Robotics & Machine Learning Daily News2024,Issue(Jul.4) :50-51.

Research from Shandong University Broadens Understanding of Machine Learning (At omic-scale three-dimensional irradiation-induced defect kinetics models for bcc Fe-based alloys)

山东大学的研究拓宽了机器学习的理解(在omic尺度下bcc铁基合金三维辐照诱导缺陷动力学模型)

Robotics & Machine Learning Daily News2024,Issue(Jul.4) :50-51.

Research from Shandong University Broadens Understanding of Machine Learning (At omic-scale three-dimensional irradiation-induced defect kinetics models for bcc Fe-based alloys)

山东大学的研究拓宽了机器学习的理解(在omic尺度下bcc铁基合金三维辐照诱导缺陷动力学模型)

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摘要

由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于人工智能的新报告。根据中国人民共和国济南的新闻报道,NewsRx编辑的研究表明:“硫化缺陷和位错之间的相互作用可能导致宏观硬化和脆化。本研究采用分子动力学(MD)和机器学习方法研究了体心立方铁基合金中位错与空洞和铜团簇相互作用的三维动力学模型。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting out of Jinan, People’s Republ ic of China, by NewsRx editors, research stated, “The interaction between irradi ation defects and dislocations could lead to macroscopic hardening and embrittle ment. In this study, molecular dynamics (MD) and machine learning were conducted to study three-dimensional void- and Cu-cluster-induced kinetics models under i nteraction with dislocations in body-centered cubic Fe-based alloys.”

Key words

Shandong University/Jinan/People’s Rep ublic of China/Asia/Alloys/Cyborgs/Emerging Technologies/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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