Issue 31, 2024

A Monte Carlo simulation of tracer diffusion in amorphous polymers

Abstract

Tracer diffusion in amorphous polymers is a sought-after quantity for a range of technological applications. In this regard, a quantitative description of the so-called decoupling from the reverse proportionality between viscosity and diffusion coefficient into a fractional one remains a challenge requiring a deeper insight. This work employs a Monte Carlo simulation framework in 3 dimensions to investigate the consequences of different scenarios for estimating this fractional exponent on the diffusion coefficient of tracers in polymers near glass transition. To this end, we adopted a continuous-time random walk model for tracer diffusion in the supercooled liquid state. The waiting time distribution of the diffusants was computed based on the rotational correlation times of the polymer. This proposed procedure is of particular interest because it brings the quantity of waiting time (and its statistics) in connection with the measurable observable of rotational times. In the framework of our simulations the aforementioned fractional exponent appears in the relation between the diffusant's waiting time and the rotational time of the diffusion medium. A limited comparison with experimental diffusivities from the literature revealed a reasonable agreement with a fractional exponent on the basis of the molar volumes of the diffusant and the monomeric unit. Finally, an analysis of time-averaged mean squared displacement pointed to normal Brownian dynamics for tracer diffusion in polymers above the glass transition temperature.

Graphical abstract: A Monte Carlo simulation of tracer diffusion in amorphous polymers

Supplementary files

Article information

Article type
Paper
Submitted
26 Jun 2024
Accepted
15 Jul 2024
First published
24 Jul 2024
This article is Open Access
Creative Commons BY license

Soft Matter, 2024,20, 6204-6214

A Monte Carlo simulation of tracer diffusion in amorphous polymers

A. Mansuri, P. Vora, T. Feuerbach, J. Winck, A. W. P. Vermeer, W. Hoheisel, J. Kierfeld and M. Thommes, Soft Matter, 2024, 20, 6204 DOI: 10.1039/D4SM00782D

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