Evidence map›Paper›PMID 35492091›Full record

ArticleRSC advances2020

The implementation of artificial neural networks for the multivariable optimization of mesoporous NiO nanocrystalline: biodiesel application.

Soroush Soltani, Taha Roodbar Shojaei, Nasrin Khanian, Thomas Shean Yaw Choong, Umer Rashid, Imededdine Arbi Nehdi, Rozita Binti Yusoff

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in RSC advances, 2020. 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

7 authors.

Soroush SoltaniDepartment of Chemical and Environmental Engineering, Universiti Putra Malaysia 43400 Selangor Malaysia soroush.soltaani@gmail.com.ORCID https://orcid.org/0000-0002-7540-7257
Taha Roodbar ShojaeiDepartment of Mechanical Engineering of Agricultural Machinery, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran Karaj Iran.
Nasrin KhanianDepartment of Physics, Faculty of Science, Islamic Azad University Karaj Iran.
Thomas Shean Yaw ChoongDepartment of Chemical and Environmental Engineering, Universiti Putra Malaysia 43400 Selangor Malaysia soroush.soltaani@gmail.com.
Umer RashidInstitute of Advanced Technology, Universiti Putra Malaysia 43400 Selangor Malaysia.
Imededdine Arbi NehdiDepartment of Chemistry, College of Science, King Saud University Riyadh 11451 Saudi Arabia.
Rozita Binti YusoffDepartment of Chemical Engineering, Faculty of Engineering, University of Malaya W. Persekutuan Kuala Lumpur 50603 Kuala Lumpur Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the present research, artificial neural network (ANN) modelling was utilized to determine the relative importance of effective variables to achieve optimum specific surface areas of a synthesized catalyst. Initially, carbonaceous nanocrystalline mesoporous NiO core-shell solid sphere composites were produced by applying incomplete carbonized glucose (ICG) as the pore directing agent and polyethylene glycol (PEG; 4000) as the surfactant

Identifiers

PMID35492091
PMCPMC9051417

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.