Advanced computation and data approaches provide the potential for game-changing breakthroughs in science, engineering, and technology. Advanced Computation and Data in Materials and Manufacturing: Core Knowledge Gaps and Opportunities specifically focuses on determining the gaps in core knowledge that, if fulfilled, would enable transformative science and engineering breakthroughs within the materials and manufacturing arenas.
Study Features
- Examines the core knowledge required to fully realize the potential of advanced computational and data-enabled research.
- Identifies 38 technical gaps, and provides detailed discussion and action plans to close the six highest priority gaps.
- Provides broad recommendations that address overarching cultural and community issues, including a lack of cross-disciplinary collaboration and inadequate training opportunities.
- Offers guidance on how individuals, groups, and organizations can proactively address infrastructure, education, and training needs.
- Presents case studies to introduce how groups are currently addressing knowledge gap areas, as well as illustrating some of their ongoing challenges.
This study was conducted by TMS on behalf of the U.S. National Science Foundation.
Resources for Sharing Study Content
- Suggested Citation: The Minerals, Metals & Materials Society (TMS), Advanced Computation and Data in Materials and Manufacturing: Core Knowledge Gaps and Opportunities (Pittsburgh, PA: TMS, 2018). Electronic copies available at www.tms.org/coreknowledge
Workshop Plenary Presentations
"Digitization of Materials Innovation in support of Advanced Manufacturing"
Surya Kalidindi
Georgia Institute of Technology
"Advanced Computing for Materials and Manufacturing"
Somnath Ghosh
Johns Hopkins University
"Manufacturing and Uncertainty"
Tony Schmitz
University of North Carolina, Charlotte
Workshop Participants
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Pinar Acar
Virginia Polytechnic and State University
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Ankit Agrawal
Northwestern University
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Raymundo Arroyave
Texas A&M University
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Mohsen Asle Zaeem
Missouri University of Science & Technology
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Marco Buongiorno Nardelli
University of North Texas
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Jennifer Carter
Case Western Reserve University
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Wei Chen
Northwestern University
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Kevin Chou
University of Louisville
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Joanne Culbertson
U.S. National Science Foundation
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Gregory Deirlein
Stanford University
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Roger Ghanem
University of Southern California
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Somnath Ghosh
Johns Hopkins University
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Louis Hector
General Motors Global R&D
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Zubaer Hossain
University of Delaware
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Surya Kalidindi
Georgia Institute of Technology
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Marko Knezevic
University of New Hampshire
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Alexis Lewis
U.S. National Science Foundation
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Bin Li
University of Nevada, Reno
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Bo Li
Case Western Reserve University
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Gang Li
Clemson University
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Xiaochun Li
University of California, Los Angeles
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Zi-Kui Liu
Pennsylvania State University
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Turab Lookman
Los Alamos National Laboratory
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Marianna Maiaru
University of Massachusetts, Lowell
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David McDowell
Georgia Institute of Technology
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Caglar Oskay
Vanderbilt University
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Siddiq Qidwai
U.S. National Science Foundation
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Tony Schmitz
University of North Carolina, Charlotte
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Alejandro Strachan
Purdue University
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Wai Ching Sun
Columbia University
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Veera Sundararaghavan
University of Michigan
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Yan Wang
Georgia Institute of Technology
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Ji-Cheng Zhao
The Ohio State University
Planning Team
David L McDowell, Team Co-Chair
Georgia Institute of Technology
Veera Sundararaghavan, Team Co-Chair
University of Michigan
Raymundo Arroyave
Texas A&M University
Tony Schmitz
University of North Carolina, Charlotte
Michael Tonks
University of Florida
Related TMS Studies
- Harnessing Materials Innovations to Support Next Generation Manufacturing Technologies, March 2018, TMS
- Building a Materials Data Infrastructure: Opening New Pathways to Discovery and Innovation in Science and Engineering, May 2017, TMS
- Modeling Across Scales: A Roadmapping Study for Connecting Materials Models and Simulations Across Length and Time Scales, May 2015, TMS
- Implementing Integrated Computational materials Engineering (ICME) in the Aerospace, Automotive, and Maritime Industries, July 2013, TMS