Evidence map›Paper›PMID 40321501›Full record

ArticleACS omega2025

Development and Testing of Robust 3D Printed ZnO/Clay Photocatalysts for Sustainable Wastewater Treatment.

Sardar Ali, Mohannad T Aljarrah, Awni Al-Otoom, Noor Abdelaziz

Abstract read
In one paragraph

Article in ACS omega, 2025. 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. 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

4 authors.

Sardar AliCollege of Engineering and Technology, University of Doha for Science and Technology, 24449 Doha, Qatar.ORCID https://orcid.org/0009-0007-8101-2300
Mohannad T AljarrahCollege of Engineering and Technology, University of Doha for Science and Technology, 24449 Doha, Qatar.
Awni Al-OtoomCollege of Engineering and Technology, University of Doha for Science and Technology, 24449 Doha, Qatar.
Noor AbdelazizCollege of Engineering and Technology, University of Doha for Science and Technology, 24449 Doha, Qatar.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Contamination of water resources with organic pollutants is a serious environmental problem. Degradation of organic pollutants using photocatalytic materials is a promising method of wastewater treatment. In this work, we report on the fabrication of novel 3D printed (3DP) ZnO/Clay materials to be used as efficient photocatalysts for the degradation of methylene blue (MB). Extrusion-based direct ink writing technology was utilized to print the scaffolds. The synthesized scaffolds were thoroughly characterized using the analytical techniques of Brunauer-Emmett-Teller, Fourier transform infrared, X-ray diffraction, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The photocatalytic activity was studied by measuring the photodegradation of MB under simulated solar radiation. The synergistic effects of adsorption and photodegradation resulted in a 100% removal efficiency of MB within 40 min by the 3DP catalyst. The reported catalysts require minimum time for MB degradation with high pollutants removal efficiency, and therefore, no further treatment is required after usage for the catalytic experiment. The 3DP catalysts also demonstrated excellent stability during the reusability test, where performance of the catalysts was assessed for the degradation of MB using several consecutive cycles without any treatment or regeneration. This work can provide a way for preparing efficient and environmentally friendly photocatalysts.

Identifiers

PMID40321501
PMCPMC12044459

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.