Robotics & Machine Learning Daily News2024,Issue(Jun.7) :117-118.

Reports Outline Machine Learning Study Findings from Lanzhou University of Techn ology (Deep Potential Fitting and Mechanical Properties Study of Mgalsi Alloy)

兰州工业大学机器学习研究成果概要(Mgalsi合金深势拟合与力学性能研究)

Robotics & Machine Learning Daily News2024,Issue(Jun.7) :117-118.

Reports Outline Machine Learning Study Findings from Lanzhou University of Techn ology (Deep Potential Fitting and Mechanical Properties Study of Mgalsi Alloy)

兰州工业大学机器学习研究成果概要(Mgalsi合金深势拟合与力学性能研究)

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摘要

由一名新闻记者兼机器人与机器学习每日新闻的工作人员新闻编辑-一项关于机器学习的新研究现在已经可用。根据NewsRx记者从中国兰州发回的新闻报道,研究表明:“MgAlSi合金材料具有重量轻、强度高、电导热性能好和耐腐蚀性能好的主要性能,在工业领域有多种应用,为实现轻量化和高性能需求做出了重要贡献。”本研究的资助者包括国家自然科学基金(NSFC)、中国博士后科学基金、兰州工业大学杰出青年科学家基金。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – A new study on Machine Learning is now available. According to news reporting originating in Lanzhou, People’s Republic of China, by NewsRx journalists, research stated, “MgAlSi alloy materials have the main p roperties of light weight and high strength, good electrical and thermal conduct ivity and corrosion resistance, and have various applications in the industrial field, making an important contribution to the realization of lightweight and hi gh performance needs.” Funders for this research include National Natural Science Foundation of China ( NSFC), China Postdoctoral Science Foundation, Funds for Distinguished Young Scie ntists of Lanzhou University of Technology, China.

Key words

Lanzhou/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Molecular Dynamics/Physics/Lanzhou University of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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