Inverse Bioproduct Design Through Machine Learning and Molecular Simulation

Research output: NRELPresentation

Abstract

This work aims to identify performance advantaged bioproducts (PABPs) through computational property prediction. A major goal of this project is to guide targeted synthesis of polymers and small molecule materials to those that have the highest likelihood of performance advantages.
Original languageAmerican English
Number of pages32
StatePublished - 2023

Publication series

NamePresented at the 2023 U.S. Department of Energy's Bioenergy Technologies Office (BETO) Project Peer Review, 3-7 April 2023, Denver, Colorado

NREL Publication Number

  • NREL/PR-2800-85637

Keywords

  • BETO
  • machine learning
  • PABP
  • peer review
  • polymers
  • simulation

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