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Search Publications by: Zachary Trautt (Fed)

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Displaying 1 - 16 of 16

Workshop Report on Autonomous Methodologies for Accelerating X-ray Measurements

November 5, 2024
Author(s)
Zachary Trautt, Austin McDannald, Brian DeCost, Howard Joress, A. Gilad Kusne, Francesca Tavazza, Tom Blanton
The National Institute of Standards and Technology and the International Centre for Diffraction Data co-hosted a workshop on 17-18 October 2023 to identify and prioritize the goals, challenges, and opportunities for critical and emerging technology needs

Driving U.S. Innovation in Materials and Manufacturing using AI and Autonomous Labs

August 14, 2024
Author(s)
Howie Joress, Zachary Trautt, Austin McDannald, Brian DeCost, A. Gilad Kusne, Francesca Tavazza
With the goal of advancing US competitiveness and excellence in the materials and manufacturing industries, we present our vision for the National Center for Autonomous Materials Science. The objective of this center is to enable and promote the use of

A Roadmap for LIMS at NIST Material Measurement Laboratory

April 11, 2022
Author(s)
Gretchen Greene, Jared Ragland, Zachary Trautt, June W. Lau, Raymond Plante, Joshua Taillon, Adam Abel Creuziger, Chandler A. Becker, Joe Bennett, Niksa Blonder, Lisa Borsuk, Carelyn E. Campbell, Adam Friss, Lucas Hale, Michael Halter, Robert Hanisch, Gary R. Hardin, Lyle E. Levine, Samantha Maragh, Sierra Miller, Chris Muzny, Marcus William Newrock, John Perkins, Anne L. Plant, Bruce D. Ravel, David J. Ross, John Henry J. Scott, Christopher Szakal, Alessandro Tona, Peter Vallone
Instrumentation generates data faster and in higher quantity than ever before, and interlaboratory research is in historic demand domestically and internationally to stimulate economic innovation. Strategic mission needs of the NIST Material Measurement

Towards improved FAIRness of the ThermoML Archive

February 28, 2022
Author(s)
Demian Riccardi, Zachary Trautt, Ala Bazyleva, Eugene Paulechka, Vladimir Diky, Joe W. Magee, Andrei F. Kazakov, Scott Townsend, Chris Muzny
The ThermoML archive is a subset of Thermodynamics Research Center (TRC) data holdings corresponding to cooperation between NIST TRC and five journals: Journal of Chemical Engineering and Data (ISSN: 0021-9568), The Journal of Chemical Thermodynamics (ISSN

FAIR Digital Object Demonstrators 2021

January 18, 2022
Author(s)
Peter Wittenburg, Ivonne Anders, Christophe Blanchi, Merret Buurman, Carole Goble, Jonas Grieb, Alex Hardisty, Sharif Islam, Thomas Jejkal, Tibor Kalman, Christine Kirkpatrick, Laurence Lannom, Thomas Lauer, Giridhar Manepalli, Karsten Peters-von Gehlen, Andreas Pfeil, Robert Quick, Mark van de Sanden, Ulrich Schwardmann, Stian Soiland-Reyes, Rainer Stotzka, Zachary Trautt, Dieter Van Uytvanck, Claus Weiland, Philipp Wieder
This paper gives a summary of implementation activities in the realm of FAIR Digital Objects (FDO). It gives an idea which software components are robust and used for many years, which components are comparatively new and are being tested out in pilot

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

November 12, 2020
Author(s)
Kamal Choudhary, Kevin Garrity, Andrew C. Reid, Brian DeCost, Adam Biacchi, Angela R. Hight Walker, Zachary Trautt, Jason Hattrick-Simpers, Aaron Kusne, Andrea Centrone, Albert Davydov, Francesca Tavazza, Jie Jiang, Ruth Pachter, Gowoon Cheon, Evan Reed, Ankit Agrawal, Xiaofeng Qian, Vinit Sharma, Houlong Zhuang, Sergei Kalinin, Ghanshyam Pilania, Pinar Acar, Subhasish Mandal, David Vanderbilt, Karin Rabe
The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques

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

July 14, 2020
Author(s)
Brian L. DeCost, Jason R. Hattrick-Simpers, Zachary T. Trautt, Aaron G. 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

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

Computational screening of high-performance optoelectronic materials using OptB88vdW and TB-mBJ formalisms

May 8, 2018
Author(s)
Kamal Choudhary, Qin Zhang, Sugata Chowdhury, Nhan V. Nguyen, Zachary T. Trautt, Marcus W. Newrock, Faical Y. Congo, Andrew C. Reid, Francesca M. Tavazza
We perform high-throughput density functional theory (DFT) calculations for optoelectronic properties (electronic bandgap and frequency dependent dielectric function) using the OptB88vdW functional (OPT) and the Tran-Blaha modified Becke Johnson potential

An Informatics Infrastructure for the Materials Genome Initiative

July 6, 2016
Author(s)
Alden A. Dima, Sunil K. Bhaskarla, Chandler A. Becker, Mary C. Brady, Carelyn E. Campbell, Philippe J. Dessauw, Robert J. Hanisch, Ursula R. Kattner, Kenneth G. Kroenlein, Adele P. Peskin, Raymond L. Plante, Guillaume Sousa Amaral, Zachary T. Trautt, James A. Warren, Sharief S. Youssef, Sheng Yen Li, Pierre Francois Rigodiat, Marcus W. Newrock
A materials data infrastructure that enables the sharing and transformation of a wide range of materials data is an essential part of achieving the goals of the Materials Genome Initiative. We describe two high-level requirements of such an infrastructure