Polymer informatics: Current status and critical next steps

Chen, Lihua; Pilania, Ghanshyam; Batra, Rohit; Huan, Tran Doan; Kim, Chiho; Kuenneth, Christopher; Ramprasad, Rampi

doi:10.1016/j.mser.2020.100595

Polymer informatics: Current status and critical next steps

Journal Article · Sat Dec 26 04:00:00 EST 2020 · Materials Science and Engineering. R, Reports

DOI:https://doi.org/10.1016/j.mser.2020.100595· OSTI ID:1825409

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Georgia Inst. of Technology, Atlanta, GA (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Argonne National Lab. (ANL), Argonne, IL (United States). Center for Nanoscale Materials

Artificial intelligence (AI) based approaches are beginning to impact several domains of human life, science and technology. Polymer informatics is one such domain where AI and machine learning (ML) tools are being used in the efficient development, design and discovery of polymers. Surrogate models are trained on available polymer data for instant property prediction, allowing screening of promising polymer candidates with specific target property requirements. Questions regarding synthesizability, and potential (retro)synthesis steps to create a target polymer, are being explored using statistical means. Data-driven strategies to tackle unique challenges resulting from the extraordinary chemical and physical diversity of polymers at small and large scales are being explored. Other major hurdles for polymer informatics are the lack of widespread availability of curated and organized data, and approaches to create machine-readable representations that capture not just the structure of complex polymeric situations but also synthesis and processing conditions. Methods to solve inverse problems, wherein polymer recommendations are made using advanced AI algorithms that meet application targets, are being investigated. As various parts of the burgeoning polymer informatics ecosystem mature and become integrated, efficiency improvements, accelerated discoveries and increased productivity can result. Here in this paper, we review emergent components of this polymer informatics ecosystem and discuss imminent challenges and opportunities.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1825409

Alternate ID(s):: OSTI ID: 1831182
OSTI ID: 1781277

Report Number(s):: LA-UR--20-27820

Journal Information:: Materials Science and Engineering. R, Reports, Journal Name: Materials Science and Engineering. R, Reports Vol. 144; ISSN 0927-796X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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