Microfluidics and Nanofluidics最新文献

This study proposes a novel co-flow capillary microfluidic device that can generate highly monodisperse droplets and polymeric microspheres. The device mainly consists of two self-aligning special-shaped polymeric capillaries. The outer capillary features a gradually contracting and expanding geometry, and the inner has an elliptical cross section at the end. The elliptical nozzle of the inner capillary fits into the contraction region of the outer capillary, and so assembled device, namely a plane-symmetric co-flow capillary, benefits from the self-alignment of the capillaries. The design and manufacturing process of the device are outlined, including a discussion on how the processing conditions affect the capillary geometry. Subsequently, the proposed device is used for droplet generation tests, and the diameter distribution of generated droplets and their influencing factors are investigated. The droplet generation mechanism with the elliptical nozzle is discussed with the help of modeling and simulation. Furthermore, monodisperse porous polymeric microspheres are fabricated using the proposed device, and their porous features are characterized. The results show that the proposed device can produce monodisperse droplets with a mean diameter of a few hundred micrometers and a coefficient of variance (CV) of less than 1%, reflecting the stability of the device. Additionally, porous polymeric microspheres could be successfully produced, and the CV of the size distribution is only around 1%.

The Controlled transport of tiny particles in a microfluidic environment has attracted the attention of numerous researchers in the field of lab-on-a-chip. In this work, for the first time, a fully operational microfluidic chip composed of asymmetric magnetic tracks that unidirectionally transport multiple magnetic particles synced with a general tri-axial magnetic field is proposed. In this innovative chip, the particle motion is analogous to the electron transport in electrical diodes, with similar controllability and automation levels not seen in other single-particle manipulation systems. The vertical bias component of the magnetic field by providing a repulsive force between the particles and preventing undesired cluster formation, makes the proposed chip even more similar to the electrical circuits. Additionally, the chip functions as a highly sensitive biosensor capable of detecting extremely low levels of DNA fragments using ligand-functionalized magnetic beads. The uniqueness of the proposed sensor lies in the introduction of a novel particle/analyte concentrator based on the proposed diodes, which enhances its detection sensitivity. This sensitivity is even further enhanced by a single-particle and pair detection image processing code. Furthermore, the background noise is reduced by eliminating the unwanted bead cluster formation commonly observed in previous works. The proposed device serves as a high-throughput unidirectional transport system at the single-particle resolution, offering sensitive bio-detection with many applications in biomedicine.

Curvilinear microchannels have enabled high throughput sized-based separation and manipulation of microparticles. Real life applications usually deal with fluid’s non-Newtonian behavior, where particles dynamics are altered compared to Newtonian mediums. Despite multiple reports on particle manipulation in shear-thinning fluids, no fundamental experimental investigation has been reported on microparticle focusing behavior inside shear-thickening fluids such as metallic oxide nanofluids in water (e.g., SiO₂-water). These nanofluids pose unique thermal characteristics and exhibit a drastic increase in viscosity as the shear rate rises in the microchannel. Here, we investigate the particle focusing behavior of co-flows of SiO₂ nanofluids inside curved microchannels with various channel widths and radii of curvature. We also report on the effect of nanofluid concentration, fluid axial velocity, and the particle size on particle migration. We observed a behavioral change in particle migration in SiO₂ nanofluids, where the shear-dependent effect could enhance the particle focusing at lower flow rates. Moreover, the dominance of Dean drag at higher axial velocities would dominate the particle migration and transfer them towards two focusing peaks close to the sidewalls. A thorough investigation of particle behavior in nanofluids inside curved microchannels could enable future applications in heat exchangers, solar energy collectors, and nanoplastic detection.

In recent years, the microfluidic squeezing method for cell intracellular delivery has demonstrated high efficiency and generalizability. This approach, however, still faces difficulties in effectively transfecting large molecules. Integration of this method with other membrane disruption strategies can enhance intracellular delivery efficiency and cell viability. Notably, the combination of microchannel squeezing and electric fields emerges as the most crucial strategy. The cell membrane is rapidly perforated in a microfluidic device, and then an electric field is introduced to further improve the permeability of the plasma membrane, allowing transmembrane transit of impermeable molecules. Nevertheless, the underlying mechanism of the combined squeezing and electroporation method on cell membrane destabilization and material transport remains unclear. Thus, this paper aims to develop a computational model to investigate the intracellular delivery process influenced by various external stimuli and to examine the implications of mixing external stimuli as well as the distinct effects of electric and squeezing on intracellular delivery. Meanwhile, we modified the squeezing parameters (microchannel size and cell velocity) and the electric field parameters (pulse length, electric field strength, etc.) to optimize the cell’s absorption of foreign substances. The simulation results indicate that a decrease in the contraction width, an increase in the contraction length, and an increase in the average cell velocity could promote the squeezing deformation of the cell as well as the formation of pores on the cell membrane. And the joint action of cell squeezing and electric field enhances cellular absorption of substances. In addition, the change of electrical parameters also affects the results of cell squeezing in conjunction with the electric field. For example, the increased length of electric field pulses improves the cell membrane permeability. However, the electric field intensity must be set in a reasonable range (< several kV/cm) to prevent cell inactivation.

This paper reports a fabrication method that can make microstructures such as microfluidic channels and nanostructures to generate surface plasmon resonance (SPR) signals in one-step using hot embossing. We first made a micro/nanostructural mold on a silicon substrate through sequential e-beam lithography, reactive ion etching (RIE), photolithography, and inductively coupled plasma RIE. The fabricated mold and cyclo-olefin polymer (COP) film were pressed between two flat, heated metal bases under optimal conditions, and the micro/nanostructures were complementarily transferred to the COP film. After depositing a thin aluminum film onto the nanostructure, the device was completed by patterning Nafion that crossed two channels and a nearby nanostructure, and by bonding the COP film to a flat polydimethylsiloxane (PDMS) substrate with holes punched for the inlets and outlets. SPR signals of the nanostructures of the microfluidic channel were calibrated using glycerol solutions of different percentages, and a wavelength sensitivity of 393 nm/refractive index unit was found for the Al-based nanoslit SPR sensing chip. To detect macromolecules, we first modified bovine serum albumin (BSA) onto the surface of the SPR chip and then allowed different concentrations of anti-BSA samples to flow into the device. A calibration curve for detecting anti-BSA was constructed, and anti-BSA detection levels with and without preconcentration were compared.

The present study introduces a microfluidic device that employs impedance measurement to accurately enumerate cells in suspension. Prior to the development of this device, impedance cytometry microfluidic chips necessitated the use of planar electrodes and sheath fluids, which complicated the system, or utilized small constricted regions that impeded cell movement and reduced operational efficiency. This newly developed device is capable of sensitive and rapid cell enumeration without the need for sheath fluid or planar electrodes, making it suitable for point-of-care applications. Instead of thin-film electrodes, the same needles used for liquid injection were implemented for impedance measurement, thus simplifying the device. The physical parameters of the device were designed using analytical and computer-aided simulations to determine the maximum dimensions required for sensitive detection of human cells. Simulations were also employed to investigate the effects of flow rates, cell shape, and injection method on device performance, and results were compared with experimental findings. Finally, this novel device was tested for its ability to count MCF7 cells at various flow rates and concentrations, with a limit of detection of 32.3 cells per μL being achieved in 1 mL/hr flow rate.

Structures of paper-based microfluidic chips affect the sweat-absorbing time when they are used for sweat analysis. For the first time, we use COMSOL to establish two types of paper-based chip sweat-absorbing models that can quantitatively analyze this phenomenon. The standard model contains 1089 sweat glands, and the simplified model simplifies it according to the idea of finite element division, including 81 sweat glands. Sweat flows in from the bottom of the paper-based chip and out from the electrode contact surface (the upper surface of the central cylinder of the paper-based chip). Both models contain six paper-based chip structures, use Richards’ equation as the governing equation, set the outflow velocity to 0, and set the sweating rate of a sweat gland at 0.6 (mu)L/min. In the standard model, it takes only 46 s for the paper-based structure with the fastest sweat-absorbing speed to completely saturate the electrode contact surface with sweat (meaning the sweat-absorbing time is 46 s), which is 13.06(%) shorter than that of the slowest structure. In the simplified model, the top 3 structures of sweat-absorbing speed are consistent with the standard model. The simulation results show that the sweat-absorbing time is positively correlated with the H value of the bottom surface of the paper-based structure (defined as the area of the bottom surface /the area of sweat glands covered by the bottom surface), which can be proved by analytical and experimental methods. The analytical method proves that this conclusion can be generalized to other sweating rate conditions.

Understanding the slip behaviors on the graphene surfaces is crucial in the field of nanofluidics and nanofluids. The reported values of the slip length in the literature from both experimental measurements and simulations are quite scattered. The presence of low concentrations of functional groups may have a greater impact on the flow behavior than expected. Using non-equilibrium molecular dynamics simulations, we specifically investigated the influence of hydroxyl-functionalized graphene surfaces on the boundary slip, particularly the effects related to hydrogen bond dynamics. We observed that hydroxyl groups significantly hindered the sliding motion of neighboring water molecules. Hydrogen bonds can be found between hydroxyl groups and water molecules. During the flow process, these hydrogen bonds continuously form and break, resulting in the energy dissipation. We analyzed the energy balance under different driving forces and proposed a theoretical model to describe the slip length which also considers the influence of hydrogen bond dynamics. The effects of the driving force and the surface functional group concentration were also studied.

Kinetic theory and modeling have been proven extremely suitable in computing the flow rates in rarefied gas pipe flows, but they are computationally expensive and more importantly not practical in design and optimization of micro- and vacuum systems. In an effort to reduce the computational cost and improve accessibility when dealing with such systems, two efficient methods are employed by leveraging machine learning (ML). More specifically, random forest regression (RFR) and symbolic regression (SR) have been adopted, suggesting a framework capable of extracting numerical predictions and analytical equations, respectively, exclusively derived from data. The database of the reduced flow rates W used in the current ML framework has been obtained using kinetic modeling and it refers to nonlinear flows through circular tubes (tube length over radius (l in [0,5]) and downstream over upstream pressure (p in [0,0.9])) in a very wide range of the gas rarefaction parameter (delta in [0,10^3]). The accuracy of both RFR and SR models is assessed using statistical metrics, as well as the relative error between the ML predictions and the kinetic database. The predictions obtained by RFR show very good fit on the simulation data, having a maximum absolute relative error of less than (12.5%). Various expressions of the form of (W=W(p,l,delta )) with different accuracy and complexity are acquired from SR. The proposed equation, valid in the whole range of the relevant parameters, exhibits a maximum absolute relative error less than (17%). To further improve the accuracy, the dataset is divided into three subsets in terms of (delta) and one SR-based closed-form expression of each subset is proposed, achieving a maximum absolute relative error smaller than (9%). Very good performance of all proposed equations is observed, as indicated by the obtained accuracy measures. Overall, the present ML-predicted data may be very useful in gaseous microfluidics and vacuum technology for engineering purposes.