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Modeling of on-chip (bio)-particle separation and counting using 3D electrode structures
This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.In lab-on-a-chip applications, manipulation and quantification of (bio)particles is required in a
variety of biomedical applications such as drug screening, disease detection and treatment. For manipulation
of particles, electrical techniques such as dielectrophoresis (DEP) is very suitable. For the quantification or
counting of the bioparticles, flow cytometer, fluorescence-activated cell sorting (FACS) and magneticactivated
cell sorting (MACS) are common techniques. In this study, modeling of microfluidic (bio)-particle
separation based on dielectrophoresis and counting based on capacitance measurement using COMSOL
Multiphysics have been presented. The device performance with planar and 3D electrode structures have
been compared. Microfluidic devices with an asymmetric pair (for separation) and a symmetric pair (for
counting) of electrodes are considered. The effects of the geometrical parameters, material properties, flow
rate, particle size and applied voltage on the device performance have been discussed. The fabrication
procedure of 3D electrode structures is also addressed
Electrostatic and electrokinetic contributions to the elastic moduli of a driven membrane
We discuss the electrostatic contribution to the elastic moduli of a cell or
artificial membrane placed in an electrolyte and driven by a DC electric field.
The field drives ion currents across the membrane, through specific channels,
pumps or natural pores. In steady state, charges accumulate in the Debye layers
close to the membrane, modifying the membrane elastic moduli. We first study a
model of a membrane of zero thickness, later generalizing this treatment to
allow for a finite thickness and finite dielectric constant. Our results
clarify and extend the results presented in [D. Lacoste, M. Cosentino
Lagomarsino, and J. F. Joanny, Europhys. Lett., {\bf 77}, 18006 (2007)], by
providing a physical explanation for a destabilizing term proportional to
\kps^3 in the fluctuation spectrum, which we relate to a nonlinear ()
electro-kinetic effect called induced-charge electro-osmosis (ICEO). Recent
studies of ICEO have focused on electrodes and polarizable particles, where an
applied bulk field is perturbed by capacitive charging of the double layer and
drives flow along the field axis toward surface protrusions; in contrast, we
predict "reverse" ICEO flows around driven membranes, due to curvature-induced
tangential fields within a non-equilibrium double layer, which hydrodynamically
enhance protrusions. We also consider the effect of incorporating the dynamics
of a spatially dependent concentration field for the ion channels.Comment: 22 pages, 10 figures. Under review for EPJ
Large scale Micro-Photometry for high resolution pH-characterization during electro-osmotic pumping and modular micro-swimming
Micro-fluidic pumps as well as artificial micro-swimmers are conveniently
realized exploiting phoretic solvent flows based on local gradients of
temperature, electrolyte concentration or pH. We here present a facile
micro-photometric method for monitoring pH gradients and demonstrate its
performance and scope on different experimental situations including an
electro-osmotic pump and modular micro-swimmers assembled from ion exchange
resin beads and polystyrene colloids. In combination with the present
microscope and DSLR camera our method offers a 2 \mu m spatial resolution at
video frame rate over a field of view of 3920x2602 \mu m^2. Under optimal
conditions we achieve a pH-resolution of 0.05 with about equal contributions
from statistical and systematical uncertainties. Our quantitative
micro-photometric characterization of pH gradients which develop in time and
reach out several mm is anticipated to provide valuable input for reliable
modeling and simulations of a large variety of complex flow situations
involving pH-gradients including artificial micro-swimmers, microfluidic
pumping or even electro-convection.Comment: 5 figures, 15 page
Entropy generation analysisfor the design optimizationof solid oxide fuel cells
Purpose - The aim of this paper is to investigate performance improvements of a monolithic solid oxide fuel cell geometry through an entropy generation analysis. Design/methodology/approach - The analysis of entropy generation rates makes it possible to identify the phenomena that cause the main irreversibilities in the fuel cell, to understand their causes and to propose changes in the design and operation of the system. The various contributions to entropy generation are analyzed separately in order to identify which geometrical parameters should be considered as the independent variables in the optimization procedure. The local entropy generation rates are obtained through 3D numerical calculations, which account for the heat, mass, momentum, species and current transport. The system is then optimized in order to minimize the overall entropy generation and increase efficiency. Findings - In the optimized geometry, the power density is increased by about 10 per cent compared to typical designs. In addition, a 20 per cent reduction in the fuel cell volume can be achieved with less than a 1 per cent reduction in the power density with respect to the optimal design. Research limitations/implications - The physical model is based on a simple composition of the reactants, which also implies that no chemical reactions (water gas shift, methane steam reforming, etc.) take place in the fuel cell. Nevertheless, the entire procedure could be applied in the case of different gas compositions. Practical implications - Entropy generation analysis allows one to identify the geometrical parameters that are expected to play important roles in the optimization process and thus to reduce the free independent variables that have to be considered. This information may also be used for design improvement purposes. Originality/value - In this paper, entropy generation analysis is used for a multi-physics problem that involves various irreversible terms, with the double use of this physical quantity: as a guide to select the most relevant design geometrical quantities to be modified and as objective function to be minimized in the optimization proces
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