Evidence map›Paper›PMID 41458171›Full record

ArticleMethodsX2026

Artificial neural network based predictive modeling of viscosity of an oil based hybrid nanofluid.

Muhammad Furqan, Fahim Raees, Muhammad Khalid

Abstract read
In one paragraph

Article in MethodsX, 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

3 authors.

Muhammad FurqanDepartment of Mathematics, NED University of Engineering and Technology 75270 Karachi, Pakistan.
Fahim RaeesDepartment of Mathematics, NED University of Engineering and Technology 75270 Karachi, Pakistan.
Muhammad KhalidDepartment of Physics University of Karachi 75270 Karachi, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In many industries like micro-electronics, mechanical engines, transportation, manufacturing and nuclear reactors cooling characteristics which is a crucial challenge can optimize using nanofluid. Nanofluids are also used for better energy transfer and storage in many devices. In the current study the viscosity variation studied by the impact of input variables solid volume fraction and temperature. Sol-gel auto-combustion was used to prepare nickel ferrite (NiFe

Indexed as

Artificial neural networkEngine oil 20w-50NanofluidViscosity, carbon nanotube

Identifiers

PMID41458171
PMCPMC12743530

What OpenQuestion holds

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LicenceCC BY
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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.