Evidence map›Paper›PMID 40277655›Full record

ReviewGels (Basel, Switzerland)2025

Magnetic Ionogel and Its Applications.

Sayan Ganguly, Shlomo Margel

Abstract readReview
In one paragraph

Review in Gels (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

2 authors.

Sayan GangulyDepartment of Chemistry, University of Waterloo, 200 University Ave West, Waterloo, ON N2L 3G1, Canada.
Shlomo MargelDepartment of Chemistry, Bar-Ilan Institute for Nanotechnology and Advanced Materials (BINA), Bar-Ilan University, Ramat-Gan 5290002, Israel.ORCID 0000-0001-6524-8179

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic ionogels, a category of hybrid materials consisting of magnetic nanoparticles and ionic liquids, have garnered significant interest owing to their remarkable attributes, including tunability, flexibility, and reactivity to external magnetic fields. These materials provide a distinctive amalgamation of the benefits of both magnetic nanoparticles and ionogels, resulting in improved efficacy across many applications. Magnetic ionogels may be readily controlled using magnetic fields, rendering them suitable for drug administration, biosensing, soft robotics, and actuators. The capacity to incorporate these materials into dynamic systems presents novel opportunities for the development of responsive, intelligent materials capable of real-time environmental adaptation. Nonetheless, despite the promising potential of magnetic ionogels, problems persist, including the optimization of the magnetic particle dispersion, the enhancement of the ionogel mechanical strength, and the improvement of the long-term stability. This review presents a comprehensive examination of the syntheses, characteristics, and uses of magnetic ionogels, emphasizing significant breakthroughs and persistent problems within the domain. We examine recent advancements and prospective research trajectories aimed at enhancing the design and efficacy of magnetic ionogels for practical applications across diverse fields, including biomedical uses, sensors, and next-generation actuators. This review seeks to elucidate the present status of magnetic ionogels and their prospective influence on materials science and engineering.

Indexed as

drug delivery systemsionic liquidsmagnetic ionogelsresponsive actuatorssmart materials

Identifiers

PMID40277655
PMCPMC12026471

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.