3 citations · 5 across the 4 of their papers we have counts for
5 papers
Accelerated Discovery of Molten Salt Corrosion-resistant Alloy by High-throughput Experimental and Modeling Methods Coupled to Data Analytics
Yafei Wang, Bonita Goh, Phalgun Nelaturu +10
Insufficient availability of molten salt corrosion-resistant alloys severely limits the fruition of a variety of promising molten salt technologies that could otherwise have signif…
On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning
A. Gilad Kusne, Heshan Yu, Changming Wu +13
Active learning - the field of machine learning (ML) dedicated to optimal experiment design, has played a part in science as far back as the 18th century when Laplace used it to gu…
Scientific AI in materials science: a path to a sustainable and scalable paradigm
Brian DeCost, Jason Hattrick-Simpers, Zachary Trautt +3
Recently there has been an ever-increasing trend in the use of machine learning (ML) and artificial intelligence (AI) methods by the materials science, condensed matter physics, an…
A high-throughput structural and electrochemical study of metallic glass formation in Ni-Ti-Al
Howie Joress, Brian L. DeCost, Suchismita Sarker +7
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…
On-the-fly Segmentation Approaches for X-ray Diffraction Datasets for Metallic Glasses
Fang Ren, Travis Williams, Jason Hattrick-Simpers +1
Investment in brighter sources and larger detectors has resulted in an explosive rise in the data collected at synchrotron facilities. Currently, human experts extract scientific i…