Evidence map›Paper›PMID 39726392›Full record

ArticleMacromolecular rapid communications2025

The Intramolecular Self-Assembly of Statistical Copolymers in Aqueous Solution to Form Anisotropic Single-Chain Nanoparticles with Tunable Aspect Ratio.

Thomas J Neal, Rebecca E Stone, Csilla György, Svetomir B Tzokov, Sebastian G Spain, Oleksandr O Mykhaylyk

Abstract read
In one paragraph

Article in Macromolecular rapid communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Thomas J NealSchool of Mathematical and Physical Sciences, University of Sheffield, Dainton Building, Sheffield, S3 7HF, UK.
Rebecca E StoneICON, 500 South Oak Way, Green Park, Reading, RG2 6AG, UK.
Csilla GyörgySchool of Mathematical and Physical Sciences, University of Sheffield, Dainton Building, Sheffield, S3 7HF, UK.
Svetomir B TzokovSchool of Biosciences, University of Sheffield, Firth Court, Western Bank, Sheffield, S10 2TN, UK.
Sebastian G SpainSchool of Mathematical and Physical Sciences, University of Sheffield, Dainton Building, Sheffield, S3 7HF, UK.
Oleksandr O MykhaylykSchool of Mathematical and Physical Sciences, University of Sheffield, Dainton Building, Sheffield, S3 7HF, UK.ORCID https://orcid.org/0000-0003-4110-8328

Funding

AkzoNobel (Slough, UK)Engineering and Physical Sciences Research Council EP/L016281/1Engineering and Physical Sciences Research Council EP/M028437/1Engineering and Physical Sciences Research Council EP/V034804/1
6 · The paper itself

Abstract

Natural single-chain nanoparticles (SCNPs) such as proteins have inspired research into the formation and application of synthetic SCNPs. Although the latter can mimic general aspects of the self-assembly behavior of their biological counterparts, these systems remain relatively understudied. In this respect, a systematic series of amphiphilic statistical copolymers (ASC) of different molecular weights, with a hydrophilic comonomer (methacrylic acid) and varying hydrophobic comonomer to encompass methacrylates of different hydrophobicity, are synthesized. Small-angle X-ray scattering studies confirmed that SCNPs are achieved for each copolymer series when dispersed in basified water at 1% w/w. When the aggregation number of the ASC nanoparticles is close to unity the particle shape elongates resulting in a larger particle surface area to volume ratio, allowing more hydrophilic groups to locate on the particle surface tending to keep the particle surface charge density (PSC) constant. Thus, within a series, particle elongation increases with copolymer molecular weight. Structural parameters of SCNPs formed by ASCs composed of hydrophobic components with low partition coefficients are well consistent with predictions obtained from the PSC model. These results highlight the main parameters, namely molecular weight and acid content, responsible for the SCNP formation and provide insight into how specific particle morphology can be targeted.

Indexed as

NanoparticlesPolymersAnisotropyHydrophobic and Hydrophilic InteractionsMethacrylatesMolecular StructureMolecular WeightParticle SizeScattering, Small AngleSolutionsSurface PropertiesWaterMethacrylatesPolymersSolutionsWateramphiphilic copolymersproteinsSAXSself‐assemblysingle‐chain nanoparticle

Identifiers

PMID39726392
PMCPMC11884217

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.