System and Method for Tuning Compositions of High-Entropy Electrocatalysts Using Active Generative Graph Learning
The invention presents a novel, integrated system and method that combines active learning (AL) with deep generative graph models to efficiently discover optimal high-entropy electrocatalyst compositions.
Prof. ZHAO Shijun, Dr. ZHANG Jun
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Graph Neural Network
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Density functional theory (DFT)
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Hydrogen Evolution Reaction (HER)
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Generative Adversarial Networks
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High-Entropy Electrocatalysts
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Active Learning
