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              <text>Thermal optimisation through the stratified bioconvective jetflow of nanofluid</text>
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              <text>Bioconvection; jetflow; microorganisms; nanofluid; slip mechanisms</text>
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              <text>Bioconvection is a fascinating phenomenon observed in various biological systems, where the motion of motile microorganisms generates fluid flow patterns. This article explores the occurrence and characteristics of bioconvection within the context of a jet flow. The study of bioconvection in jet flow involves the interaction between motile microorganisms and the fluid dynamics of the surrounding medium. Microorganisms such as bacteria and algae are known to exhibit directed swimming behavior, which can lead to the formation of dynamic flow structures. Investigating the mechanisms underlying bioconvection in jet flow requires a multidisciplinary approach encompassing fluid dynamics, microbial ecology, and mathematical modeling. Experimental techniques, such as microscopy and particle image velocimetry, along with computational simulations, are employed to analyze the complex interactions between microorganisms and the fluid flow. In this regard, a supportive mathematical model is designed using partial differential equations (PDEs) which are later transformed into ordinary differential equations using similarity transformations. The resulting system of equations is solved using the RKF-45 method and the outcomes are recorded in tables and graphs. The consideration of thermophoresis has shown a significant impact on the heat and mass transfer of the jet flow and both these profiles are observed to increase with thermophoresis. Meanwhile, the Schmidt number decrease their respective mass profiles. Furthermore, the porosity is found to create a drag force which tends to oppose the fluid flow.  2023 Taylor &amp;amp; Francis Group, LLC.</text>
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              <text>Yu L.; Li Y.; Puneeth V.; Singh C.; Singhal A.; Anwar M.S.</text>
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              <text>Numerical Heat Transfer, Part B: Fundamentals, Vol-85, No. 6, pp. 791-804.</text>
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              <text>Taylor and Francis Ltd.</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1080/10407790.2023.2256971" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/10407790.2023.2256971&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170661232&amp;amp;doi=10.1080%2F10407790.2023.2256971&amp;amp;partnerID=40&amp;amp;md5=88df1982b734da8de4ef0d2faae6cab9" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85170661232&amp;amp;doi=10.1080%2f10407790.2023.2256971&amp;amp;partnerID=40&amp;amp;md5=88df1982b734da8de4ef0d2faae6cab9&lt;/a&gt;</text>
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              <text>ISSN: 10407790; CODEN: NHBFE</text>
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              <text>Online</text>
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              <text>Yu L., School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China; Li Y., School of Computer Science, University of St. Andrews, St. Andrews, United Kingdom; Puneeth V., School of Sciences, CHRIST University, Delhi-NCR, Ghaziabad, India; Singh C., School of Sciences, CHRIST University, Delhi-NCR, Ghaziabad, India; Singhal A., School of Sciences, CHRIST University, Delhi-NCR, Ghaziabad, India; Anwar M.S., Department of Mathematics, University of Jhang, Jhang, Pakistan</text>
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