Abstract
A numerical study has been made on the electroosmotic flow (EOF) through a polyelectrolyte layer coated periodically surface modulated soft nanochannel. We have considered the wall of nanochannel have negative charged when charge density of polyelectrolyte layer (PEL) is positive. A transformation is considered to map the physical region into the rectangular computational region. The governing equations for the electrokinetic flow are Laplace and Poisson equation for the distribution of external and induces potential; the Nernst-Planck equations for ion species and the modified Navier-Stokes equations for flow field. These equations are solved numerically over the staggered system in control volume approach. We have investigated the influence of surface modulation, heterogeneity, electrolyte concentration, PEL thickness and charged density in our study. The combined effects for geometrical modulation and charge heterogeneity in soft channel wall are found prominent. The increasing of the ionic concentration decreases the net charge and therefore, increase the flow rate. The EOF velocity increases with the ionic concentration for zero-scaled PEL charged density. The increase of PEL charged density decreases of the EOF velocity for fixed ion concentration. There is no circulation for low ionic concentration and it appears only for high ionic concentration. The effects of the induced potential are prominent for opposite PEL charged density. The increase of the softness parameter decreases the EOF velocity.
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Acknowledgement
One of the authors (S. Bera) acknowledges for the financial support received from the Science & Engineering Research Board, Government of India for through the project grant (File no: ECR/2016/000771).
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Bera, S., Bhattacharyya, S. (2020). Numerical Study on Electrokinetic Flow Through Periodically Modulated Soft Nanochannel. In: Castillo, O., Jana, D., Giri, D., Ahmed, A. (eds) Recent Advances in Intelligent Information Systems and Applied Mathematics. ICITAM 2019. Studies in Computational Intelligence, vol 863. Springer, Cham. https://doi.org/10.1007/978-3-030-34152-7_29
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DOI: https://doi.org/10.1007/978-3-030-34152-7_29
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