Evidence map›Paper›PMID 32182867›Full record

ArticlePolymers2020

Self-Consistent Mean Field Calculations of Polyelectrolyte-Surfactant Mixtures in Solution and upon Adsorption onto Negatively Charged Surfaces.

Eduardo Guzmán, Laura Fernández-Peña, Gustavo S Luengo, Ana María Rubio, Antonio Rey, Fabien Léonforte

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

3 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
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  3. Review
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 at 2 institutions in 2 countries.

Eduardo GuzmánDepartamento de Química Física, Universidad Complutense de Madrid, 28040 Madrid, Spain.ORCID 0000-0002-4682-2734
Laura Fernández-PeñaDepartamento de Química Física, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Gustavo S LuengoL'Oréal Research and Innovation, 93600 Aulnay-Sous Bois, France.ORCID 0000-0001-8816-5536
Ana María RubioDepartamento de Química Física, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Antonio ReyDepartamento de Química Física, Universidad Complutense de Madrid, 28040 Madrid, Spain.
Fabien LéonforteL'Oréal Research and Innovation, 93600 Aulnay-Sous Bois, France.ORCID 0000-0001-7968-8511
Universidad Complutense de Madrid · ESL'Oréal (France) · FR

Funding

Ministerio de Ciencia, Innovación y Universidades CTQ2016-78895-R
6 · The paper itself

Abstract

Self-Consistent Mean-Field Calculations (SCF) have provided a semi-quantitative description of the physico-chemical behavior of six different polyelectrolyte-surfactant mixtures. The SCF calculations performed showed that both the formation of polymer-surfactant in bulk and the adsorption of the formed complexes onto negatively-charged surfaces are strongly affected by the specific nature of the considered systems, with the polymer-surfactant interactions playing a central role in the self-assembly of the complexes that, in turn, affects their adsorption onto interfaces and surfaces. This work evidences that SCF calculations are a valuable tool for deepening on the understanding of the complex physico-chemical behavior of polyelectrolyte-surfactant mixtures. However, it is worth noting that the framework obtained on the basis of an SCF approach considered an equilibrium situation which may, in some cases, be far from the real situation appearing in polyelectrolyte-surfactant systems.

Indexed as

adsorptioncalculationscomplexesmixturespolyelectrolytesurfactants

Identifiers

PMID32182867
PMCPMC7182847
OpenAlexW3010107835

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.