New Data from Ministry of Education Illuminate Findings in Machine Learning (Mec hanical Degradations of Fe-c Alloys Induced By Stress Corrosion In Supercritical Co2 Environments: a Study Based On Molecular Dynamics Simulation and ...)

Robotics & Machine Learning Daily News2024，Issue(Oct.21) ：63-63.

来源：

NETL
NSTL

New Data from Ministry of Education Illuminate Findings in Machine Learning (Mec hanical Degradations of Fe-c Alloys Induced By Stress Corrosion In Supercritical Co2 Environments: a Study Based On Molecular Dynamics Simulation and ...)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Machine Learning are presented in a new report. According to news reporting originating in Changsha, People’s Repub lic of China, by NewsRx journalists, research stated, “Under supercritical carbo n dioxide (SCO2) conditions, stress corrosion cracking (SCC) of steel can signif icantly degrade their mechanical properties and shorten their service life. Howe ver, few studies have been focused on predicting such property degradation.”

Key words

Changsha/People’s Republic of China/Asia/Alloys/Cyborgs/Emerging Technologies/Machine Learning/Molecular Dynamics/Physics/Ministry of Education

引用本文复制引用

出版年

2024

Robotics & Machine Learning Daily News

ISSN：

段落导航