nanoparticles (4-10 nm) to capture configurational complexity.
• Prediction of structural evolution and ORR activity based on theoretical calculations.

Main Results:

• Disordered Pt_0.85Cu_0.15 nanoparticles achieve optimal mass activity near 5 nm and a plateau at ~6 nm.
• Catalytic activity is driven by a high density of Pt(111) terrace sites in disordered nanoparticles.
• A size-dependent performance crossover between ordered and disordered Pt-Cu particles was identified, influenced by subsurface ordering and *OH binding energies.

Conclusions:

• Mechanistic insights into the structure-activity relationships of Pt-Cu alloy nanocatalysts were provided.
• Design strategies for enhancing catalytic efficiency by tailoring surface and subsurface structures were proposed.
• The study highlights the importance of atomic ordering and nanoparticle size for ORR performance.