U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Search Publications by: Aaron Gilad Kusne (Fed)

Search Title, Abstract, Conference, Citation, Keyword or Author
Displaying 26 - 37 of 37

Scientific AI in Materials Science: a Path to a Sustainable and Scalable Paradigm

July 13, 2020
Author(s)
Brian DeCost, Jason Hattrick-Simpers, Zachary Trautt, Aaron Kusne, Martin L. Green, Eva Campo
Recent years have seen an ever-increasing trend in the use of machine learning (ML) and artificial intelligence (AI) methods by the materials science, condensed matter physics, and chemistry communities. This perspective article identifies key scientific

Materials Science in the AI age: high-throughput library generation, machine learning and a pathway from correlations to the underpinning physics

July 21, 2019
Author(s)
Kamal Choudhary, Aaron Kusne, Francesca Tavazza, Jason Hattrick-Simpers, Rama K. Vasudevan, Apurva Mehta, Ryan Smith, Lukas Vlcek, Sergei V. Kalinin, Maxim Ziatdinov
The use of advanced data analytics, statistical and machine learning approaches ('AI') to materials science has experienced a renaissance, driven by advances in computer sciences, availability and access of software and hardware, and a growing realization

An Inter-Laboratory Comparative High Throughput Experimental Materials Study of Zn-Sn-Ti-O Thin Films

March 19, 2019
Author(s)
Jason R. Hattrick-Simpers, Zachary T. Trautt, Kamal Choudhary, Aaron G. Kusne, Feng Yi, Martin L. Green, Sara Barron, Andriy Zakutayev, Nam Nguyen, Caleb Phillips, John Perkins, Ichiro Takeuchi, Apurva Mehta
High throughput experimental (HTE) techniques are an increasingly important way to accelerate the rate of materials research and development for many possible applications. However, there are very few publications on the reproducibility of the HTE results

Unsupervised phase mapping of X-ray diffraction data by nonnegative matrix factorization integrated with custom clustering

August 6, 2018
Author(s)
Valentin Stanev, Velimir Vesselinov, Aaron Gilad Kusne, Graham Antoszewski, Ichiro Takeuchi, Boian Alexandrov
Analyzing large X-ray diffraction (XRD) datasets is a key step in high-throughput mapping of the compositional phase diagrams of combinatorial materials libraries. Optimizing and automating this task can help accelerate the process of discovery of

Machine learning modeling of superconducting critical temperature

June 28, 2018
Author(s)
Aaron Gilad Kusne, Valentin Stanev, Ichiro Takeuchi
Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon remain poorly understood; prime among these is the connection between superconductivity and chemical
Was this page helpful?