Evidence map›Paper›PMID 41767050›Full record

ArticleMacromolecules2025

Rational Design of Zwitterionic Polymers with Tunable Phase Separation Propensity.

Timo N Schneider, Suiying Ye, Nicola Carrara, Umberto Capasso Palmiero, Matteo Salvalaglio, Paolo Arosio

Abstract read
In one paragraph

Article in Macromolecules, 2025. 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

The trial behind it

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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.

Timo N SchneiderDepartment of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog Weg 1, Zurich 8093, Switzerland.ORCID https://orcid.org/0000-0002-8989-1406
Suiying YeDepartment of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog Weg 1, Zurich 8093, Switzerland.
Nicola CarraraDepartment of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog Weg 1, Zurich 8093, Switzerland.
Umberto Capasso PalmieroDepartment of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog Weg 1, Zurich 8093, Switzerland.
Matteo SalvalaglioDepartment of Chemical Engineering, University College London, London WC1E 6BT, U.K.ORCID https://orcid.org/0000-0003-3371-2090
Paolo ArosioDepartment of Chemistry and Applied Biosciences, ETH Zurich, Vladimir Prelog Weg 1, Zurich 8093, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Zwitterionic polymers are emerging as promising candidates for forming fluid-like coacervates with desirable characteristics, including antifouling capabilities, stimulus responsiveness, and biocompatibility. These attributes make them particularly appealing for applications in the biomedical field, including bioseparation, biochemical analysis, and diagnostics. However, there are currently no clear guiding principles for predicting the phase separation behavior of zwitterionic polymers and informing the design of novel phase-separating polymers. In this study, we develop a workflow that combines molecular dynamics simulations, theory, and experiments to predict the phase separation propensity of zwitterionic polymers, as well as the material properties of the resulting coacervates. We validate our simulation-based workflow as a predictive tool by synthesizing new zwitterionic polymers that undergo no phase separation, liquid-liquid phase separation, or liquid-gel phase separation. Beyond their predictive power, we show that molecular simulations provide insights into the attractive homotypic intermolecular interactions mediated by distinct functional groups, rationalizing the large differences observed between zwitterionic monomers that exhibit minimal structural variations. Our approach provides valuable insights into the molecular principles governing the phase separation of distinct zwitterionic polymers, with important implications for the design of their materials.

Identifiers

PMID41767050
PMCPMC12573804

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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.