Evidence map›Paper›PMID 38495186›Full record

ArticleHeliyon2024

Numerical entropy analysis of MHD electro-osmotic flow of peristaltic movement in a nanofluid.

M Gnaneswara Reddy, K Venugopal Reddy, Basma Souayeh, H Fayaz

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

M Gnaneswara ReddyDepartment of Mathematics, Acharya Nagarjuna University Campus, Ongole, 523 001, AP, India.
K Venugopal ReddyDepartment of Mathematics, Anurag University, Hyderabad, 500100, India.
Basma SouayehDepartment of Physics, College of Science, King Faisal University, PO Box 400, Al-Ahsa, 31982, Saudi Arabia.
H FayazModeling Evolutionary Algorithms Simulation and Artificial Intelligence, Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study investigates the MHD electro-osmotic flow of entropy generation analysis for peristaltic movement in a nanofluid with temperature-dependent viscosity. Long wavelengths, i.e., The magnitude of a wave's energy corresponds directly to its frequency while being inversely related to its wavelength in terms of velocity, temperature, and concentration, govern and confine the flow stream in the laminar region. Ohmic heating and hall effects are also included. Graphs are used to obtain and examine numerical solutions for axial velocity, temperature, concentration, Bejan number, and entropy generation. The effects of this research can help to improve pumping and gastrointestinal movements in different engineering devices. Debye-Huckel and lubrication approximations are studied to access the Boltzmann distribution of electric potential across an electric double layer. The investigations of an existing model are important in illuminating the microfluidics machinery used at the micro level for various transport phenomena in which fluids as well as particles are transported together. The current study has many applications and can be further extended to a three-dimensional profile with appropriate modifications and assumptions. When studying entropy generation, it is essential to examine the irreversible factors, while also taking into account the velocity and thermal slip conditions at channel boundaries. Moreover, the concept of entropy generation holds significant importance in comprehending various biological phenomena. Hence, the current research holds promising implications for both industrial and medical fields. The entropy generation is minimum at left wall of the channel for negative values of Helmholtz-Smoluchowski velocity.

Indexed as

Electro-osmosis flowEntropy generationMHDNanofluidPeristalsis

Identifiers

PMID38495186
PMCPMC10943348

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LicenceCC BY
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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.