Evidence map›Paper›PMID 38794623›Full record

ArticlePolymers2024

Dual Semi-Interpenetrating Networks of Water-Soluble Macromolecules and Supramolecular Polymer-like Chains: The Role of Component Interactions.

Anna L Makarova, Alexander L Kwiatkowski, Alexander I Kuklin, Yuri M Chesnokov, Olga E Philippova, Andrey V Shibaev

Abstract read
In one paragraph

Article in Polymers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

6 authors.

Anna L MakarovaFaculty of Physics, Lomonosov Moscow State University, 119991 Moscow, Russia.
Alexander L KwiatkowskiFaculty of Physics, Lomonosov Moscow State University, 119991 Moscow, Russia.ORCID 0000-0002-0514-384X
Alexander I KuklinJoint Institute for Nuclear Research, 141980 Dubna, Russia.
Yuri M ChesnokovNational Research Center, Kurchatov Institute, 123182 Moscow, Russia.ORCID 0000-0001-8365-4699
Olga E PhilippovaFaculty of Physics, Lomonosov Moscow State University, 119991 Moscow, Russia.ORCID 0000-0002-1098-0255
Andrey V ShibaevFaculty of Physics, Lomonosov Moscow State University, 119991 Moscow, Russia.ORCID 0000-0002-3019-5764

Funding

Russian Science Foundation 21-73-10197
6 · The paper itself

Abstract

Dual networks formed by entangled polymer chains and wormlike surfactant micelles have attracted increasing interest in their application as thickeners in various fields since they combine the advantages of both polymer- and surfactant-based fluids. In particular, such polymer-surfactant mixtures are of great interest as novel hydraulic fracturing fluids with enhanced properties. In this study, we demonstrated the effect of the chemical composition of an uncharged polymer poly(vinyl alcohol) (PVA) and pH on the rheological properties and structure of its mixtures with a cationic surfactant erucyl bis(hydroxyethyl)methylammonium chloride already exploited in fracturing operations. Using a combination of several complementary techniques (rheometry, cryo-transmission electron microscopy, small-angle neutron scattering, and nuclear magnetic resonance spectroscopy), we showed that a small number of residual acetate groups (2-12.7 mol%) in PVA could significantly reduce the viscosity of the mixed system. This result was attributed to the incorporation of acetate groups in the corona of the micellar aggregates, decreasing the molecular packing parameter and thereby inducing the shortening of worm-like micelles. When these groups are removed by hydrolysis at a pH higher than 7, viscosity increases by five orders of magnitude due to the growth of worm-like micelles in length. The findings of this study create pathways for the development of dual semi-interpenetrating polymer-micellar networks, which are highly desired by the petroleum industry.

Indexed as

polymerself-assemblysurfactantviscoelasticitywormlike micelles

Identifiers

PMID38794623
PMCPMC11125886

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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.