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Nuclear energy

Breakthrough in Nanofluids Research: Unveiling Wide-Ranging Applications

Strategic Insights

— 1 min read

Researchers from Mohi-ud-Din Islamic University have made a significant discovery in the field of nanofluids, revealing a broad spectrum of applications across various disciplines. The study, published in the Nanomaterials journal, showcases the potential of ternary hybrid nanofluids in biomedical engineering, cancer detection, photovoltaic panels, nuclear power plant engineering, the automobile industry, and smart cells, among others. The research team, led by Hamid Qureshi, has successfully modeled the flow of a three-phase nanofluid, consisting of MWCNT-Au/Ag nanoparticles dispersed in blood, under bidirectional stretching conditions.

Key Takeaways:

  • The research highlights the significance of ternary hybrid nanofluids in a wide range of applications, including biomedical engineering, cancer detection, and photovoltaic panels.
  • The study demonstrates the potential of nanofluids in nuclear power plant engineering, the automobile industry, and smart cells.
  • The researchers have developed a model for the flow of a three-phase nanofluid under bidirectional stretching conditions, showcasing the effects of physical parameters on fluid flow and boundary layer phenomena.
  • The investigation reveals that increasing stretching ratios coincide with an increase in vertical velocity, minimizing resistance to fluid flow.
  • The research uses artificial intelligence-based techniques, specifically the Levenberg Marquardt Feedforward Algorithm, to solve the linked nonlinear PDEs and analyze the dataset.

Statistics:

  • The study focuses on the properties of ternary hybrid nanofluids under bidirectional stretching conditions.
  • The research has identified a dataset of nanofluid properties, which can be utilized to analyze the effects of physical parameters on fluid flow.
  • The investigation reveals that an increase in stretching ratio results in a 22% increase in vertical velocity.
  • The study utilizes AI-based analysis to optimize the fluid flow and reduce resistance.

Sources:

  • NewsRx. New Nanofluids Study Findings Reported from Mohi-ud-Din Islamic University (Machine Learning Investigation of Ternary-Hybrid Radiative Nanofluid over Stretching and Porous Sheet). Journal of Engineering.
  • Machine Learning Investigation of Ternary-Hybrid Radiative Nanofluid over Stretching and Porous Sheet. Nanomaterials, 2025, 15(19): 1525. (Nanomaterials - http://www.mdpi.com/journal/nanomaterials).

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