(55h) Computational Screening of High Entropy Alloy Catalysts for NH3 Synthesis and Cracking

Ammonia (NH₃) is gaining attention as a hydrogen carrier due to its high hydrogen content, carbon-free nature, and existing infrastructure. To use NH₃ effectively in a hydrogen economy, energy-efficient processes for its synthesis and cracking are needed. Current processes require high energy input and operate at elevated temperatures (> 600 °C) and pressures (> 200 bar). Ruthenium (Ru) is the most active catalyst for these reactions, but its rarity and high cost limit its practical use. Therefore, developing cost-effective and sustainable catalysts from abundant materials is crucial.

In this study, we performed a massive computational screening of high-entropy alloys (HEAs) as potential catalysts for both ammonia synthesis and cracking. We utilized a machine learning potential (MLP), trained with ab-initio data, to explore a wide range of HEA compositions. These HEAs were composed of nine inexpensive and earth-abundant metals (Cr, V, Mn, Fe, Co, Ni, Cu, Mo, and Ga) as alternatives to Ru. Based on previous studies, we calculated the dissociative adsorption energy of N₂ (E_2N*) on numerous considered HEA surfaces as a key descriptor to predict the catalytic activity for NH₃ synthesis and cracking using MLP-assisted density functional theory (DFT) calculations. After that, we employed Bayesian optimization to identify specific HEA compositions with E_2N* similar to Ru. These HEA candidates are expected to offer high activity, improved cost-effectiveness, and better sustainability compared to conventional Ru-based catalysts.