DC Field | Value | Language |
---|---|---|
dc.contributor.author | Bang, Kihoon | ko |
dc.contributor.author | Hong, Doosun | ko |
dc.contributor.author | Park, Youngtae | ko |
dc.contributor.author | Kim, Donghun | ko |
dc.contributor.author | Han, Sang Soo | ko |
dc.contributor.author | Lee, Hyuck-Mo | ko |
dc.date.accessioned | 2023-05-27T09:00:08Z | - |
dc.date.available | 2023-05-27T09:00:08Z | - |
dc.date.created | 2023-05-23 | - |
dc.date.created | 2023-05-23 | - |
dc.date.issued | 2023-05 | - |
dc.identifier.citation | NATURE COMMUNICATIONS, v.14, no.1 | - |
dc.identifier.issn | 2041-1723 | - |
dc.identifier.uri | http://hdl.handle.net/10203/306945 | - |
dc.description.abstract | Surface Pourbaix diagrams are critical to understanding the stability of nanomaterials in electrochemical environments. Their construction based on density functional theory is, however, prohibitively expensive for real-scale systems, such as several nanometer-size nanoparticles (NPs). Herein, with the aim of accelerating the accurate prediction of adsorption energies, we developed a bond-type embedded crystal graph convolutional neural network (BE-CGCNN) model in which four bonding types were treated differently. Owing to the enhanced accuracy of the bond-type embedding approach, we demonstrate the construction of reliable Pourbaix diagrams for very large-size NPs involving up to 6525 atoms (approximately 4.8 nm in diameter), which enables the exploration of electrochemical stability over various NP sizes and shapes. BE-CGCNN-based Pourbaix diagrams well reproduce the experimental observations with increasing NP size. This work suggests a method for accelerated Pourbaix diagram construction for real-scale and arbitrarily shaped NPs, which would significantly open up an avenue for electrochemical stability studies. | - |
dc.language | English | - |
dc.publisher | NATURE PORTFOLIO | - |
dc.title | Machine Learning-Enabled Exploration of the Electrochemical Stability of Real-Scale Metallic Nanoparticles | - |
dc.type | Article | - |
dc.identifier.wosid | 001001080600025 | - |
dc.identifier.scopusid | 2-s2.0-85160271971 | - |
dc.type.rims | ART | - |
dc.citation.volume | 14 | - |
dc.citation.issue | 1 | - |
dc.citation.publicationname | NATURE COMMUNICATIONS | - |
dc.identifier.doi | 10.1038/s41467-023-38758-1 | - |
dc.contributor.localauthor | Lee, Hyuck-Mo | - |
dc.contributor.nonIdAuthor | Bang, Kihoon | - |
dc.contributor.nonIdAuthor | Hong, Doosun | - |
dc.contributor.nonIdAuthor | Park, Youngtae | - |
dc.contributor.nonIdAuthor | Kim, Donghun | - |
dc.contributor.nonIdAuthor | Han, Sang Soo | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordPlus | ADSORBATE-ADSORBATE INTERACTIONS | - |
dc.subject.keywordPlus | OXYGEN REDUCTION REACTION | - |
dc.subject.keywordPlus | FUEL-CELL | - |
dc.subject.keywordPlus | ADSORPTION ENERGIES | - |
dc.subject.keywordPlus | SURFACE | - |
dc.subject.keywordPlus | OXIDATION | - |
dc.subject.keywordPlus | CATALYSTS | - |
dc.subject.keywordPlus | CO | - |
dc.subject.keywordPlus | ELECTROCATALYSTS | - |
dc.subject.keywordPlus | APPROXIMATION | - |
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