Machine learning glass transition temperature of polyacrylamides using quantum chemical descriptors

Yu-Zhong Zhang; Xiaojie Xu

doi:10.1039/d0py01581d

journal article Jan 01, 2021

Machine learning glass transition temperature of polyacrylamides using quantum chemical descriptors

Yu-Zhong Zhang

Xiaojie Xu

Polymer Chemistry Vol. 12 No. 6 pp. 843-851 · Royal Society of Chemistry (RSC)

View at Publisher Save 10.1039/d0py01581d

Abstract

Polyacrylamides glass transition temperature predictions from different models, where the GPR model is from the current study. The GPR model based on quantum chemical descriptors shows a high degree of accuracy.

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References

Details

Published: Jan 01, 2021
Vol/Issue: 12(6)
Pages: 843-851
License: View

Authors

Y

Yu-Zhong Zhang

North Carolina State University; Raleigh; USA

X

Xiaojie Xu

North Carolina State University; Raleigh; USA

Cite This Article

Yu-Zhong Zhang, Xiaojie Xu (2021). Machine learning glass transition temperature of polyacrylamides using quantum chemical descriptors. Polymer Chemistry, 12(6), 843-851. https://doi.org/10.1039/d0py01581d

Machine learning glass transition temperature of polyacrylamides using quantum chemical descriptors

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