Visualizing high entropy alloy spaces: methods and best practices†

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY Digital discovery Pub Date : 2024-12-04 DOI:10.1039/D4DD00262H
Brent Vela, Trevor Hastings, Marshall Allen and Raymundo Arróyave
{"title":"Visualizing high entropy alloy spaces: methods and best practices†","authors":"Brent Vela, Trevor Hastings, Marshall Allen and Raymundo Arróyave","doi":"10.1039/D4DD00262H","DOIUrl":null,"url":null,"abstract":"<p >Multi-Principal Element Alloys (MPEAs) have emerged as an exciting area of research in materials science in the 2020s, owing to the vast potential for discovering alloys with unique and tailored properties enabled by the combinations of elements. However, the chemical complexity of MPEAs poses a significant challenge in visualizing composition–property relationships in high-dimensional design spaces. Without effective visualization techniques, designing chemically complex alloys is practically impossible. In this methods article, we present a suite of visualization techniques that allow for meaningful and insightful visualizations of MPEA composition spaces and property spaces. Our contribution to this suite are projections of entire alloy spaces for the purposes of design. We deploy this of visualization techniques on the following MPEA case studies: (1) constraint-satisfaction alloy design scheme, (2) Bayesian optimization alloy design campaigns, (3) and various other scenarios in the ESI. Furthermore, we show how this method can be applied to any barycentric design space. While there is no one-size-fits-all visualization technique, our toolbox offers a range of methods and best practices that can be tailored to specific MPEA research needs. This article is intended for materials scientists interested in performing research on multi-principal element alloys, chemically complex alloys, or high entropy alloys and is expected to facilitate the discovery of novel and tailored properties in MPEAs.</p>","PeriodicalId":72816,"journal":{"name":"Digital discovery","volume":" 1","pages":" 181-194"},"PeriodicalIF":6.2000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2025/dd/d4dd00262h?page=search","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital discovery","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2025/dd/d4dd00262h","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Multi-Principal Element Alloys (MPEAs) have emerged as an exciting area of research in materials science in the 2020s, owing to the vast potential for discovering alloys with unique and tailored properties enabled by the combinations of elements. However, the chemical complexity of MPEAs poses a significant challenge in visualizing composition–property relationships in high-dimensional design spaces. Without effective visualization techniques, designing chemically complex alloys is practically impossible. In this methods article, we present a suite of visualization techniques that allow for meaningful and insightful visualizations of MPEA composition spaces and property spaces. Our contribution to this suite are projections of entire alloy spaces for the purposes of design. We deploy this of visualization techniques on the following MPEA case studies: (1) constraint-satisfaction alloy design scheme, (2) Bayesian optimization alloy design campaigns, (3) and various other scenarios in the ESI. Furthermore, we show how this method can be applied to any barycentric design space. While there is no one-size-fits-all visualization technique, our toolbox offers a range of methods and best practices that can be tailored to specific MPEA research needs. This article is intended for materials scientists interested in performing research on multi-principal element alloys, chemically complex alloys, or high entropy alloys and is expected to facilitate the discovery of novel and tailored properties in MPEAs.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
可视化高熵合金空间:方法和最佳实践
多主元素合金(mpea)在21世纪20年代成为材料科学研究的一个令人兴奋的领域,因为通过元素组合可以发现具有独特和定制性能的合金的巨大潜力。然而,mpea的化学复杂性对高维设计空间中可视化组成-属性关系提出了重大挑战。如果没有有效的可视化技术,设计化学上复杂的合金实际上是不可能的。在本文中,我们提出了一套可视化技术,允许对MPEA组合空间和属性空间进行有意义和深刻的可视化。我们对这个套件的贡献是整个合金空间的投影,用于设计目的。我们将可视化技术应用于以下MPEA案例研究:(1)约束满足合金设计方案,(2)贝叶斯优化合金设计活动,(3)ESI中的各种其他场景。此外,我们展示了如何将这种方法应用于任何以重心为中心的设计空间。虽然没有放之四海而皆准的可视化技术,但我们的工具箱提供了一系列方法和最佳实践,可以根据特定的MPEA研究需求进行定制。本文面向对多主元素合金、化学复杂合金或高熵合金的研究感兴趣的材料科学家,有望促进mpea中新颖和定制特性的发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
2.80
自引率
0.00%
发文量
0
期刊最新文献
Back cover Unveiling CO2 reactivity with data-driven methods† Dissecting errors in machine learning for retrosynthesis: a granular metric framework and a transformer-based model for more informative predictions SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions† Active learning high coverage sets of complementary reaction conditions†
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1