Modeling of Interfaces and Surface Microfluidics

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (29 January 2023) | Viewed by 1202

Special Issue Editor


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Guest Editor
Department of Physics, University of Thessaly, Lamia, Greece
Interests: nanaotechnologies; nanoscience; machine learning; artificial intelligence; atomistic modelling; multiscale modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Microfluidic devices can be used in many applications, such as biomedical or biological analysis or during water cleaning and purification, just to mention few ones. As the related experiments are not easy to perform at the microscale and they are relatively complex, modeling and simulation are important in the facilitation and acceleration of microfluidic device designs, such as MEMS. Surfaces play an important role at the microscale as they can affect flows. A considerable amount of research has been carried out regarding surface modification in microfluidic designs, as it can affect the flowrate through slip based on a surface’s hydrophobicity/hydrophilicity or assist with ion separation in other cases. Functionalization is another important area of research. Several methods are employed in modeling, such as molecular dynamics and dissipative particle dynamics, to name a couple. However, in several cases, these methods have to be combined in order to achieve better resolution, and more recently, methods coupled with machine learning have been developed.

Topics of interest include but are not limited to the following:

  • The multiscale modeling of surfaces and interfaces in microfluidics;
  • Machine-learning-assisted modeling of surfaces and interfaces in microfluidics;
  • Complex hydrophilic and hydrophobic surfaces;
  • Applications of modeling in biological fluid devices;
  • Applications in desalination and water purification using microfluidic devices;
  • Membranes made from micropores.

Prof. Dr. Theodoros Karakasidis
Guest Editor

Manuscript Submission Information

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Keywords

  • microfluidics surface modeling
  • surface modification
  • surface functionalization
  • molecular dynamics simulation of microfluidic surfaces
  • dissipative particle dynamics
  • smoothed-particle hydrodynamics
  • hydrophobic/hydrophilic surfaces

Published Papers (1 paper)

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Research

16 pages, 3383 KiB  
Article
Numerical Analysis of Heat Transfer Enhancement Due to Nanoparticles under the Magnetic Field in a Solar-Driven Hydrothermal Pretreatment System
by Yang Yu, Kai Wang, Yurong Zhao, Qicheng Chen and Nanhang Dong
Processes 2022, 10(12), 2649; https://doi.org/10.3390/pr10122649 - 9 Dec 2022
Viewed by 919
Abstract
Solar-driven hydrothermal pretreatment is an efficient approach for the pretreatment of microalgae biomass for biofuel production. In order to enhance the heat transfer, the magnetic fields effects on flow and heat transfer of nanofluids were investigated in a three-dimensional circular pipe. The magnetic [...] Read more.
Solar-driven hydrothermal pretreatment is an efficient approach for the pretreatment of microalgae biomass for biofuel production. In order to enhance the heat transfer, the magnetic fields effects on flow and heat transfer of nanofluids were investigated in a three-dimensional circular pipe. The magnetic fields were applied in different directions and magnetic field intensities to the flow. In this paper, Finite Volume Method was used to simulate flow and heat transfer of nanofluids under a magnetic field, and the Discrete Phase Model was selected to calculate two-phase flow, which was water mixed with metal nanoparticles. The research was also carried out with the various physical properties of nanoparticles, including the volume share of nanoparticles, particle diameter, and particle types. When the magnetic fields were applied along the X, Y, and Z directions and the intensity of magnetic fields was 0.5 T, the heat transfer coefficients of Cu-H2O nanofluids flow were increased evenly by 9.17%, 10.28%, and 10.32%, respectively. When the magnetic field was applied, the heat transfer coefficients and the Nusselt numbers were both increased with the increment of intensities of the magnetic field. Full article
(This article belongs to the Special Issue Modeling of Interfaces and Surface Microfluidics)
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