AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learni...
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is the need to accurately compute the adsorption energy for an adsorbate and a catalyst surface of interest. Traditionally, the identification of low energy adsorbate-surfac...
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AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials
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TN_cdi_proquest_journals_2742870863
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2742870863
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E-ISSN
2331-8422
DOI
10.48550/arxiv.2211.16486
