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Polymer expert – A software tool for de novo polymer design.

Authors :
Bicerano, Jozef
Rigby, David
Freeman, Clive
LeBlanc, Benoit
Aubry, Jason
Source :
Computational Materials Science. Feb2024, Vol. 235, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

[Display omitted] A versatile and user-friendly "expert system" for de novo polymer design, named Polymer Expert, has been developed and implemented. Polymer Expert can be used to rapidly generate novel candidate polymer repeat units to meet desired performance targets. It is anticipated to accelerate innovation through materials science in industries that use polymers and polymer matrix composites. It was implemented by (1) generating an initial repeat unit database, (2) expanding this initial database into a large analog repeat unit database, (3) performing calculations for all repeat units in the large analog database by using quantitative structure–property relationships (QSPR) of broad applicability, and (4) integrating the resulting searchable library of repeat units and their predicted properties (PEARL, acronym for Polymer Expert Analog Repeat-unit Library) as a new module in a materials modeling and simulation software suite. Its use is illustrated by identifying biobased alternatives for poly(ethylene terephthalate) (PET) and bisphenol-A polycarbonate (BPAPC), alternatives for highly crystalline polypropylene homopolymer (PPHP) and 10% glass fiber containing polypropylene (PP10GF), and polymers that may provide unusually high dielectric constants. Many promising candidates were unobvious and unlikely to have been identified without using a polymer informatics approach. Future work will focus on improving the quality of candidate repeat units by refining the QSPR method, enhancing the diversity of candidate repeat units by expanding PEARL, providing additional interactive search options, and converting Polymer Expert into a versatile R&D platform that users can customize for their own needs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09270256
Volume :
235
Database :
Academic Search Index
Journal :
Computational Materials Science
Publication Type :
Academic Journal
Accession number :
175455423
Full Text :
https://doi.org/10.1016/j.commatsci.2024.112810