Data-driven optimisation of more sustainable high-to-medium entropy Perovskites for oxygen evolution catalysts

An initial library of thirty (minimal ruthenium) high-to-medium entropy La(Ru_wNi_xMn_yFe_z)O₃ oxygen evolution reaction (OER) catalysts were synthesised via a two-step process involving continuous hydrothermal flow synthesis (co-precipitation), followed by heat-treatment in air at 800 °C for 8 h. Structural analysis using powder X-ray diffraction (XRD) suggested the formation of a phase-pure orthorhombic LaFeO₃-type Perovskite structure (Pnma) in all samples except the most Ru-rich composition, which additionally showed minor rutile RuO₂ peaks. Electrochemical OER screening identified two initial champions that were La_0.94Ru_0.46Ni_0.10Mn_0.16Fe_0.34O₃ (exhibited high performance with a moderate Ru content) and La_1.00Ru_0.16Ni_0.30Mn_0.22Fe_0.32O₃ (low Ru content catalyst), with the latter delivering an overpotential of 325 mV at 10 mA cm^-2 and excellent stability of 70 h at 10 mA cm^-2 (only 4% decay). Subsequently, the electrochemical data were used to inform machine learning (ML)-guided synthesis of twelve new compositions spanning moderate- and low-Ru contents. This approach resulted in samples with improved OER performance, which included sample La_1.00Ru_0.10Ni_0.38Mn_0.18Fe_0.34O₃ (329 mV, Tafel slope 79 mV dec^-1, 93% voltage retention after 106 h at 10 mA cm^-2; durability up to 30 mA cm^-2) and sample La_1.02Ru_0.16Ni_0.36Mn_0.12Fe_0.34O₃ (269 mV, Tafel slope 62 mV dec^-1, > 90% voltage retention after 85 h at 10 mA cm^-2 and with outstanding stability with 92% voltage retention after 45 h at 30 mA cm^-2). This work demonstrates an efficient strategy for generating phase-pure Perovskite catalyst libraries and shows that a coupled electrochemical screening and ML-guided synthesis process can accelerate the discovery of stable, sustainable OER catalysts containing less critical elements but with high performance.