Evidence map›Paper›PMID 41769136›Full record

ArticleMacromolecules2026

Coarse-Grained Simulations of Thermosensitive Polymer Nanocomposites.

María Del Mar Ramos-Tejada, Alberto Martín-Molina, Daniel Montesinos, Luis Pérez-Mas, Manuel Quesada-Pérez

Abstract read
In one paragraph

Article in Macromolecules, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

María Del Mar Ramos-TejadaDepartamento de Física, Escuela Politécnica Superior de Linares, Universidad de Jaén, Linares, Jaén 23700, Spain.ORCID https://orcid.org/0000-0001-6790-8732
Alberto Martín-MolinaDepartamento de Física Aplicada, Universidad de Granada, Campus de Fuentenueva s/n, Granada 18071, Spain.ORCID https://orcid.org/0000-0001-8023-8665
Daniel MontesinosInstituto de Física Interdisciplinar y Sistemas Complejos (IFISC) Campus Universitat de les Illes Balears Carretera de Valldemossa, Km 7,5 Edificio Científico-Técnico, Palma de Mallorca, Islas Baleares 07122, Spain.ORCID https://orcid.org/0009-0004-8402-5324
Luis Pérez-MasDepartamento de Física Aplicada, Universidad de Granada, Campus de Fuentenueva s/n, Granada 18071, Spain.ORCID https://orcid.org/0000-0001-6097-776X
Manuel Quesada-PérezDepartamento de Física, Escuela Politécnica Superior de Linares, Universidad de Jaén, Linares, Jaén 23700, Spain.ORCID https://orcid.org/0000-0003-0519-7845

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanogels (as well as other polymer networks) can absorb nanoparticles that give them new properties and expand their application possibilities. The resulting hybrid entities constitute a kind of polymer nanocomposites, which have become an emerging area of research. In this work, coarse-grained simulations have been used to study how certain properties of these nanocomposites (size, number of nanoparticles inside, net charge, and surface potential) change with temperature. Four nanocomposites with different values of charge anchored to the polymer network (known as bare charge) were simulated. The degree to which nanocomposites shrink and expel the particles they contain depends strongly on the bare charge, which, in turn, could be related to the pH in pH-sensitive micro- and nanogels. Our results also reveal that nanoparticles are responsible for nanocomposites exhibiting much richer and more complex behavior than nanogels. Furthermore, the strong correlations that nanoparticles experience when the polymer network shrinks should not be ignored in mean-field theories that try to predict how nanocomposites behave.

Identifiers

PMID41769136
PMCPMC12947680

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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.