Evidence map›Paper›PMID 41392817›Full record

ReviewWater science and technology : a journal of the International Association on Water Pollution Research2025

Molecularly imprinted polymer for the removal of nutrients from water: synthesis, application, performance and limitation.

Emmanuella Anang, Abolade Busari

Abstract readReview
PubMed Publisher
In one paragraph

Review in Water science and technology : a journal of the International Association on Water Pollution Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

2 authors.

Emmanuella AnangCollege of Science and Engineering, East Texas A&M University, Commerce 75428, Texas USA E-mail: emmanuella.anang@etamu.edu.ORCID https://orcid.org/0000-0003-1887-0517
Abolade BusariDepartment of Chemistry and Biochemistry, Central Michigan University, Mount Pleasant 48859, Michigan, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nutrient contamination is a major contributor to eutrophication and water quality degradation worldwide. Conventional treatment technologies often lack selectivity and efficiency in complex aquatic environments, highlighting the need for advanced materials with tailored recognition capabilities. Molecularly imprinted polymers (MIPs) have emerged as promising adsorbents for nutrient remediation due to their high selectivity, stability and reusability. This review synthesizes recent progress on the synthesis strategies of MIPs. Applications of MIPs in removing phosphate, nitrate and ammonia from water are critically examined, with particular attention to adsorption performance under varying environmental conditions. The limitations of current systems, including modest adsorption capacities, incomplete template removal, matrix interferences and scalability challenges, are discussed alongside concerns about the fate and transport of MIPs in natural waters. Finally, the review highlights future opportunities in green synthesis and hybrid MIP composites to overcome current barriers. Collectively, this work positions MIPs as promising next-generation materials for selective nutrient removal and sustainable water remediation.

Indexed as

Molecular ImprintingMolecularly Imprinted PolymersNutrientsWater Pollutants, ChemicalWater PurificationAdsorptionMolecularly Imprinted PolymersNutrientsWater Pollutants, Chemicaladsorption capacityeutrophicationnutrient contaminationpolymerwater treatment

Identifiers

PMID41392817

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.