ArticleDiscover nano2026
A comparative analysis on MHD fluid flow over a thickness varying surface using Buongiorno model.
Article in Discover nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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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.
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0 citing papers in PubMed.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nanofluids have extensive applications across engineering and industrial domains, including heat exchangers, microelectronics, chillers, and pharmaceutical processes. Utilizing these advanced features, this study is opted to analyze the properties of non-Newtonian Casson nanofluids over a thin surface, considering the effects of thermophoresis, Brownian motion, and heat source/sink. The governing equations are transformed using similarity transformations and solved numerically via the Runge-Kutta-Fehlberg method. The influence of the governing parameters on velocity, temperature, concentration, skin friction coefficient, local Nusselt number, and local Sherwood number is examined and addressed. The primary outcomes demonstrate that increasing the magnetic field reduces fluid velocity due to Lorentz forces. Meanwhile parameters such as wall thickness and velocity power index enhance velocity and temperature profiles. Brownian motion and thermophoresis elevate temperature and concentration near the boundary. Also, higher heat source/sink values significantly boost temperature profiles. These results have direct and practical implications for optimizing heat transfer and flow behavior in non-Newtonian fluids. Current study has immediate applications in biomedical engineering, chemical processing, and microscale fluid systems.Clinical trial number: Not applicable.
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