Graph (c) shows the osmotic pressure profiles in the right and left halves of the particle. Graph (b) shows the same average concentration of reactants (cri) and products (cpi) on the right side of the particle.
- INTRODUCTION
- PROBLEM FORMULATION
- Governing Equations
- Boundary Conditions
- Analytical Solution
- Numerical Solution Methodology
- VALIDATION
- RESULTS AND DISCUSSION
- CONCLUSIONS
Particle size, fluid viscosity, applied field intensity, and surface potential have been shown to significantly affect particle velocity. Interestingly, the speed and direction of the electrophoretic movement of the 'Janus' particles can be tuned with the variation of the chemical heterogeneities on the surface.
PROBLEM FORMULATION
SOLUTION METHODOLOGIES
- Analytical Solution
- Numerical Methodology
- Validation
RESULTS AND DISCUSSION
- Homogeneous Channels
- Mixing in Heterogeneous Channels
- Mixing in Flexible Channels
CONCLUSIONS
- INTRODUCTION
- MATERIALS
- METHODS
- Preparation of Active Material
- Electrode fabrication
- Preparation and characterization of SC
- Design of Separators
- Electrochemical analysis
- Supercapacitor Arrangement
- CHARACTERIZATIONS
- THEORETICAL FORMULATION
- RESULTS AND DISCUSSION
- Electrode geometry and distance
- Frequency dependent PPS performance
- Charge storage mechanism
- Capacitance from TCM and CV analysis
- CONCLUSIONS
A theoretical model consisting of the Poisson-Nernst-Planck equations for the electric field in the electrolyte and the Laplace equation for the electric field in the electrodes, together with the Navier-Stokes equations for the fluid flow, was numerically solved with appropriate boundary conditions to discover the routes to supercapacitance between experiments. Taken together, experimental and theoretical studies reveal that the use of a potential drop across the EDL originating from opposing electric fields due to electrode polarization and EDL formation could provide more precise routes to the supercapacitance of such SCs.
- INTRODUCTION
- RESULTS AND DISCUSSION
- CNT-bot Locomotion
- Fuel Cell Application
- Dye Degradation Application
- EXPERIMENTAL SECTION
- Materials and methods
- Characterization
- CONCLUSIONS
The use of carboxyl-functionalized multi-walled-carbon nanotubes (MWCNT) facilitated a propulsion of CNT bot in the alkaline water by expelling carbon dioxide bubbles. In addition, light-stimulated Photo-Fenton reaction led to the phototaxis of CNT-bot.
PROBLEM FORMULATION
- Governing Equations
- Boundary Conditions
Close to the particle surface, a polar coordinate is taken, with the center of the particle stated as r = 0. Here ci represents the sum of the concentration of all components (including both the reactants and the products). The fluid-structure interaction (FSI) is believed to follow the motion of the particle migrating during the osmotic pressure gradient.
Here the symbols, s and σ represent the density of the solid and stress tensor of a Newtonian fluid, respectively. The boundary conditions for Eq. 6.2) differs for the imposed and auto-chemophoretic motion of the particle. For the imposed chemophoretic motion, Dirichlet boundary condition is used at the inlet and outlet of the channel.
At one end, either at x = 0 or at x = l, cri = cri0 is maintained, whereas the concentration of the product (cpi) is initially kept zero at both ends of the channel. For the auto-chemophoretic movement of the particle, constant concentration (cri) at the beginning of the simulation, i.e. to ensure that the movement of the particle along with the fluid inside the channel is only due to the chemical gradient, no pressure gradient across the channel is taken and both ends of the channel are kept at atmospheric pressure.
NUMERICAL METHODOLOGY
For the fluid-structure interaction, the two-way coupling is forced together with the particle. To this end, continuity of velocity boundary condition, 𝐮 = 𝐮𝑠̇ , has been imposed on the particle surface, while a no-slip condition is imposed along the inner wall of the tube. Zero displacement (us = 0) and zero velocity (𝐮𝑠̇ = 0) of the particle at the initial time (t = 0) have been imposed to satisfy the two boundary conditions necessary to solve the equation.
The hydrodynamic stress, which is imparted to the particle surface, is obtained from the coupled momentum equations. The finite element method (FEM) of the commercial CFD simulation software, COMSOL MultiphysicsTM, is given for the discretization and solution of the coupled set of Eqs. The software uses the Galerkin least square (GLS) method along with second-order elements for velocity calculations and first-order elements to discretize the equations.
Consistent initialization and time marching is taken care of by the software using a second-order backward difference method with a suitable time step size of ~10-4 s.
VALIDATION
- Analytical Model
- Boundary Conditions
- Comparison of Semi-Analytical and Simulation Results
Here la is the active distance measured from the particle surface (r = R), to which the effect of reaction diffusion does not extend and above which the concentration can be safely assumed to be constant. Here, cRS and cPS are stable concentrations of the reactant and product on the particle surface and also everywhere at the initial time point (t = 0). To prove the validity of the CFD numerical code, this section compares the concentration profiles obtained by CFD simulation and the proposed analytical model.
Analytical solutions using a moving reference frame are somewhat cumbersome and also beyond the scope of this study. Different kinetic parameters are used, based on the differential reaction rate kinetics on the two different sides of the particle. Figures 6.2 (a) and 6.2 (b) show a comparison of the profiles on the left and right halves of the particle, where the reaction rate constants are kR = 8.5.
The figures show a good match between the numerical and analytical profiles near the particle surface and it deviates as we move away from the surface. The non-linearity of CFD simulation, associated fluid flow, particle motion affects the concentration profile and these may be the reasons for the slight discrepancy between the simulation and analytical profiles, especially far from the particle surface. A first-order reaction is proceeding with rate constants kL = 1.75 and kR = 8.9 s-1 in the left and right halves of the particle, respectively.
RESULTS & DISCUSSION
- Influence of Shape
- Influence of External concentration gradient
- Influence of Zero concentration gradient
Therefore, the particle moves from the left to the right side of the channel while being guided by an externally imposed concentration field. Graphs (c) and (d) show the developed osmotic pressure (π) as a function of the time profile for the left and right side of the particle, respectively. The higher osmotic pressure that develops on the right half of the particle facilitates the movement of the particles towards the left side.
Images (d) through (f) show the reactant concentration, product concentration, and osmotic pressure versus distance from the particle surface profiles (l) for a particle with a higher reaction rate constant on the left half of the particle. Distance from the right side of the particle surface is taken as positive (+l) and distance from the left surface is taken as negative (-l). However, the evolution of across the particle is also determined by the component diffusivities.
Two different orientations of the particle can be taken (one with a higher reaction rate constant on the left side and another with a higher rate constant on the right side of the particle). A blue arrow indicates left to right motion and a red arrow indicates motion from the right to left side of the particle. The more the formation of the product, the more the osmotic pressure is built up around the particle.
CONCLUSIONS
As the reactant diffusivity product (Dp/Dr) increases, the particle exhibits a larger velocity magnitude. In this scenario, the osmotic pressure increases more on the left side, thus driving the particle from the left to the right side of the channel, which is shown as a positive velocity in the figure. Here, Dr and Dp denote the average diffusivities of the reactant and product components, respectively.
The positive value of the coefficient shows velocity in the positive direction while the negative value coefficient shows velocity in the left-hand direction. However, the magnitude of velocity differs for the equal magnitude of the coefficient having different signs. In addition to the difference in diffusivities and reaction kinetics, the stoichiometric ratios also determine the motion of the particle.
We have defined a reaction in which one of the products (C) increases in number as the reaction propagates. The presence of an imposed chemical potential gradient across the Janus particle can either facilitate or reverse the motion of the particle. A change in the total stoichiometric numbers of the products with respect to the number of reactants can actually have a significant impact on the motion of the particle.
Journal Publications
Pattader, Joint mass transfer of two components associated with the spontaneous interfacial convection in the liquid-liquid extraction system, Chem. Pattader, Efficient Microextraction Process Exploiting Spontaneous Interfacial Convection Driven by Marangoni and Electric Field Instability: A Computational Fluid Dynamics Study (Manuscript Submitted). Pattader, Multicomponent Mass Transfer Counts in Liquid-Liquid Extraction in the Presence of Spontaneous Interfacial Convection, Solvent-Extr.
Conference Publications
Mandal, Paper-based enzymatic chemiresist for POC detection of ethanol in human breath, IEEE Sens. MWCNT, AuNP Nanocomposite Based POCT Sensor for Quantitative Detection of Urea in Biological Samples, Nirmal Roy, S. Efficient Microextraction Process Exploiting Spontaneous Interface-Driven Marangoni Confection and Electric Field Instability: A Computational Fluid Dynamics Study, S.
11 Countermass transfer of multiple components in liquid-liquid extraction in the presence of spontaneous interfacial convection, S.Mitra, E.
Patents
Effects of Fluid-Structure Interaction and Surface Heterogeneity on Microparticle Electrophoresis, S. Multimodal Chemo-Magneto-Photoloads of 3G CNT Bots to Drive Fuel Cells, S. 11 Multicomponent Counter Mass Transfer in the Presence of Liquid-Liquid Extraction from Spontaneous Interfacial Convection, S.Mitra, E. Pattader, Alumni Symposium, Calcutta University, 2019, India. Gao, W.; Jurado-Sanchez, B.; Fedorak, Y.; Wang, J., Water-powered micromotors for rapid photocatalytic degradation of biological and chemical warfare agents. S; Sandoval, M., Ellipsoidal Brownian self-propelled particles in a magnetic field. i.; Maekawa, S.; Sinova, J., Spinmotive force due to motion of magnetic bubble arrays driven by magnetic field gradient.
B; Soni, G.; Meinhart, C.; Bruus, H., Numerical analysis of finite Debye length effects in induced charge electroosmosis. Relationship between skin permeability and electrophoresis of biologically active materials in living human skin. S; Work, E., Electrophoresis of proteins in polyacrylamide and starch gels. M., Temperature gradient gel electrophoresis analysis of 16S rRNA from human fecal samples reveals stable and host-specific communities of active bacteria. G., Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction amplified genes encoding 16S rRNA. 110) Pan, B.-f.;.
Janusz, W.; Buszewski, B., Effect of zeta potential value on bacterial behavior during electrophoretic separation. 129) Schwer, C.; Kenndler, E., Electrophoresis in fused silica capillaries: the influence of organic solvents on the electroosmotic rate and. G.; Barkai, N.; Leibler, S., Robustness in bacterial chemotaxis. 132) Piazza, R.; Parola, A., Thermophoresis in colloidal suspensions. 136) Wang, H.; E.; Sen, A., Hydrazine fuels for bimetallic catalytic microfluidic pumping. 146) Ma, X.; Wang, X.; Hahn, K.; Sánchez, S., Motion control of urea-powered biocompatible hollow microcapsules. 147) Schattling, P.; Thingholm, B.; Stadler, B., Enhanced diffusion of glucose-powered Janus particles. Streaming potential and the electroosmotic countereffect. 168) Erickson, D.; Li, D., Streaming potential and streaming current methods for the characterization of heterogeneous solid surfaces. 169) Luong, D.; Sprik, R., Flow potential and electroosmosis measurements to characterize porous materials.
