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Main Authors: Chahal-Crockett, Rajni, Toomey, Michael D., Kearney, Logan T., Gao, Yawei, Damron, Joshua T., Naskar, Amit K., Roy, Santanu
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.24798
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author Chahal-Crockett, Rajni
Toomey, Michael D.
Kearney, Logan T.
Gao, Yawei
Damron, Joshua T.
Naskar, Amit K.
Roy, Santanu
author_facet Chahal-Crockett, Rajni
Toomey, Michael D.
Kearney, Logan T.
Gao, Yawei
Damron, Joshua T.
Naskar, Amit K.
Roy, Santanu
contents Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li+, by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH- dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li+-coupled electron transfer along the PAN backbone, causing ~10,000 times faster sequential ring-formation of the remaining nitriles. PAN's extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.
format Preprint
id arxiv_https___arxiv_org_abs_2603_24798
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials
Chahal-Crockett, Rajni
Toomey, Michael D.
Kearney, Logan T.
Gao, Yawei
Damron, Joshua T.
Naskar, Amit K.
Roy, Santanu
Materials Science
Chemical Physics
Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li+, by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH- dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li+-coupled electron transfer along the PAN backbone, causing ~10,000 times faster sequential ring-formation of the remaining nitriles. PAN's extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.
title Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials
topic Materials Science
Chemical Physics
url https://arxiv.org/abs/2603.24798