Robotics & Machine Learning Daily News2024,Issue(Sep.10) :34-35.

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)

Robotics & Machine Learning Daily News2024,Issue(Sep.10) :34-35.

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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Abstract

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.

Key words

Yangzhou/People's Republic of China/As ia/Cyborgs/Elements/Emerging Technologies/Gases/Hydrogen/Inorganic Chemica ls/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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