constitutive fluid dynamic equations for modeling blood plasma microchannel  (COMSOL Inc)

Journal: Biosensors

Article Title: Intelligent Microfluidics for Plasma Separation: Integrating Computational Fluid Dynamics and Machine Learning for Optimized Microchannel Design

doi: 10.3390/bios15020094

Figure Lengend Snippet: ( A ) The schematic of the trifurcation microchannel geometry model. ( B ) The meshed geometry of the model includes an inset zoom-in view, which illustrates the triangular-shaped mesh elements with higher density near the channel bifurcation.

Article Snippet: These three constitutive fluid dynamic equations for modeling blood plasma microchannel in COMSOL are as follows: The Reynolds number (Re): (2) Re = ρ v D h μ Here, ρ is the density of the blood, v is the inlet velocity provided to the microchannel, Dh is a characteristic length, and μ is the dynamic viscosity of the blood.

Techniques:

Journal: Biosensors

Article Title: Intelligent Microfluidics for Plasma Separation: Integrating Computational Fluid Dynamics and Machine Learning for Optimized Microchannel Design

doi: 10.3390/bios15020094

Figure Lengend Snippet: Comparative study of microchannel design optimization for blood plasma separation.

Article Snippet: These three constitutive fluid dynamic equations for modeling blood plasma microchannel in COMSOL are as follows: The Reynolds number (Re): (2) Re = ρ v D h μ Here, ρ is the density of the blood, v is the inlet velocity provided to the microchannel, Dh is a characteristic length, and μ is the dynamic viscosity of the blood.

Techniques: Clinical Proteomics, High Throughput Screening Assay, Software

Journal: Microsystems & Nanoengineering

Article Title: Microfluidic impedance flow cytometer leveraging virtual constriction microchannel and its application in leukocyte differential

doi: 10.1038/s41378-024-00833-y

Figure Lengend Snippet: Working principle of the microfluidic impedance flow cytometer leveraging a virtual constriction microchannel formed by crossflow of conductive sample and insulated sheath fluids with underneath micro-electrodes for impedance measurements, including ( a ) schematic of the microfluidic impedance flow cytometer utilizing virtual constriction microchannel and ( b ) a typcial single-cell pluse and and its formation: as a cell travels through the virtual constriction microchannel between two electrodes, in amplitude, there is a peak due to blockage of electrical lines and then a dip because of expansion of the sample-sheath boundaries due to the traveling cell. As to phase variations, at high frequency domain (e.g., 2.5 MHz), there is a clear dip while at low frequency domain (e.g., 400 kHz), the phase profiles may be affected by the electrical double layer

Article Snippet: As to numerical simulation, a 3D simulation model of the virtual constriction microchannel was established using COMSOL Multiphysics 5.5.

Techniques: Flow Cytometry

Journal: Microsystems & Nanoengineering

Article Title: Microfluidic impedance flow cytometer leveraging virtual constriction microchannel and its application in leukocyte differential

doi: 10.1038/s41378-024-00833-y

Figure Lengend Snippet: Impedance amplitude and phase profiles of individual ( a ) K562, ( b ) Jurkat, and ( c ) HL-60 traveling through the virtual constriction microchannel with representative microscopic images shown in ( d ) where the expansion of the sample-sheath boundaries due to a traveling cell was noticed

Article Snippet: As to numerical simulation, a 3D simulation model of the virtual constriction microchannel was established using COMSOL Multiphysics 5.5.

Techniques:

Journal: Microsystems & Nanoengineering

Article Title: Microfluidic impedance flow cytometer leveraging virtual constriction microchannel and its application in leukocyte differential

doi: 10.1038/s41378-024-00833-y

Figure Lengend Snippet: Impedance amplitude and phase profiles of individual ( a ) NEU, ( b ) EOS, ( c ) MON, and ( d ) LYM from Donor 1, Donor 2, and Donor 3 traveling through the virtual constriction microchannel

Article Snippet: As to numerical simulation, a 3D simulation model of the virtual constriction microchannel was established using COMSOL Multiphysics 5.5.

Techniques:

Journal: Bioengineering & Translational Medicine

Article Title: Characterization of human islet function in a convection‐driven intravascular bioartificial pancreas

doi: 10.1002/btm2.10444

Figure Lengend Snippet: Simulated in vitro and in vivo oxygen concentrations in the tissue unit as a function of islet perifusion rate 10 min after introducing glucose (28 mM) in the bulk fluid (a). Surface plots of oxygen concentration gradient across the tissue unit with radial and longitudinal cross‐sections halfway through the unit. The average oxygen concentration at the islet cores farthest from the microchannel (worst‐case scenario) plotted at (b) 160 mmHg and (c) 95 mmHg inlet pO 2 . Simulations at arterial pO 2 levels suggest that at least 100 nl/min/IEQ (***) is required to be within the oxygen threshold of uninhibited maximal insulin production (0.034 mol/m 3 ). See Table for correlation between perifusion rate and islet density loading levels. Statistical significance is expressed as * p < .05 and ** p < .001

Article Snippet: Single microchannel models of the 2.5%, 10.0%, and 20.0% (v/v) islet densities shown in Figure were created in COMSOL and their outer walls were defined by the symmetry boundary condition.

Techniques: In Vitro, In Vivo, Concentration Assay