Issue 45, 2024

A multi-scale framework for predicting α-cyclodextrin assembly on polyethylene glycol axles

Abstract

Controlling the distribution of rings on polymer axles, such as α-cyclodextrin (αCD) on polyethylene glycol (PEG), is paramount in imparting robust mechanical properties to slide-ring gels and polyrotaxane-based networks. Previous experiments demonstrated that the functionalization of polymer ends could modulate the coverage of αCDs on PEG. To explore the design rule, we propose a multi-scale framework for predicting αCD assembly on bare and functionalized PEG. Our approach combines all-atom molecular dynamics with two-dimensional (2D) umbrella sampling to compute the free energy landscapes of threading αCDs onto PEG with ends functionalized by various moieties. Together with the predicted free energy landscapes and a lattice treatment for αCD and polymer diffusion in dilute solutions, we construct a kinetic Monte Carlo (kMC) model to predict the number and intra-chain distribution of αCDs along the polymer axle. Our model predicts the effects of chain length, concentration, and threading barrier on the supramolecular structure of end-functionalized polypseudorotaxane. With simple modifications, our approach can be extended to explore the design rule of polyrotaxane-based materials with advanced network architectures.

Graphical abstract: A multi-scale framework for predicting α-cyclodextrin assembly on polyethylene glycol axles

Supplementary files

Article information

Article type
Paper
Submitted
01 Sep 2024
Accepted
31 Oct 2024
First published
08 Nov 2024
This article is Open Access
Creative Commons BY-NC license

Soft Matter, 2024,20, 9068-9082

A multi-scale framework for predicting α-cyclodextrin assembly on polyethylene glycol axles

C. D. Smith, C. Ke and W. Zhang, Soft Matter, 2024, 20, 9068 DOI: 10.1039/D4SM01048E

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