Evidence map›Paper›PMID 41977368›Full record

ReviewInternational journal of molecular sciences2026

Ion-Imprinted Chitosan Technology for Heavy Metal Ion Removal from Water and Wastewater: A Review on Recent Insights and Future Perspectives.

Łukasz Wujcicki, Joanna Kluczka

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Łukasz WujcickiDepartment of Inorganic, Analytical Chemistry and Electrochemistry, Faculty of Chemistry, Silesian University of Technology, B. Krzywoustego 6, 44-100 Gliwice, Poland.ORCID 0009-0008-2475-150X
Joanna KluczkaDepartment of Inorganic, Analytical Chemistry and Electrochemistry, Faculty of Chemistry, Silesian University of Technology, B. Krzywoustego 6, 44-100 Gliwice, Poland.ORCID 0000-0002-4937-7832

Funding

Silesian University of Technology 04/010/BKM26, 04/010/BK26/1120
6 · The paper itself

Abstract

Ion-imprinting technology based on biosorbents via sorption demonstrates potential for the selective removal of metal ions from water and wastewater. This offers both high sorption capacity and selectivity for specific metals. Current research trends are toward the development of sorbents with minimal environmental impact. Among the most rapidly evolving classes of sorbents are those derived from biopolymers, such as chitosan-a natural derivative of chitin that can be readily functionalized. Due to the growing interest in this topic, it is necessary to summarize the current knowledge. In this article, we provide a comprehensive overview of the latest advances in ion-imprinted chitosan-based materials designed for the purification of metal-contaminated aqueous systems. We conduct a bibliographic analysis and describe a variety of chitosan-based materials exhibiting selectivity toward heavy metals, including chromium Cr(III/VI), cobalt Co(II), nickel Ni(II), copper Cu(II), zinc Zn(II), arsenic As(III/V), cadmium Cd(II), mercury Hg(II), and lead Pb(II). Finally, we discuss future prospects and highlight current research gaps, aiming to guide further scientific exploration and innovation in this promising field.

Indexed as

ChitosanMetals, HeavyMolecular ImprintingWastewaterWater Pollutants, ChemicalWater PurificationAdsorptionIonsChitosanIonsMetals, HeavyWastewaterWater Pollutants, ChemicaladsorptionbiopolymerchitosanIIPion-imprintingmetal ionsselectivewastewaterwater treatment

Identifiers

PMID41977368
PMCPMC13072893

What OpenQuestion holds

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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.