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With fossil fuels dominating global energy consumption, there's an urgent need for clean alternatives. PEMFCs convert hydrogen to electricity cleanly, but are limited by inefficient oxygen reduction reactions (ORR) requiring expensive platinum catalysts. More efficient, stable, and cost-effective catalysts are needed. High-entropy alloys (HEAs) with single-atom Pt sites offer enhanced catalytic performance while using less precious metal. These multi-element alloys provide tunable properties and stability, though finding optimal compositions through traditional methods is impractical.

This research uses data-driven inverse-design to optimize HEA compositions for ORR, focusing on the Pt–Ni–Mn–Co–Cu–Mo–Cr system. We aim to maximize activity and stability through: (1) generative modeling of active compositions, (2) stability assessment, and (3) understanding activity mechanisms.

By combining computational methods with materials informatics, we seek to accelerate development of improved ORR catalysts for more sustainable energy conversion.

Visit my github for the code relating to this project: https://github.com/Sunavlis5/HEADIFF

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