Secondary Flows, Mixing, and Chemical Reaction Analysis of Droplet-Based Flow inside Serpentine Microchannels with Different Cross Sections

Optimization of passive micromixers: effects of pillar configuration and gaps on mixing efficiency

Chemical bioreactions play a significant role in many of the microfluidic devices, and their applications in biomedical science have seen substantial growth. Given that effective mixing is vital for initiating biochemical reactions in many applications, micromixers have become increasingly prevalent for high-throughput assays. In this research, a numerical study using the finite element method was conducted to examine the fluid flow and mass transfer characteristics in novel micromixers featuring an array of pillars. The study utilized two-dimensional geometries. The impact of pillar configuration on mixing performance was evaluated using concentration distribution and mixing index as key metrics. The study explores the effects of pillar array design on mixing performance and pressure drop, drawing from principles such as contraction-expansion and split-recombine. Two configurations of pillar arrays, slanted and arrowhead, are introduced, each undergoing investigation regarding parameters such as pillar diameter, gap size between pillar groups, distance between pillars, and vertical shift in pillar groups. Subsequently, optimal micromixers are identified, exhibiting mixing efficiency exceeding 99.7% at moderate Reynolds number (Re = 1), a level typically challenging for micromixers to attain high mixing efficiency. Notably, the pressure drop remains low at 1102 Pa. Furthermore, the variations in mixing index over time and across different positions along the channel are examined. Both configurations demonstrate short mixing lengths and times. At a distance of 4300 μm from the inlet, the slanted and arrowhead configurations yielded mixing indices of 97.2% and 98.9%, respectively. The micromixers could provide a mixing index of 99.5% at the channel's end within 8 s. Additionally, both configurations exceeded 90% mixing indices by the 3 s. The combination of rapid mixing, low pressure drop, and short mixing length positions the novel micromixers as highly promising for microfluidic applications.

Simple Method for On-Demand Droplet Trapping in a Microfluidic Device Based on the Concept of Hydrodynamic Resistance

We demonstrate an innovative method to catch the desired droplets from a train of droplets and immobilize them in traps located in an integrated microfluidic device. To this end, water-in-oil droplets are generated in a flow-focusing junction and then guided to a channel connected to chambers designated for on-demand droplet trapping. Each chamber is connected to a side channel through a batch of microposts. The side channels are also connected to the flexible poly(vinyl chloride) tubes, which can be closed by attaching binder clips. The hydrodynamic resistance of the routes in the device can be changed by opening and closing the binder clips. In this way, droplets are easily guided into individual traps based on the user's demand. A set of numerical simulations was also conducted to investigate the authenticity of the employed idea and to find the optimal geometry for implementing our strategy. This simple method can be easily employed for on-demand droplet trapping without using on-chip valves or complex off-chip actuators proposed in previous studies.

Enhanced mixing efficiency and reduced droplet size with novel droplet generators

Nowadays, droplet microfluidics has become widely utilized for high-throughput assays. Efficient mixing is crucial for initiating biochemical reactions in many applications. Rapid mixing during droplet formation eliminates the need for incorporating micromixers, which can complicate the chip design. Furthermore, immediate mixing of substances upon contact can significantly improve the consistency of chemical reactions and resulting products. This study introduces three innovative designs for droplet generators that achieve efficient mixing and produce small droplets. The T-cross and cross-T geometries combine cross and T junction mixing mechanisms, resulting in improved mixing efficiency. Numerical simulations were conducted to compare these novel geometries with traditional T and cross junctions in terms of mixing index, droplet diameter, and eccentricity. The cross-T geometry exhibited the highest mixing index and produced the smallest droplets. For the flow rate ratio of 0.5, this geometry offered a 10% increase in the mixing index and a decrease in the droplet diameter by 10% compared to the T junction. While the T junction has the best mixing efficiency among traditional droplet generators, it produces larger droplets, which can increase the risk of contamination due to contact with the microchannel walls. Therefore, the cross-T geometry is highly desirable in most applications due to its production of considerably smaller droplets. The asymmetric cross junction offered a 8% increase in mixing index and around 2% decrease in droplet diameter compared to the conventional cross junction in flow rate ratio of 0.5. All novel geometries demonstrated comparable mixing efficiency to the T junction. The cross junction exhibited the lowest mixing efficiency and produced larger droplets compared to the cross-T geometry (around 1%). Thus, the novel geometries, particularly the cross-T geometry, are a favorable choice for applications where both high mixing efficiency and small droplet sizes are important.

An experimental study of centrifugal microfluidic platforms for magnetic-inertial separation of circulating tumor cells using contraction-expansion and zigzag arrays

Cancer diagnosis has recently been at the forefront of recent medical research, with ongoing efforts to develop devices and technologies for detecting cancer in patients. One promising approach for cancer diagnosis is the detection of Circulating Tumor Cells (CTCs) in blood samples. Separating these rare cells from the diverse background of blood cells and analyzing them can provide valuable insights into the disease's stage and lethality. Here we present the design and fabrication of a centrifugal microfluidic platform on a polymeric disk that utilizes centrifugal forces for cell isolation. The separation units exploit both active and passive methods. In other words, in addition to introducing novel geometry for channels, an external magnetic field is also employed to separate the target cells from the background cells. In order for the external field to function, the CTCs must first be labeled with antibody-conjugated nanoparticles; the separation process should be then performed. Before the experimental tests, a numerical study was done to determine the optimum parameters; the angular velocity and magnetization investigations showed that 2000 rpm and 868,000 (kA/m) are the optimum conditions for the designed device to reach the efficiency of 100% for both White Blood Cells (WBCs) and CTCs. These results indicate that the passive region of the channels primarily contributes to the focusing of the target cells, and showed that the focusing effect is more pronounced in the expansion-contraction geometry compared to the zigzag geometry. Additionally, the results proved that curved channel geometries performed better than straight ones in terms of separation efficiency. However, if the separation relies solely on channel geometry, the majority of cells would be directed towards the non-target chamber, leading to suboptimal results. This is due to the direction of the forces acting on the cells. However, including an external magnetic field improves the direction of the net force and enhances the separation efficiency. Finally, the numerical and experimental results of the study were compared, and the curved expansion-contraction channel is introduced as the best geometry having 100% and ∼92% CTC separation efficiency, respectively.

Deep learning with microfluidics for on-chip droplet generation, control, and analysis

Droplet microfluidics has gained widespread attention in recent years due to its advantages of high throughput, high integration, high sensitivity and low power consumption in droplet-based micro-reaction. Meanwhile, with the rapid development of computer technology over the past decade, deep learning architectures have been able to process vast amounts of data from various research fields. Nowadays, interdisciplinarity plays an increasingly important role in modern research, and deep learning has contributed greatly to the advancement of many professions. Consequently, intelligent microfluidics has emerged as the times require, and possesses broad prospects in the development of automated and intelligent devices for integrating the merits of microfluidic technology and artificial intelligence. In this article, we provide a general review of the evolution of intelligent microfluidics and some applications related to deep learning, mainly in droplet generation, control, and analysis. We also present the challenges and emerging opportunities in this field.

Numerical study of a double-stair-shaped dielectrophoresis channel for continuous on-chip cell separation and lysis using finite element method

Prognostication of numerous chronic diseases are in need of identifying circulating tumor cells (CTCs), afterwards, separating and reviving contaminated samples are required. Conventional methods of separating blood cells, namely cytometry or magnetically activated cell sorting, in many cases lose their functionality, or efficiency under different conditions. Hence microfluidic methods of separation have been implemented. Herein, an innovative integrated double stair-shaped microchannel is designed and optimized, capable of 'separation', and 'chemical lysis' simultaneously in which the lysis reagent concentration can be controlled to tune the lysis intensity. The method of insulator-based dielectrophoresis (iDEP), which is the main physics in this device, is utilized yielding maximum separation. Pivotal features of the applied voltage, the voltage difference, the angles and the number of stairs, and the width of the throat in the microchannel have been numerically explored in order to optimize the channel in terms of separation and the lysis buffer concentration. The overall state of optimum case for the voltage difference (ΔV) of 10 owns the following features: the number of stairs is 2, the angle of stairs is 110°, the width of throat is 140 μm, and the inlet voltages are 30 V and 40 V. Also, the overall state of optimum cases for delta possess the following features: the number of stairs is 2, the angle of stairs is 110°, the width of throat is 140 μm, and the inlet voltages are 30 V and 35 V.

Characterization of Fluidic-Barrier-Based Particle Generation in Centrifugal Microfluidics

The fluidic barrier in centrifugal microfluidic platforms is a newly introduced concept for making multiple emulsions and microparticles. In this study, we focused on particle generation application to better characterize this method. Because the phenomenon is too fast to be captured experimentally, we employ theoretical models to show how liquid polymeric droplets pass a fluidic barrier before crosslinking. We explain how secondary flows evolve and mix the fluids within the droplets. From an experimental point of view, the effect of different parameters, such as the barrier length, source channel width, and rotational speed, on the particles’ size and aspect ratio are investigated. It is demonstrated that the barrier length does not affect the particle’s ultimate velocity. Unlike conventional air gaps, the barrier length does not significantly affect the aspect ratio of the produced microparticles. Eventually, we broaden this concept to two source fluids and study the importance of source channel geometry, barrier length, and rotational speed in generating two-fluid droplets.

Droplet Manipulation under a Magnetic Field: A Review

The magnetic manipulation of droplets is one of the emerging magnetofluidic technologies that integrate multiple disciplines, such as electromagnetics, fluid mechanics and so on. The directly driven droplets are mainly composed of ferrofluid or liquid metal. This kind of magnetically induced droplet manipulation provides a remote, wireless and programmable approach beneficial for research and engineering applications, such as drug synthesis, biochemistry, sample preparation in life sciences, biomedicine, tissue engineering, etc. Based on the significant growth in the study of magneto droplet handling achieved over the past decades, further and more profound explorations in this field gained impetus, raising concentrations on the construction of a comprehensive working mechanism and the commercialization of this technology. Current challenges faced are not limited to the design and fabrication of the magnetic field, the material, the acquisition of precise and stable droplet performance, other constraints in processing speed and so on. The rotational devices or systems could give rise to additional issues on bulky appearance, high cost, low reliability, etc. Various magnetically introduced droplet behaviors, such as deformation, displacement, rotation, levitation, splitting and fusion, are mainly introduced in this work, involving the basic theory, functions and working principles.

Droplet-based microfluidics in biomedical applications

Droplet-based microfluidic systems have been employed to manipulate discrete fluid volumes with immiscible phases. Creating the fluid droplets at microscale has led to a paradigm shift in mixing, sorting, encapsulation, sensing, and designing high throughput devices for biomedical applications. Droplet microfluidics has opened many opportunities in microparticle synthesis, molecular detection, diagnostics, drug delivery, and cell biology. In the present review, we first introduce standard methods for droplet generation (i.e., passive and active methods) and discuss the latest examples of emulsification and particle synthesis approaches enabled by microfluidic platforms. Then, the applications of droplet-based microfluidics in different biomedical applications are detailed. Finally, a general overview of the latest trends along with the perspectives and future potentials in the field are provided.

Architecture-Driven Fast Droplet Transport without Mass Loss

Spontaneous droplet transport without mass loss has great potential applications in the fields of energy and biotechnology, but it remains challenging due to the difficulty in obtaining a sufficient driving force for the transport while suppressing droplet mass loss. Learning from the slippery peristome of Nepenthes alata and wedge topology of a shorebird beak that can spontaneously feed water against gravity, a combined system consisting of two face-to-face hydrophilic slippery liquid-infused porous surfaces (SLIPS) with variable beak-like opening and spacing was proposed to constrain the droplet in-between and initiate fast droplet transport over a long distance of 75 mm with a maximum speed of 12.2 mm·s^-1 without mass loss by taking advantage of the Laplace pressure gradient induced by the asymmetric shape of the constrained droplet. The theoretical model based on the Navier-Stokes equation was developed to interpret the corresponding mechanism of the droplet transport process. In addition, in situ sophisticated droplet manipulations such as droplet mixing are readily feasible when applying flexible 304 stainless foil as the substrate of SLIPS. It is believed that extended research would contribute to new references for the precise and fast droplet motion control intended for energy harvest and water collection devices.

Atomic Scale Interactions between RNA and DNA Aptamers with the TNF-α Protein

Interest in the design and manufacture of RNA and DNA aptamers as apta-biosensors for the early diagnosis of blood infections and other inflammatory conditions has increased considerably in recent years. The practical utility of these aptamers depends on the detailed knowledge about the putative interactions with their target proteins. Therefore, understanding the aptamer-protein interactions at the atomic scale can offer significant insights into the optimal apta-biosensor design. In this study, we consider one RNA and one DNA aptamer that were previously used as apta-biosensors for detecting the infection biomarker protein TNF-α, as an example of a novel computational workflow for selecting the aptamer candidate with the highest binding strength to a target. We combine information from the binding free energy calculations, molecular docking, and molecular dynamics simulations to investigate the interactions of both aptamers with TNF-α. The results reveal that the RNA aptamer has a more stable structure relative to the DNA aptamer. Interaction of aptamers with TNF-α does not have any negative effect on its structure. The results of molecular docking and molecular dynamics simulations suggest that the RNA aptamer has a stronger interaction with the protein. Also, these findings illustrate that basic residues of TNF-α establish more atomic contacts with the aptamers compared to acidic or pH-neutral ones. Furthermore, binding energy calculations show that the interaction of the RNA aptamer with TNF-α is thermodynamically more favorable. In total, the findings of this study indicate that the RNA aptamer is a more suitable candidate for using as an apta-biosensor of TNF-α and, therefore, of greater potential use for the diagnosis of blood infections. Also, this study provides more information about aptamer-protein interactions and increases our understanding of this phenomenon.