ArticleAngewandte Chemie (International ed. in English)2021
Bayesian Optimization of High-Entropy Alloy Compositions for Electrocatalytic Oxygen Reduction*.
Article in Angewandte Chemie (International ed. in English), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed.
- AI-driven electrocatalysis: reinforcement learning-based control and theoretical modeling of the glycerol oxidation reaction.Energy & environmental science · 2026Article
- Interpretable Bayesian optimization for catalyst discovery.Faraday discussions · 2026Article
- A scanning flow cell approach for generation of electrocatalyst material librariesJournal of materials chemistry. A · 2026Article
- Artificial Intelligence-Assisted Design of High-Entropy Oxide Catalysts.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- From Experiment-Driven to Theory- and Data-Driven: A Computational Paradigm Shift in High-Entropy Electrocatalyst Design.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Multi-Objective Catalyst Discovery in High-Entropy Alloy Composition Space: The Role of Noble Metals on the Pareto Front for Oxygen Reduction Reaction.Angewandte Chemie (International ed. in English) · 2026Article
- Unveiling the correlation between high-entropy alloy element systems and electrocatalytic activity.National science review · 2026Article
- Insights Into Atomic Ordering and Morphological Control Integration Design for Next-Generation Proton Exchange Membrane Fuel Cells.ChemSusChem · 2026Review
- Synthesis of High-Entropy Alloy Nanomaterials for Electrocatalytic Multi-Electron Transfer Reactions.ACS nano · 2026Review
- Next-Generation Aerogel Electrocatalysts for Oxygen Reduction Reaction.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- Sustainable Materials Design With Multi-Modal Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Few-Shot Ensemble Learning for Catalysis and Application to Trimetallics for Oxygen Reduction.ACS catalysis · 2026Article
- Unraveling the Mixing Entropy-Activity Relationship in High Entropy Alloy Catalysts: The More, The Better?Journal of the American Chemical Society · 2026Review
- AI-Accelerated Discovery of Electrocatalyst Materials.ACS materials Au · 2026Review
- Breaking the symmetry of high-entropy alloy surfaces for compressively strain-tuned oxygen reduction reaction.Nature communications · 2025Article
- Uncertainty in the era of machine learning for atomistic modeling.Digital discovery · 2025Review
- Accelerating Combinatorial Electrocatalyst Discovery with Bayesian Optimization: a Case Study in the Quaternary System Ni-Pd-Pt-Ru for the Oxygen Evolution Reaction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- AI-driven design of multiprincipal element alloys for optimal water splitting.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Bayesian Learning Aided Theoretical Optimization of IrPdPtRhRu High Entropy Alloy Catalysts for the Hydrogen Evolution Reaction.Small methods · 2025Article
- Electronic descriptors for designing high-entropy alloy electrocatalysts by leveraging local chemical environments.Nature communications · 2025Article
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13 authors.
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Abstract
Active, selective and stable catalysts are imperative for sustainable energy conversion, and engineering materials with such properties are highly desired. High-entropy alloys (HEAs) offer a vast compositional space for tuning such properties. Too vast, however, to traverse without the proper tools. Here, we report the use of Bayesian optimization on a model based on density functional theory (DFT) to predict the most active compositions for the electrochemical oxygen reduction reaction (ORR) with the least possible number of sampled compositions for the two HEAs Ag-Ir-Pd-Pt-Ru and Ir-Pd-Pt-Rh-Ru. The discovered optima are then scrutinized with DFT and subjected to experimental validation where optimal catalytic activities are verified for Ag-Pd, Ir-Pt, and Pd-Ru binary alloys. This study offers insight into the number of experiments needed for optimizing the vast compositional space of multimetallic alloys which has been determined to be on the order of 50 for ORR on these HEAs.
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