Evidence map›Paper›PMID 37880280›Full record

ArticleScientific reports2023

Artificial intelligence models for methylene blue removal using functionalized carbon nanotubes.

Abd-Alkhaliq Salih Mijwel, Ali Najah Ahmed, Haitham Abdulmohsin Afan, Haiyam Mohammed Alayan, Mohsen Sherif, Ahmed Elshafie

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

6 authors at 5 institutions in 3 countries.

Abd-Alkhaliq Salih MijwelDepartment of Civil Engineering, College of Engineering, Universiti Tenaga Nasional (UNITEN), 43000, Kajang, Selangor, Malaysia.
Ali Najah AhmedDepartment of Civil Engineering, College of Engineering, Universiti Tenaga Nasional (UNITEN), 43000, Kajang, Selangor, Malaysia. mahfoodh@uniten.edu.my.
Haitham Abdulmohsin AfanUpper Euphrates Basin Developing Center, University of Anbar, Ramadi, Iraq.
Haiyam Mohammed AlayanChemical Engineering Department, University of Technology, Al-Sinaa Street 52, Baghdad, 10066, Iraq. haiyam.m.abdalraheem@uotechnology.edu.iq.
Mohsen SherifNational Water and Energy Center, United Arab Emirates University, P.O. Box 15551, Al Ain, United Arab Emirates.
Ahmed ElshafieDepartment of Civil Engineering, Faculty of Engineering, University of Malaya (UM), 50603, Kuala Lumpur, Malaysia.
Universiti Tenaga Nasional · MYUnited Arab Emirates University · AEUniversity of Anbar · IQUniversity of Malaya · MYUniversity of Technology - Iraq · IQ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to assess the practicality of utilizing artificial intelligence (AI) to replicate the adsorption capability of functionalized carbon nanotubes (CNTs) in the context of methylene blue (MB) removal. The process of generating the carbon nanotubes involved the pyrolysis of acetylene under conditions that were determined to be optimal. These conditions included a reaction temperature of 550 °C, a reaction time of 37.3 min, and a gas ratio (H

Identifiers

PMID37880280
PMCPMC10600184
OpenAlexW4387949102

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.