Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities

Deguire, Eileen; Bartolo, Laura; Brindle, Ross; Devanathan, Ram; Dickey, Elizabeth; Fessler, Justin; French, Roger H.; Fotheringham, Ulrich; Harmer, Martin P.; Lara-Curzio, Edgar; Lichtner, Sara; Maillet, Emmanuel; Mauro, John; Mecklenborg, Mark; Meredig, Bryce; Rajan, Krishna; Rickman, Jeffrey M.; Sinnott, Susan B.; Spahr, Charlie; Suh, Changwon; Tandia, Adama; Ward, Logan; Weber, Richard

doi:10.1111/jace.16677

Data-driven glass/ceramic science research: Insights from the glass and ceramic and data science/informatics communities

Journal Article · Fri Nov 01 04:00:00 EDT 2019 · Journal of the American Ceramic Society

DOI:https://doi.org/10.1111/jace.16677· OSTI ID:1572500

Deguire, Eileen ^[1]; Bartolo, Laura ^[2]; Brindle, Ross ^[3]; ^[4]; Dickey, Elizabeth ^[5]; Fessler, Justin ^[6]; French, Roger H. ^[7]; Fotheringham, Ulrich ^[8]; Harmer, Martin P. ^[9]; Lara-Curzio, Edgar ^[10]; Lichtner, Sara ^[3]; Maillet, Emmanuel ^[6]; Mauro, John ^[11]; Mecklenborg, Mark ^[1]; Meredig, Bryce ^[12]; Rajan, Krishna ^[13]; Rickman, Jeffrey M. ^[9]; Sinnott, Susan B. ^[11]; Spahr, Charlie ^[1]; Suh, Changwon ^[3] more »

The American Ceramic Society
Kent State University
Nexight Group
BATTELLE (PACIFIC NW LAB)
North Carolina State University
IBM
DuPont Central Research
Schott
Lehigh University
Oak Ridge National Laboratory
Pennsylvania State University
Citrine IO
Iowa State University
Corning
University of Chicago
Materials Development, Inc.

Data-driven science and technology have helped achieve meaningful results in areas such as materials/drug discovery and health care, but efforts to apply high-end data science algorithms to the areas of glass and ceramics are still limited. Many glass and ceramic researchers are interested in enhancing their work by using more data and data analytics to efficiently develop better functional materials. Simultaneously, the data science community is looking for a way to access materials data resources to test and validate their advanced computational learning algorithms. To bring together the glass/ceramic and data science communities to address this issue, The American Ceramic Society (ACerS) convened a Glass/Ceramics Data Science Workshop on February 6, 2018, at Nexight Group offices in Silver Spring, Maryland. The workshop, sponsored by the National Institute for Standards and Technology (NIST) Advanced Manufacturing Technologies (AMTech) program, brought together a select group of 20 key leaders in the data science, informatics, and glass/ceramics communities to identify the greatest opportunities and mechanisms for facilitating increased collaboration and coordination between these communities. This article summarizes workshop discussions about the current challenges that limit interactions and collaboration between the glass/ceramic and data science communities, opportunities for a coordinated approach that leverages existing knowledge in both communities, and a clear path toward the enhanced use of data science technologies for functional glass and ceramic research and development.

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

DOE Contract Number:: AC05-76RL01830

OSTI ID:: 1572500

Report Number(s):: PNNL-SA-136773

Journal Information:: Journal of the American Ceramic Society, Journal Name: Journal of the American Ceramic Society Journal Issue: 11 Vol. 102

Country of Publication:: United States

Language:: English

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