Abstract
AbstractWe employ statistical learning to present a principled framework for the establishment of quantitative structure‐property relationships (QSPR). We focus on property predictions of industrial polymers formed by multiple reagents and at varying molecular weights. We develop a theoretical description of QSPR as well as a rigorous mathematical method for the assimilation of experimental data. Results show that our methods can perform exceptionally well at establishing QSPR for glass transition temperature and intrinsic viscosity of polyesters.This article is protected by copyright. All rights reserved
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