Robotics & Machine Learning Daily News2024,Issue(Jun.12) :9-10.

Researchers’ Work from Pennsylvania State University (Penn State) Focuses on Mac hine Learning (Design and Validation of Refractory Alloys Using Machine Learning , Calphad, and Experiments)

宾夕法尼亚州立大学(宾州州立大学)的研究人员的工作重点是Mac Hine学习(使用机器学习、Calphad和实验设计和验证耐火合金)

Robotics & Machine Learning Daily News2024,Issue(Jun.12) :9-10.

Researchers’ Work from Pennsylvania State University (Penn State) Focuses on Mac hine Learning (Design and Validation of Refractory Alloys Using Machine Learning , Calphad, and Experiments)

宾夕法尼亚州立大学(宾州州立大学)的研究人员的工作重点是Mac Hine学习(使用机器学习、Calphad和实验设计和验证耐火合金)

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摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的新数据在一份新的报告中提供。根据NewsRx编辑在宾夕法尼亚州立大学公园的新闻报道,研究表明:“耐高温多元合金(RMCAs)由于其优异的力学性能而作为高温结构应用的潜在材料引起了人们的关注。然而,常规合金设计在成分受限和缺乏足够覆盖的计算数据库方面存在局限性。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Machine Learning are pre sented in a new report. According to news reporting out of University Park, Penn sylvania, by NewsRx editors, research stated, “Refractory multicomponent alloys (RMCAs) have garnered attention as potential materials for high-temperature stru ctural applications, due to their excellent mechanical properties. However, conv entional alloy design has limitations in terms of constrained compositional spac e and a lack of computational databases with adequate coverage.”

Key words

University Park/Pennsylvania/United States/North and Central America/Alloys/Cyborgs/Emerging Technologies/Machine Learning/Pennsylvania State University (Penn State)

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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