Computational discovery of high-performance B-Al-Ga nanoclusters for oxygen reduction reaction catalysis

The search for efficient catalysts is central to the progress of renewable energy technologies, particularly fuel cells. Platinum still sets the benchmark for the oxygen reduction reaction (ORR), yet its scarcity and cost remain serious drawbacks. In this work, we applied a computational strategy combining global structure searches with conceptual density functional theory (cDFT) descriptors to investigate boron-aluminium-gallium (B-Al-Ga) nanoalloys. From an extensive set of candidate clusters, a selected number were shortlisted and then examined in detail through adsorption energy calculations, solvation corrections, and ab initio molecular dynamics simulations. Among these, two clusters, B₄Al₂ and B₂Al, were identified as promising, showing moderate overpotentials and good stability even under solvated conditions. Examination of their electronic features reveals the composition-activity relationships, where boron facilitates stability and electron uptake, aluminium contributes to higher reactivity, and gallium fine-tunes electron donation. Taken together, these results provide guiding principles for the design of platinum-free ORR catalysts and illustrate a general computational framework that can be applied to other catalytic systems in the search for sustainable materials.