Evidence map›Paper›PMID 37103796›Full record

ReviewMembranes2023

Application of Photo-Fenton-Membrane Technology in Wastewater Treatment: A Review.

Lihua Liang, Lin Ji, Zhaoyan Ma, Yuanyuan Ren, Shuyu Zhou, Xinchang Long, Chenyang Cao

Abstract readReview
In one paragraph

Review in Membranes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

7 authors.

Lihua LiangCollege of Urban and Environmental Science, Northwest University, Xi'an 710127, China.ORCID 0000-0002-9705-8481
Lin JiCollege of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Zhaoyan MaCollege of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Yuanyuan RenCollege of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Shuyu ZhouCollege of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Xinchang LongCollege of Urban and Environmental Science, Northwest University, Xi'an 710127, China.
Chenyang CaoCollege of Urban and Environmental Science, Northwest University, Xi'an 710127, China.

Funding

China NSF 51401165Key R&D plan of Shaanxi Province 2021SF-451
6 · The paper itself

Abstract

Photo-Fenton coupled with membrane (photo-Fenton-membrane) technology offers great potential benefits in future wastewater treatment because it can not only degrade refractory organics, but also separate different pollutants from water; additionally, it often has a membrane-self-cleaning ability. In this review, three key factors of photo-Fenton-membrane technology, photo-Fenton catalysts, membrane materials and reactor configuration, are presented. Fe-based photo-Fenton catalysts include zero-valent iron, iron oxides, Fe-metal oxides composites and Fe-based metal-organic frameworks. Non-Fe-based photo-Fenton catalysts are related to other metallic compounds and carbon-based materials. Polymeric and ceramic membranes used in photo-Fenton-membrane technology are discussed. Additionally, two kinds of reactor configurations, immobilized reactor and suspension reactor, are introduced. Moreover, we summarize the applications of photo-Fenton-membrane technology in wastewater, such as separation and degradation of pollutants, removal of Cr(VI) and disinfection. In the last section, the future prospects of photo-Fenton-membrane technology are discussed.

Indexed as

membranephotocatalysisphoto-Fentonwastewater treatment

Identifiers

PMID37103796
PMCPMC10142173

What OpenQuestion holds

Textmetadata
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.