Evidence map›Paper›PMID 34068870›Full record

ReviewMembranes2021

Donnan Membrane Process for the Selective Recovery and Removal of Target Metal Ions-A Mini Review.

Dennis Asante-Sackey, Sudesh Rathilal, Emmanuel Kweinor Tetteh, Elorm Obotey Ezugbe, Lingham V Pillay

Abstract readReview
In one paragraph

Review in Membranes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. 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

5 authors.

Dennis Asante-SackeyDepartment of Chemical Engineering, Durban University of Technology, Durban 4001, South Africa.ORCID 0000-0001-8239-0011
Sudesh RathilalDepartment of Chemical Engineering, Durban University of Technology, Durban 4001, South Africa.ORCID 0000-0002-4677-5309
Emmanuel Kweinor TettehDepartment of Chemical Engineering, Durban University of Technology, Durban 4001, South Africa.ORCID 0000-0003-1400-7847
Elorm Obotey EzugbeDepartment of Chemical Engineering, Durban University of Technology, Durban 4001, South Africa.ORCID 0000-0003-4231-5628
Lingham V PillayDepartment of Process Engineering, Stellenbosch University, Matieland 7600, South Africa.

Funding

Water Research Commission , South Africa WRC/240.
6 · The paper itself

Abstract

Membrane-based water purification technologies contribute significantly to water settings, where it is imperative to use low-cost energy sources to make the process economically and technically competitive for large-scale applications. Donnan membrane processes (DMPs) are driven by a potential gradient across an ion exchange membrane and have an advantage over fouling in conventional pressure driven membrane technologies, which are gaining attention. DMP is a removal, recovery and recycling technology that is commonly used for separation, purification and the concentrating of metals in different water and waste streams. In this study, the principle and application of DMP for sustainable wastewater treatment and prospects of chemical remediation are reviewed and discussed. In addition, the separation of dissolved metal ions in wastewater settings without the use of pressure driven gradients or external energy supply membrane technologies is highlighted. Furthermore, DMP distinctive configurations and operational factors are explored and the prospects of integrating them into the wastewater treatment plants are recommended.

Indexed as

Donnan DialysisDonnan membrane procession exchange membranesmetal recovery

Identifiers

PMID34068870
PMCPMC8153574

What OpenQuestion holds

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LicenceCC BY
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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.