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Research Spending & Results

Award Detail

Doing Business As Name:Massachusetts Institute of Technology
  • Bradley D Olsen
  • (617) 253-1000
  • Klavs F Jensen
  • Regina Barzilay
  • Kenneth G Kroenlein
  • Kaoru Aou
Award Date:09/15/2021
Estimated Total Award Amount: $ 5,000,000
Funds Obligated to Date: $ 2,586,439
  • FY 2021=$2,586,439
Start Date:10/01/2021
End Date:09/30/2023
Transaction Type: Cooperative Agreements
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.083
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:NSF Convergence Accelerator Track D: A Community Resource for Innovation in Polymer Technology (CRIPT)
Federal Award ID Number:2134795
DUNS ID:001425594
Parent DUNS ID:001425594
Program:Convergence Accelerator Resrch
Program Officer:
  • Mike Pozmantier
  • (703) 292-4475

Awardee Location

Awardee Cong. District:07

Primary Place of Performance

Organization Name:Massachusetts Institute of Technology
Cong. District:07

Abstract at Time of Award

Polymer materials, ranging from clothing and personal protective equipment to construction materials and food packaging, are fundamental to providing for our basic needs for food, shelter, health, and transportation. However, developing new polymers for next-generation products takes decades, and we must move faster to remain competitive. To accelerate this process, this project is developing CRIPT, a polymer data ecosystem consisting of a web-based application and cloud database that allow polymer scientists to easily find, archive, and interact with complex polymer data. AI-driven chemistry tools and data-driven workflows within CRIPT will reduce the development time for polymer materials by an order of magnitude, creating a transformative impact on both the producers and buyers of the nearly $600 billion of polymers sold each year. Currently, searching among existing polymers is a daunting task because polymer data exists as small, disparate sets, making the navigation a complex process combining the harmonization of different data formats and the reconciliation of metadata, both of which currently require expert intervention. CRIPT offers a cloud database based on a new polymer-specific data model that simultaneously provides interoperability across different domains of polymer science and engineering, while retaining critical metadata that allows domain experts to correlate information across many independent records. A series of chemically-inspired AI innovations, including a chemistry-based query language, a graph-based schema preserving temporal structure in data, algorithms for automatic data validation, AI-human cooperative tools for data ingestion, and the integration of machines into the data ecosystem are also provided to add FAIR principles, trust in data, and ease of use to the system. 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.

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