High-Throughput Computational Framework for the Discovery of Structurally Diverse Monomers in High-Strength Aramid Fibers

High-performance aramid fibers are valued for exceptional strength and thermal stability, yet further improvement requires discovery of new monomer chemistries. We present a high-throughput computational framework that integrates cheminformatics filtering, molecular dynamics (MD) simulations, and an...

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Bibliographic Details
Main Author:	Hyeonsuk Yoo (10104409) (author)
Other Authors:	Ruth M. Muthoka (16858978) (author), Joonhyeok Park (14682373) (author), Dongjin Kim (2852660) (author), Xiangyu Zhang (630437) (author), Yongjin Lee (1428223) (author)
Published:	2025
Subjects:	Biophysics Biochemistry Medicine Neuroscience Space Science Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified structurally diverse monomers strong hydrogen bonding selected aramid polymers rigid bridging units performance aramid fibers new monomer chemistries integrates cheminformatics filtering enhanced intermolecular cohesion automated simulation interface polymer – polymer improvement requires discovery throughput polymer discovery throughput computational framework stronger interchain cohesion polymer classes ∼ 9 ∼ 29 versatile platform using technora thermal stability targeted ). systematically evaluated particularly amide nmp solvent nmp ). n </ molecular dynamics improved solubility heterocyclic cores exceptional strength dominant contributors containing systems broadly applicable although demonstrated >- methyl
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High-Throughput Computational Framework for the Discovery of Structurally Diverse Monomers in High-Strength Aramid Fibers

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