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Community Resource for Innovation in Polymer Technology (CRIPT): A Scalable Polymer Material Data Structure

Published

Author(s)

Dylan Walsh, Weizhong Zou, Ludwig Schneider, Reid Mello, Michael Deagen, Joshua Mysona, Tzyy-Shyang Lin, Juan de Pablo, Klavs Jensen, Debra Audus, Bradley Olsen

Abstract

Polymeric materials are integral components of nearly every aspect of modern life. However, developing cheminformatic solutions for polymers has been difficult since they are large stochastic molecules with hierarchical structures spanning multiple length scales. Here we present the design for a general material data model that underpins the Community Resource for Innovation in Polymer Technology (CRIPT) data ecosystem.
Citation
ACS Central Science

Keywords

Data models, FAIR data, Chemical structure, Copolymers, Materials, Polymers, Separation science

Citation

Walsh, D. , Zou, W. , Schneider, L. , Mello, R. , Deagen, M. , Mysona, J. , Lin, T. , de Pablo, J. , Jensen, K. , Audus, D. and Olsen, B. (2023), Community Resource for Innovation in Polymer Technology (CRIPT): A Scalable Polymer Material Data Structure, ACS Central Science, [online], https://doi.org/10.1021/acscentsci.3c00011, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935334 (Accessed October 7, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created February 20, 2023, Updated February 22, 2023