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
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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.
期刊介绍:
The Journal of Combinatorial Chemistry has been relaunched as ACS Combinatorial Science under the leadership of new Editor-in-Chief M.G. Finn of The Scripps Research Institute. The journal features an expanded scope and will build upon the legacy of the Journal of Combinatorial Chemistry, a highly cited leader in the field.