A single-chain nanoparticle-based mean-field theory for associative polymers

Fuente: arXiv
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Main Authors: Cappa, Marco, Chiani, Stefano, Sciortino, Francesco, Rovigatti, Lorenzo
Format: Preprint
Published: 2025
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author Cappa, Marco
Chiani, Stefano
Sciortino, Francesco
Rovigatti, Lorenzo
author_facet Cappa, Marco
Chiani, Stefano
Sciortino, Francesco
Rovigatti, Lorenzo
contents Associative polymers are a class of polymers containing attractive stickers that can reversibly bind to each other. Their fully-bonded state gives rise, in dilute conditions, to a fluid phase of so-called single-chain nanoparticles (SCNPs). These constructs have been used in a wide range of applications, from the design of new materials (e.g. biomolecular condensates) to drug-delivery vectors. The thermodynamic properties of SCNPs sensitively depend on the number of different sticker types, since numerical simulations show that a continuous transition to a network of chains upon increase of polymer concentration in the single sticker-type case can be replaced by an abrupt network formation (via a first-order phase transition) in the multiple sticker-type case. We present here a theory that, using the SCNP fluid as the reference system, quantifies the free energy change associated with transferring an intra-molecular bond to an inter-molecular bond, elucidating the impact on the phase separation process of the sticker topology. Despite its simplicity, the theory highlights which microscopic assumptions (looping statistics, chain-level excluded volume) are most relevant for accurately capturing the thermodynamics of these systems. Our results match available numerical predictions obtained via coarse grained simulations of these systems, highlighting in particular the sensitivity of the phase behaviour on the sequence of the stickers along the chain.
format Preprint
id arxiv_https___arxiv_org_abs_2512_16405
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A single-chain nanoparticle-based mean-field theory for associative polymers
Cappa, Marco
Chiani, Stefano
Sciortino, Francesco
Rovigatti, Lorenzo
Soft Condensed Matter
Associative polymers are a class of polymers containing attractive stickers that can reversibly bind to each other. Their fully-bonded state gives rise, in dilute conditions, to a fluid phase of so-called single-chain nanoparticles (SCNPs). These constructs have been used in a wide range of applications, from the design of new materials (e.g. biomolecular condensates) to drug-delivery vectors. The thermodynamic properties of SCNPs sensitively depend on the number of different sticker types, since numerical simulations show that a continuous transition to a network of chains upon increase of polymer concentration in the single sticker-type case can be replaced by an abrupt network formation (via a first-order phase transition) in the multiple sticker-type case. We present here a theory that, using the SCNP fluid as the reference system, quantifies the free energy change associated with transferring an intra-molecular bond to an inter-molecular bond, elucidating the impact on the phase separation process of the sticker topology. Despite its simplicity, the theory highlights which microscopic assumptions (looping statistics, chain-level excluded volume) are most relevant for accurately capturing the thermodynamics of these systems. Our results match available numerical predictions obtained via coarse grained simulations of these systems, highlighting in particular the sensitivity of the phase behaviour on the sequence of the stickers along the chain.
title A single-chain nanoparticle-based mean-field theory for associative polymers
topic Soft Condensed Matter
url https://arxiv.org/abs/2512.16405