Evidence map›Paper›PMID 38740610›Full record

ReviewMolecular diversity2024

Synthesis, modifications, and applications of iron-based nanoparticles.

Raheleh Shahbazi, Farahnaz K Behbahani

Abstract readReview
PubMed Publisher
In one paragraph

Review in Molecular diversity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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.

Raheleh ShahbaziDepartment of Chemistry, Karaj Branch, Islamic Azad University, Karaj, Iran.
Farahnaz K BehbahaniDepartment of Chemistry, Karaj Branch, Islamic Azad University, Karaj, Iran. Fk.behbahani@kiau.ac.ir.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic nanoparticles (MNPs) are appealing materials as assistant to resolve environmental pollution issues and as recyclable catalysts for the oxidative degradation of resistant contaminants. Moreover, they can significantly influence the advancement of medical applications for imaging, diagnostics, medication administration, and biosensing. On the other hand, due to unique features, excellent biocompatibility, high curie temperatures and low cytotoxicity of the Iron-based nanoparticles, they have received increasing attention in recent years. Using an external magnetic field, in which the ferrite magnetic nanoparticles (FMNPs) in the reaction mixtures can be easily removed, make them more efficient approach than the conventional method for separating the catalyst particles by centrifugation or filtration. Ferrite magnetic nanoparticles (FMNPs) provide various advantages in food processing, environmental issues, pharmaceutical industry, sample preparation, wastewater management, water purification, illness therapy, identification of disease, tissue engineering, and biosensor creation for healthcare monitoring. Modification of FMNPs with the proper functional groups and surface modification techniques play a significant role in boosting their capability. Due to flexibility of FMNPs in functionalization and synthesis, it is possible to make customized FMNPs that can be utilized in variety of applications. This review focuses on synthesis, modifications, and applications of Iron-based nanoparticles.

Indexed as

Magnetite NanoparticlesAnimalsFerric CompoundsHumansIronFerric CompoundsIronMagnetite NanoparticlesFerrite nanoparticles applicationsIron-based nanoparticles modificationsIron-based nanoparticles synthesisMagnetic separation

Identifiers

What OpenQuestion holds

Textmetadata
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.