@article{3eeda7a4d3c94aecab4f5bbaf088bb0e,
title = "Kinetic Monte Carlo Tool for Kinetic Modeling of Linear Step-Growth Polymerization: Insight into Recycling of Polyurethanes",
abstract = "A kinetic Monte Carlo model of polyurethane polymerization which explicitly tracks the polymer sequences is developed and shared. This model is benchmarked against theoretical and experimental polyurethane data and used to investigate the effect on oligomer distributions of unequal reactivity of the first and second isocyanate to react. The reverse reactions using thermodynamic consistency are then added to the framework, and analogous to the addition polymerization concept of ceiling temperature, equilibrium chain length distributions at various temperatures are calculated. For a mixture of three monomers AA, BB, and CC, where BB and CC do not react with one another, are present in stoichiometric proportions, and have different enthalpies of reaction with AA, an odd-even effect emerges. Odd length chains are more likely than even length chains for temperatures at which BB and CC have significantly different equilibrium conversions. The concept of ceiling temperature that is typically cited for addition polymers is extended here to provide a measure of conditions under which depolymerization for recycling is favored.",
keywords = "ceiling temperature, condensation polymerization, kinetic Monte Carlo, kinetic modeling, pathways-level model, polyaddition, polyurethanes, step growth polymerization",
author = "Coile, {Matthew W.} and Harmon, {Rebecca E.} and Guanhua Wang and Gorugantu SriBala and Broadbelt, {Linda J.}",
note = "Funding Information: This material is based upon work supported by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Bioenergy Technologies Office Award No. DE-EE0008928. Support of the Institute for Sustainability and Energy (ISEN) at Northwestern University is also gratefully acknowledged. M.C. gratefully acknowledges support from the Ryan Fellowship and the International Institute for Nanotechnology at Northwestern University. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1842165. Financial support from the National Science Foundation (NSF) Partnerships for International Research and Education (PIRE) program under Grant No. 1743748 is also gratefully acknowledged. This work was performed as part of the BOTTLE Consortium, which includes members from Northwestern University, and funded under Contract No. DE-AC36-08GO28308 with the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy. Funding Information: This material is based upon work supported by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Bioenergy Technologies Office Award No. DE‐EE0008928. Support of the Institute for Sustainability and Energy (ISEN) at Northwestern University is also gratefully acknowledged. M.C. gratefully acknowledges support from the Ryan Fellowship and the International Institute for Nanotechnology at Northwestern University. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE‐1842165. Financial support from the National Science Foundation (NSF) Partnerships for International Research and Education (PIRE) program under Grant No. 1743748 is also gratefully acknowledged. This work was performed as part of the BOTTLE Consortium, which includes members from Northwestern University, and funded under Contract No. DE‐AC36‐08GO28308 with the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy. Publisher Copyright: {\textcopyright} 2021 Wiley-VCH GmbH.",
year = "2022",
month = mar,
doi = "10.1002/mats.202100058",
language = "English (US)",
volume = "31",
journal = "Macromolecular Theory and Simulations",
issn = "1022-1344",
publisher = "Wiley-VCH Verlag",
number = "2",
}