ArticlePolymers2022
Study of the Dilution-Induced Deposition of Concentrated Mixtures of Polyelectrolytes and Surfactants.
Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Modifying polyelectrolyte charge density and surface coverage for enhanced polyelectrolyte-surfactant lubrication of biomimetic interfaces.RSC applied interfaces · 2026Article
- In Vitro and In Silico Evaluation of a Novel Multifunctional Cyclic Peptide with Antioxidant, Tyrosinase-Inhibitory, and Extracellular Matrix-Modulating Activities.International journal of molecular sciences · 2025Article
- Boundary Lubrication Performance of Polyelectrolyte-Surfactant Complexes on Biomimetic Surfaces.Langmuir : the ACS journal of surfaces and colloids · 2024Article
- Dilution-Induced Deposition of Concentrated Binary Mixtures of Cationic Polysaccharides and Surfactants.Polymers · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Mixtures of polyelectrolytes and surfactants are commonly used in many technological applications where the challenge is to provide well-defined modifications of the surface properties, as is the case of washing formulations in cosmetics. However, if contemporary experimental and theoretical methods can provide insights on their behavior in concentrated formulations, less is known on their behavior under practical use conditions, e.g., under dilution and vectorization of deposits. This makes it difficult to make predictions for specific performance, as, for example, good hair manageability after a shampoo or a comfortable sensorial appreciation after a skin cleanser. This is especially important when considering the formulation of new, more eco-friendly formulations. In this work, a detailed study of the phase separation process induced by dilution is described, as well as the impact on the deposition of conditioning material on negatively charged surfaces. In order to gain a more detailed physical insight, several polyelectrolyte-surfactant pairs, formed by two different polymers and five surfactants that, although non-natural or eco-friendly, can be considered as models of classical formulations, have been studied. The results evidenced that upon dilution the behavior, and hence its deposition onto the surface, cannot be predicted in terms of the behavior of simpler pseudo-binary (mixtures of a polymer and a surfactant) or pseudo-ternary mixtures (two polymers and a surfactant). In many cases, phase separation was observed for concentrations similar to those corresponding to the components in some technological formulations, whereas the latter appeared as monophasic systems. Therefore, it may be assumed that the behavior in multicomponent formulations is the result of a complex interplay of synergistic interactions between the different components that will require revisiting when new, more eco-sustainable ingredients are considered.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.