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Award Abstract # 2320276
Equipment: MRI: Track 2 Acquisition of an Automated High-Throughput System for Combinatorial Design and Development of Complex Polymer Systems

NSF Org: DMR
Division Of Materials Research
Recipient: UNIVERSITY OF ILLINOIS
Initial Amendment Date: September 13, 2023
Latest Amendment Date: September 13, 2023
Award Number: 2320276
Award Instrument: Standard Grant
Program Manager: Guebre Tessema
gtessema@nsf.gov
 (703)292-4935
DMR
 Division Of Materials Research
MPS
 Directorate for Mathematical and Physical Sciences
Start Date: September 1, 2023
End Date: August 31, 2026 (Estimated)
Total Intended Award Amount: $3,596,000.00
Total Awarded Amount to Date: $3,596,000.00
Funds Obligated to Date: FY 2023 = $3,596,000.00
History of Investigator:
  • Charles Schroeder (Principal Investigator)
    cms@illinois.edu
  • Nancy Sottos (Co-Principal Investigator)
  • Sameh Tawfick (Co-Principal Investigator)
  • Daniel Krogstad (Co-Principal Investigator)
  • Ying Diao (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Illinois at Urbana-Champaign
506 S WRIGHT ST
URBANA
IL  US  61801-3620
(217)333-2187
Sponsor Congressional District: 13
Primary Place of Performance: University of Illinois at Urbana-Champaign
506 S WRIGHT ST
URBANA
IL  US  61801-3620
Primary Place of Performance
Congressional District:
13
Unique Entity Identifier (UEI): Y8CWNJRCNN91
Parent UEI: V2PHZ2CSCH63
NSF Program(s): Major Research Instrumentation,
OFFICE OF MULTIDISCIPLINARY AC,
MPS DMR INSTRUMENTATION,
Chemical Instrumentation
Primary Program Source: 01002324DB NSF RESEARCH & RELATED ACTIVIT
01AB2324DB R&RA DRSA DEFC AAB
Program Reference Code(s): 054Z, 094Z, 095Z, 7573
Program Element Code(s): 118900, 125300, 175000, 193800
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.049, 47.083

ABSTRACT

This Major Research Instrumentation (MRI) award supports the acquisition of an automated system for high-throughput formulation and characterization of complex polymer materials at the University of Illinois at Urbana-Champaign. This state-of-the-art system integrates component dispensing, mixing, and processing with high-throughput rheological, optical, and thermal characterization of materials. The automated system will enable AI-guided, closed-loop approaches for the design, discovery, and development of new polymeric materials for energy-efficient manufacturing, multi-functional polymers, and new sustainable thermoplastics and thermosets. The automated system is designed to accommodate a variety of research workflows and will include in-line characterization equipment including a rheometer and a differential scanning calorimeter (DSC). Automation will enable data-driven discovery of new materials by drastically increasing the number of samples created and analyzed (up to 50x increase) and the data usability (up to 100x increase) by systematically generating annotated datasets. Production of well-curated data will further increase the impact of the research by promoting the publishing of data to open access national repositories. The instrument will promote synergistic connections between Illinois and external academic and industrial partners while leveraging existing institutes and materials research efforts on campus. Overall, the high-throughput system will fundamentally change how advanced materials are designed and developed by enabling data-driven, closed-loop design and characterization approaches for complex formulations of polymeric materials.

This research is aimed at advancing the rate of innovation in materials discovery by enabling data-driven approaches in polymer science. The proposed instrumentation will support the training of students and researchers to include high-throughput, robotic, and data-driven methodologies, which is critical for modern industry and advanced materials manufacturing. Automated instrumentation fundamentally changes how materials research is conducted by enabling high-throughput discovery campaigns, enhanced repeatability of experimental measurements, and improved accuracy of data. Automated characterization will further facilitate the use of artificial intelligence-based methods for materials discovery by greatly expanding the chemical and physical properties space that can be experimentally explored. This research will enable the rapid discovery and development of high-performance polymer materials to address the most pressing challenges in energy, sustainability, and advanced manufacturing. This instrumentation will bring unique capabilities by accelerating fundamental and applied polymer research, while further preparing the next-generation work force for future careers in materials science, chemical engineering, aerospace, data science, and related disciplines that rely on polymer materials. The instrument will support educational outreach efforts and undergraduate research laboratories while further engaging with students in the Worldwide Youth in Science and Engineering (WYSE) camps and the Beckman Institute Open House activities.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Please report errors in award information by writing to: awardsearch@nsf.gov.

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