Evidence map›Paper›PMID 36850129›Full record

ArticlePolymers2023

Application of Molecular Imprinting for Creation of Highly Selective Sorbents for Extraction and Separation of Rare-Earth Elements.

Ruslan Kondaurov, Yevgeniy Melnikov, Laura Agibayeva

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 30% of its field
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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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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

3 authors at 1 institution in 1 country.

Ruslan KondaurovDepartment of Biochemical Engineering, International Engineering and Technological University, Al-Farabi ave. 93a, Almaty 050060, Kazakhstan.ORCID 0000-0001-5998-8453
Yevgeniy MelnikovDepartment of Biochemical Engineering, International Engineering and Technological University, Al-Farabi ave. 93a, Almaty 050060, Kazakhstan.
Laura AgibayevaFaculty of Chemistry and Chemical Technology, Al-Farabi Kazakh National University, Al-Farabi ave. 71, Almaty 050040, Kazakhstan.
Al-Farabi Kazakh National University · KZ

Funding

Ministry of science and higher education of the Republic of Kazakhstan AP13067631
6 · The paper itself

Abstract

The aim of the work is to study the effectiveness of a molecular imprinting technique application for the creation of highly selective macromolecular sorbents for selective sorption of light and heavy rare-earth metals (for example, samarium and gadolinium, respectively) with subsequent separation from each other. These sorbents seem to be promising due to the fact that only the target rare-earth metal will be sorbed owing to the fact that complementary cavities are formed during the synthesis of molecularly imprinted polymers. In other words, the advantage of the proposed macromolecules is the absence of accompanying sorption of metals with close chemical properties. Two types of molecularly imprinted polymers (MIP) were synthetized based on methacrylic acid (MAA) and 4-vinylpyridine (4VP) functional monomers. The sorption properties (extraction degree, exchange capacity) of the MIPs were studied. The impact of template removal cycle count (from 20 to 35) on the sorption effectivity was studied. Laboratory experiments on selective sorption and separation of samarium and gadolinium from a model solution were carried out.

Indexed as

functional macromolecular structureslight and heavy rare-earth metalsmolecular imprinting techniquemolecularly imprinted polymersselective sorptionseparation of rare-earth metals

Identifiers

PMID36850129
PMCPMC9961745
OpenAlexW4319756917

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.