Howie Joress*, Brian L. DeCost, Suchismita Sarker, Trevor M. Braun, Sidra Jilani, Ryan Smith, Logan Ward, Kevin J. Laws, Apurva Mehta, Jason R. Hattrick-Simpers
{"title":"A High-Throughput Structural and Electrochemical Study of Metallic Glass Formation in Ni–Ti–Al","authors":"Howie Joress*, Brian L. DeCost, Suchismita Sarker, Trevor M. Braun, Sidra Jilani, Ryan Smith, Logan Ward, Kevin J. Laws, Apurva Mehta, Jason R. Hattrick-Simpers","doi":"10.1021/acscombsci.9b00215","DOIUrl":null,"url":null,"abstract":"<p >On the basis of a set of machine learning predictions of glass formation in the Ni–Ti–Al system, we have undertaken a high-throughput experimental study of that system. We utilized rapid synthesis followed by high-throughput structural and electrochemical characterization. Using this dual-modality approach, we are able to better classify the amorphous portion of the library, which we found to be the portion with a full width at half maximum (fwhm) of >0.42 ?<sup>–1</sup> for the first sharp X-ray diffraction peak. Proper phase labeling is important for future machine learning efforts. We demonstrate that the fwhm and corrosion resistance are correlated but that, while chemistry still plays a role in corrosion resistance, a large fwhm, attributed to a glassy phase, is necessary for the highest corrosion resistance.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2020-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1021/acscombsci.9b00215","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acscombsci.9b00215","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 29
Abstract
On the basis of a set of machine learning predictions of glass formation in the Ni–Ti–Al system, we have undertaken a high-throughput experimental study of that system. We utilized rapid synthesis followed by high-throughput structural and electrochemical characterization. Using this dual-modality approach, we are able to better classify the amorphous portion of the library, which we found to be the portion with a full width at half maximum (fwhm) of >0.42 ?–1 for the first sharp X-ray diffraction peak. Proper phase labeling is important for future machine learning efforts. We demonstrate that the fwhm and corrosion resistance are correlated but that, while chemistry still plays a role in corrosion resistance, a large fwhm, attributed to a glassy phase, is necessary for the highest corrosion resistance.