logo
ResearchBunny Logo
Abstract
This paper introduces RadonPy, an open-source library automating all-atom classical molecular dynamics (MD) simulations for calculating polymer properties. The library calculated 15 properties for over 1000 amorphous polymers, comparing MD results with experimental data from PoLyInfo for validation. Machine learning calibrated biases and variance in MD calculations. RadonPy identified eight polymers with exceptionally high thermal conductivity, highlighting the potential for advancing polymer informatics through database construction.
Publisher
npj Computational Materials
Published On
Nov 08, 2022
Authors
Yoshihiro Hayashi, Junichiro Shiomi, Junko Morikawa, Ryo Yoshida
Tags
RadonPy
molecular dynamics
polymer properties
machine learning
thermal conductivity
amorphous polymers
database construction

Related Publications

Explore these studies to deepen your understanding of the subject.

Accelerated discovery of molecular nanojunction photocatalysts for hydrogen evolution by using automated screening and flow synthesis
Chemistry

Accelerated discovery of molecular nanojunction photocatalysts for hydrogen evolution by using automated screening and flow synthesis

W. Zhang, M. Yu, et al.

Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations
Chemistry

Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations

S. Chen, T. Lin, et al.

Energetic and durable all-polymer aqueous battery for sustainable, flexible power
Engineering and Technology

Energetic and durable all-polymer aqueous battery for sustainable, flexible power

Y. Hong, K. Jia, et al.

Automated detection of intracranial aneurysms using skeleton-based 3D patches, semantic segmentation, and auxiliary classification for overcoming data imbalance in brain TOF-MRA
Medicine and Health

Automated detection of intracranial aneurysms using skeleton-based 3D patches, semantic segmentation, and auxiliary classification for overcoming data imbalance in brain TOF-MRA

S. Ham, J. Seo, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny