Evidence map›Paper›PMID 42185394›Full record

ArticleScientific reports2026

Simultaneous removal of fluoride and arsenic from water in a fixed-bed column using Fe-Al-MOF/CF composite: optimization by response surface methodology.

Ephrem Alemu, Ashootosh Mandpe, Shubham More, Dejene Beyene, Esayas Alemayehu

Abstract read
In one paragraph

Article in Scientific reports, 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

5 authors.

Ephrem AlemuFaculty of Civil and Environmental Engineering, Department of Water Supply and Environmental Engineering, Jimma Institute of Technology, Jimma University, P.O. Box 378, Jimma, Ethiopia. ephabeimnet@gmail.com.
Ashootosh MandpeDepartment of Civil Engineering, Indian Institute of Technology, Indore, 453552, India.
Shubham MoreDepartment of Civil Engineering, Indian Institute of Technology, Indore, 453552, India.
Dejene BeyeneFaculty of Civil and Environmental Engineering, Department of Water Supply and Environmental Engineering, Jimma Institute of Technology, Jimma University, P.O. Box 378, Jimma, Ethiopia.
Esayas AlemayehuFaculty of Civil and Environmental Engineering, Department of Water Supply and Environmental Engineering, Jimma Institute of Technology, Jimma University, P.O. Box 378, Jimma, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fluoride and arsenic contamination of groundwater remains a major concern for drinking water safety, particularly in regions relying on untreated groundwater sources. Although metal-organic frameworks (MOFs) have demonstrated effective adsorption for contaminant removal, their application under continuous-flow conditions remains underexplored, limiting their practical deployment in water treatment systems. In this study, a structured bimetallic Fe-Al metal-organic framework was grown on carbon felt to form a composite (Fe-Al-MOF/CF), which was evaluated for simultaneous fluoride and arsenic removal from water in a fixed-bed column. The composite adsorbent was synthesized through electrochemical deposition, enabling uniform MOF growth on the conductive substrate and improving structural stability during continuous operation. SEM, XRD, and FTIR analyses confirmed that the Fe-Al-MOF/CF structure remained intact after adsorption and regeneration, suggesting that fluoride and arsenic removal is primarily governed by surface complexation at Fe

Indexed as

Arsenic removalFixed-bed columnFluoride removalGroundwater treatmentResponse surface methodology

Identifiers

PMID42185394
PMCPMC13408491

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LicenceCC BY-NC-ND
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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.