Issue 41, 2016

Tracer diffusion in a sea of polymers with binding zones: mobile vs. frozen traps

Abstract

We use molecular dynamics simulations to investigate the tracer diffusion in a sea of polymers with specific binding zones for the tracer. These binding zones act as traps. Our simulations show that the tracer can undergo normal yet non-Gaussian diffusion under certain circumstances, e.g., when the polymers with traps are frozen in space and the volume fraction and the binding strength of the traps are moderate. In this case, as the tracer moves, it experiences a heterogeneous environment and exhibits confined continuous time random walk (CTRW) like motion resulting in a non-Gaussian behavior. Also the long time dynamics becomes subdiffusive as the number or the binding strength of the traps increases. However, if the polymers are mobile then the tracer dynamics is Gaussian but could be normal or subdiffusive depending on the number and the binding strength of the traps. In addition, with increasing binding strength and number of polymer traps, the probability of the tracer being trapped increases. On the other hand, removing the binding zones does not result in trapping, even at comparatively high crowding. Our simulations also show that the trapping probability increases with the increasing size of the tracer and for a bigger tracer with the frozen polymer background the dynamics is only weakly non-Gaussian but highly subdiffusive. Our observations are in the same spirit as found in many recent experiments on tracer diffusion in polymeric materials and question the validity of using Gaussian theory to describe diffusion in a crowded environment in general.

Graphical abstract: Tracer diffusion in a sea of polymers with binding zones: mobile vs. frozen traps

Article information

Article type
Paper
Submitted
23 Aug 2016
Accepted
20 Sep 2016
First published
21 Sep 2016

Soft Matter, 2016,12, 8554-8563

Tracer diffusion in a sea of polymers with binding zones: mobile vs. frozen traps

N. Samanta and R. Chakrabarti, Soft Matter, 2016, 12, 8554 DOI: 10.1039/C6SM01943A

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