A high-throughput structural and electrochemical study of metallic glass formation in Ni-Ti-Al

Based on 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...

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Bibliographic Details
Published in:arXiv.org 2019-12
Main Authors: Howie Joress, DeCost, Brian L, Sarker, Suchismita, Braun, Trevor M, Jilani, Sidra, Smith, Ryan, Ward, Logan, Laws, Kevin J, Mehta, Apurva, Hattrick-Simpers, Jason
Format: Article
Language:English
Subjects:
Aluminum
Amorphous materials
Corrosion resistance
Electrochemical analysis
Glass formation
Machine learning
Metallic glasses
Nickel
Organic chemistry
Structural analysis
Titanium
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Summary:Based on 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-half-maximum (FWHM) of 0.42 A\(^{-1}\) for the first sharp x-ray diffraction peak. We demonstrate that the FWHM and corrosion resistance are correlated but that, while chemistry still plays a role, a large FWHM is necessary for the best corrosion resistance.
ISSN:2331-8422
DOI:10.48550/arxiv.1912.09330