549 citations · 754 across the 10 of their papers we have counts for
10 papers
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…
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…
Control of dopant crystallinity in electrochemically treated cuprate thin films
Alex Frano, Martin Bluschke, Zhijun Xu +16
We present a methodology based on \textit{ex-situ} (post-growth) electrochemistry to control the oxygen concentration in thin films of the superconducting oxide LaCuO g…
Ionic Tuning of Cobaltites at the Nanoscale
Dustin A. Gilbert, Alexander J. Grutter, Peyton D. Murray +13
Control of materials through custom design of ionic distributions represents a powerful new approach to develop future technologies ranging from spintronic logic and memory devices…
On-the-fly Data Assessment for High Throughput X-ray Diffraction Measurement
Fang Ren, Ronald Pandolfi, Douglas Van Campen +2
Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers ma…
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…