首页|Studies from Chinese Academy of Sciences Provide New Data on Machine Learning (Accelerated Design of Low-activation High En- tropy Alloys With Desired Phase and Property By Machine Learn- ing)
Studies from Chinese Academy of Sciences Provide New Data on Machine Learning (Accelerated Design of Low-activation High En- tropy Alloys With Desired Phase and Property By Machine Learn- ing)
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NETL
NSTL
Elsevier
2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is the subject of a report. According to news reporting originating in Hefei, People’s Republic of China, by NewsRx journalists, research stated, “Low- activation high-entropy alloys (HEAs) have been regarded as novel candidate structural materials for fusion reactors due to their excellent mechanical and radiation resistant properties. Nevertheless, the potential vast composition space brings a prominent challenge in the design of low-activation HEAs.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), International Partnership Program for Grand Challenges of Chinese Academy of Sciences, Special Exchange Program of Chinese Academy of Sciences, HFIPS Director’s Fund, Collaborative Innovation Program of Hefei Science Center, CAS.
HefeiPeople’s Republic of ChinaAsiaAlloysCyborgsEmerg- ing TechnologiesMachine LearningChinese Academy of Sciences
NETL
NSTL
Elsevier
