Application and comparison of derivative-free optimization algorithms to control and optimize free radical polymerization simulated using the kinetic Monte Carlo method

Hanyu Gao, Andreas Waechter, Ivan A. Konstantinov, Steven G. Arturo, Linda J Broadbelt*

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

The diversity of the potential arrangements of multiple monomers along the length of polymer chains and their impact on polymer properties spark interest in the design of polymer sequence characteristics for particular applications. Kinetic Monte Carlo (KMC) is a technique that can track the explicit arrangement of monomers in the polymer chains, yet it is difficult to integrate with conventional gradient-based optimization algorithms that are typically invoked to design polymer properties. In this work, we applied and compared derivative-free optimization algorithms to incorporate KMC simulations and find synthesis conditions for achieving property targets and minimizing reaction time, advancing our ability to carry out the design of polymer microstructures and control polymerization processes.

Original languageEnglish (US)
Pages (from-to)268-275
Number of pages8
JournalComputers and Chemical Engineering
Volume108
DOIs
StatePublished - Jan 4 2018

Keywords

  • Derivative-free optimization
  • Kinetic Monte Carlo
  • Polymer
  • Sequence

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Application and comparison of derivative-free optimization algorithms to control and optimize free radical polymerization simulated using the kinetic Monte Carlo method'. Together they form a unique fingerprint.

  • Cite this