A Community Resource for Innovation in Polymer Technology (CRIPT)

Award ID: 2134795

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.

NSF Program Director: Michael Reksulak