English

Designing enhanced entropy binding in single-chain nano particles

Soft Condensed Matter 2022-07-26 v1 Disordered Systems and Neural Networks Statistical Mechanics

Abstract

Single-chain nanoparticles (SCNP) are a new class of bio and soft-matter polymeric objects in which a fraction of the monomers are able to form equivalently intra- or inter-polymer bonds. Here we numerically show that a fully-entropic gas-liquid phase separation can take place in SCNP systems. Control over the discontinuous (first-order) change -- from a phase of independent diluted (fully-bonded) polymers to a phase in which polymers entropically bind to each other to form a (fully-bonded) polymer network -- can be achieved by a judicious design of the patterns of reactive monomers along the polymer chain. Such a sensitivity arises from a delicate balance between the distinct entropic contributions controlling the binding.

Keywords

Cite

@article{arxiv.2207.12015,
  title  = {Designing enhanced entropy binding in single-chain nano particles},
  author = {Lorenzo Rovigatti and Francesco Sciortino},
  journal= {arXiv preprint arXiv:2207.12015},
  year   = {2022}
}

Comments

The submission also contains the SI

R2 v1 2026-06-25T01:11:45.320Z