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February 2026
Journal Article
Title
Insight into kinetic and diffusion phenomena in solvent-free poly(hydroxy-urethane) synthesis through applied step-growth modeling
Abstract
advancing the development of poly(hydroxy-urethane) (PHU) systems as sustainable alternatives to conventional, isocyanate-derived materials. In this work, we present an empirical model supporting the study of temperature- and conversion-dependent phenomena that influence PHU formation from oligomeric poly(propylene glycol)-based bis(cyclic carbonate) and short-chain 4,7,10-trioxa-1,13-tridecanediamine. For this purpose, the uncatalyzed synthesis experiments were conducted at 80-140 ◦C in a plate-plate rheometer, continuously monitoring the reaction in a melt through real-time viscosity measurements. Subsequent spectroscopic characterization verified that the dynamic rheological response can be ascribed to the formation of PHU materials free of side products. The resulting dataset was linked to molar mass evolution through a supplementary viscosity model and used to parameterize a step-growth polymerization model for cyclic carbonate aminolysis, integrating both mixing limitations at early stages and subsequent mass transfer phenomena. The model accurately reproduced experimental data in the low-temperature regime, demonstrating that linear step-growth with diffusion limitation adequately describes the reaction under given conditions and allows identification of physical effects
causing deviations in predictions at elevated temperatures. These results highlight that, beyond reaction kinetics, diffusion phenomena critically shape PHU polymerization behavior, determining temporal chain extension progress. Consequently, the proposed modeling framework enables the deconvolution of distinct reaction re-
gimes, providing crucial insight for optimizing PHU synthesis.
causing deviations in predictions at elevated temperatures. These results highlight that, beyond reaction kinetics, diffusion phenomena critically shape PHU polymerization behavior, determining temporal chain extension progress. Consequently, the proposed modeling framework enables the deconvolution of distinct reaction re-
gimes, providing crucial insight for optimizing PHU synthesis.
Author(s)
Open Access
File(s)
Rights
CC BY 4.0: Creative Commons Attribution
Language
English