Efficient sampling of reversible cross-linking polymers: Self-assembly of single-chain polymeric nanoparticles
Bernardo Oyarz\'un, Bortolo Matteo Mognetti

TL;DR
This paper introduces a novel Monte Carlo simulation method for efficiently modeling reversible cross-linking in polymers, enabling detailed study of self-assembly and morphology of single-chain polymeric nanoparticles with minimal configurational costs.
Contribution
A new simulation scheme that allows single-step binding/unbinding moves for reversible linkages, improving modeling of self-assembling polymer systems.
Findings
Reversible linkages influence nanoparticle size non-monotonically.
Regular functionalization affects chain morphology due to excluded volume effects.
Almost all reactive pairs interact at least once during simulations.
Abstract
We present a new simulation technique to study systems of polymers functionalized by reactive sites that bind/unbind forming reversible linkages. Functionalized polymers feature self-assembly and responsive properties that are unmatched by systems lacking selective interactions. The scales at which the functional properties of these materials emerge are difficult to model, especially in the reversible regime where such properties result from many binding/unbinding events. This difficulty is related to large entropic barriers associated with the formation of intra-molecular loops. In this work we present a simulation scheme that sidesteps configurational costs by dedicated Monte Carlo moves capable of binding/unbinding reactive sites in a single step. Cross-linking reactions are implemented by trial moves that reconstruct chain sections attempting, at the same time, a dimerization…
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