Machine learning reveals hidden complexities in palladium oxidation, sheds light on catalyst behavior

Machine learning reveals hidden complexities in palladium oxidation, sheds light on catalyst behavior

Researchers at the Fritz Haber Institute have developed the Automatic Process Explorer (APE), an approach that enhances our understanding of atomic and molecular processes. By dynamically refining simulations, APE has uncovered unexpected complexities in the oxidation of palladium (Pd) surfaces, offering new insights into catalyst behavior. The study is published in the journal Physical Review Letters. Researchers at the Fritz Haber Institute have developed the Automatic Process Explorer (APE), an approach that enhances our understanding of atomic and molecular processes. By dynamically refining simulations, APE has uncovered unexpected complexities in the oxidation of palladium (Pd) surfaces, offering new insights into catalyst behavior. The study is published in the journal Physical Review Letters. Analytical Chemistry Materials Science Phys.org – latest science and technology news stories

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