CITATION.bib

cff-version: 1.2.0
title: >-
  Bioplastic Design using Multitask Deep Neural
  Networks
abstract: Non-degradable plastic waste stays for decades on land and in water, jeopardizing our environment; yet our modern lifestyle and current technologies are impossible to sustain without plastics. Bio-synthesized and biodegradable alternatives such as the polymer family of polyhydroxyalkanoates (PHAs) have the potential to replace large portions of the world's plastic supply with cradle-to-cradle materials, but their chemical complexity and diversity limit traditional resource-intensive experimentation. In this work, we develop multitask deep neural network property predictors using available experimental data for a diverse set of nearly 23000 homo- and copolymer chemistries. Using the predictors, we identify 14 PHA-based bioplastics from a search space of almost 1.4 million candidates which could serve as potential replacements for seven petroleum-based commodity plastics that account for 75% of the world's yearly plastic production. We discuss possible synthesis routes for these identified promising materials. The developed multitask polymer property predictors are made available as a part of the Polymer Genome project at https://www.polymergenome.org/.
message: Please cite the paper using these metadata.
type: article
authors:
  - family-names: Kuenneth
    given-names: Christopher
    email: christopher.kuenneth@gmail.com
    orcid: 'https://orcid.org/0000-0002-6958-4679'
    affiliation: Georgia Institute of Technology, Los Alamos National Laboratory
  - family-names: Lalonde
    given-names: Jessica
    affiliation: "Los Alamos National Laboratory, Duke University"
  - family-names: Marrone
    given-names: Babetta L.
    affiliation: Los Alamos National Laboratory
  - family-names: Iverson
    given-names: Carl N. 
    affiliation: Los Alamos National Laboratory
  - family-names: Ramprasad
    given-names: Rampi
    affiliation: Georgia Institute of Technology
  - family-names: Pilania
    given-names: Ghanshyam
    affiliation: Los Alamos National Laboratory

identifiers:
  - description: arXiv
    type: doi
    value: 10.48550/ARXIV.2203.12033

repository-code: https://github.com/Ramprasad-Group/bioplastic_design