Robotics & Machine Learning Daily News2024,Issue(Jun.14) :10-11.

Findings on Machine Learning Discussed by Investigators at Chongqing University (Prediction of Hardness or Yield Strength for Ods Steels Based On Machine Learning)

重庆大学研究人员讨论的机器学习发现(基于机器学习的Ods钢硬度或屈服强度预测)

Robotics & Machine Learning Daily News2024,Issue(Jun.14) :10-11.

Findings on Machine Learning Discussed by Investigators at Chongqing University (Prediction of Hardness or Yield Strength for Ods Steels Based On Machine Learning)

重庆大学研究人员讨论的机器学习发现(基于机器学习的Ods钢硬度或屈服强度预测)

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摘要

机器人与机器学习的新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据新华社重庆新闻报道,“氧化物弥散强化(ODS)钢由于其优异的力学性能和耐辐照、耐腐蚀、耐氧化性能,成为一种极具发展前景的第四代核反应堆包覆材料。”采用扫描透射电子显微镜(STEM)、透射电子显微镜(TEM)和高分辨透射电子显微镜(HRTEM)研究了ODS钢中氧化物颗粒的形貌和物相。

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 Chongqing, People’s Repu blic of China, by NewsRx journalists, research stated, “Oxide dispersion strengt hened (ODS) steel has emerged as a highly promising cladding materials for Gener ation IV nuclear reactors due to its exceptional mechanical properties and remar kable resistance to irradiation, corrosion, and oxidation. In this study, the ma trix grain morphology, dispersion morphology, and phases of oxide particles in e ight ODS steels were studied by scanning transmission electron microscopy (STEM) , transmission electron microscopy (TEM), and high-resolution transmission elect ron microscopy (HRTEM).”

Key words

Chongqing/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning/Chongqing University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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