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Version devBuilt at: 2026-10-11 02:37:10 EDT

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@degruyterbrillimms.bsky.socialOct 8, 2026, 1:02 PM

How do magnetic, thermal and chemical effects reshape #nanofluid flow?

This study reveals how stratification, convection, radiation and chemical reactions influence #HeatAndMassTransfer, guiding advanced engineering applications.

#NanotechnologyReviews: doi.org/10.1515/ntre...

Effects of dual stratification on thermo-chemically radiative tangent hyperbolic nanofluid flow over an inclined stretching sheet
@degruyterbrillimms.bsky.socialSep 26, 2026, 5:30 AM

How can #HeatAndMassTransfer be better controlled in advanced #Magnetohydrodynamic systems?

This study shows how magnetic fields, thermal relaxation, curvature and velocity slip can tune #nanofluid flow for advanced #thermalmanagement.

#NanotechnologyReviews: doi.org/10.1515/ntre...

Sensitivity analysis of MHD Jeffery hybrid nanofluid flow over an inclined cylinder with Cattaneo–Christov flux model and non-uniform thermal source
@degruyterbrillimms.bsky.socialSep 11, 2026, 12:45 PM

See how #AI improves complex fluid modeling.
This study combines ANN-LMBPA with numerical simulations to predict MHD Williamson-Casson #nanofluid flow, enabling better optimization of heat transfer and industrial cooling systems. #FluidDynamics

#NanotechnologyReviews: doi.org/10.1515/ntre...

AI-based predictive modeling of unsteady Williamson-Casson nanofluid flow with Cattaneo-Christov heat flux driven by slippery curved stretching sheet subject to magnetic dipole
@degruyterbrillimms.bsky.socialSep 10, 2026, 4:15 AM

Smarter fluid models can accelerate engineering design.

This study uses neural networks to predict MHD Casson #nanofluid flow and heat transfer with high accuracy, improving simulation efficiency. #ArtificialNeuralNetwork

#OpenAccess in #NanotechnologyReviews: doi.org/10.1515/ntre...

Machine learning-based insights into MHD Casson nanoliquid heat transfer with zero mass flux boundary condition: an artificial neural network application