首页|Yangzhou University Reports Findings in Machine Learning (Machine learning-aided understanding of the structure-activity relationship: a case study of MoS2 supp orted metal-nonmetal pairs for the hydrogen evolution reaction)
Yangzhou University Reports Findings in Machine Learning (Machine learning-aided understanding of the structure-activity relationship: a case study of MoS2 supp orted metal-nonmetal pairs for the hydrogen evolution reaction)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting from Yangzhou, People's Repub lic of China, by NewsRx journalists, research stated, "Understanding the structu re-performance relationship is crucial for designing highly active electrocataly sts, yet this remains a challenge. Using MoS supported metal-nonmetal atom pairs (XTM@MoS, TM = Sc-Ni, and X = B, C, N, O, P, Se, Te, and S) for the hydrogen ev olution reaction (HER) as an example, we successfully uncovered the structure-ac tivity relationship with the help of density functional theory (DFT) calculation s and integrated machine learning (ML) methods." Funders for this research include Six Talent Peaks Project in Jiangsu Province, Southeast University, National Natural Science Foundation of China.
YangzhouPeople's Republic of ChinaAs iaCyborgsElementsEmerging TechnologiesGasesHydrogenInorganic Chemica lsMachine Learning
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