Microfluidic Network Research Articles

Microengineered 3D Collagen Gels with Independently Tunable Fiber Anisotropy and Directionality.

Cellular processes, including differentiation, proliferation, and migration, have been linked to the alignment (anisotropy) and orientation (directionality) of collagen fibers in the native extracellular matrix (ECM). Given the critical role that biophysical cell-matrix interactions play in regulating biological functions, several microfluidic-based methods have been used to establish 3D collagen gels with defined fiber properties; these gels have helped to establish quantitative relationships between structural ECM cues and observed cell responses. Although existing microfluidic fabrication methods provide excellent definition over collagen fiber anisotropy, they have not demonstrated the independent control over fiber anisotropy and directionality necessary to replicate in vivo collagen architecture. Therefore, to advance collagen microengineering capabilities, we present a user-friendly technology platform that uses controlled fluid flows within a non-uniform microfluidic channel network to create collagen landscapes that can be tuned as a function of extensional strain rate. Herein, we demonstrate capabilities to i) control the degree of fiber anisotropy, ii) create spatial gradients in fiber anisotropy, iii) independently define fiber directionality, and iv) generate multi-material interfaces within a 3D environment. We then address the practical issue of integrating cells into microfluidic systems by using a peel-off template technique to provide direct access to microengineered collagen gels, and demonstrate that cells respond to the defined properties of the landscape. Finally, the platform's modular capability is highlighted by integrating a sub-micrometer thick porous parylene membrane onto the microengineered collagen as a method to define cell-substrate interactions.

Reduction in sample injection bias using pressure gradients generated on chip.

Sample injection in microchip-based capillary zone electrophoresis (CZE) frequently rely on the use of electric fields which can introduce differences in the injected volume for the various analytes depending on their electrophoretic mobilities and molecular diffusivities. While such injection biases may be minimized by employing hydrodynamic flows during the injection process, this approach typically requires excellent dynamic control over the pressure gradients applied within a microfluidic network. The current article describes a microchip device that offers this needed control by generating pressure gradients on-chip via electrokinetic means to minimize the dead volume in the system. In order to realize the desired pressure-generation capability, an electric field was applied across two channel segments of different depths to produce a mismatch in the electroosmotic flow rate at their junction. The resulting pressure-driven flow was then utilized to introduce sample zones into a CZE channel with minimal injection bias. The reported injection strategy allowed the introduction of narrow sample plugs with spatial standard deviations down to about 45μm. This injection technique was later integrated to a capillary zone electrophoresis process for analyzing amino acid samples yielding separation resolutions of about 4-6 for the analyte peaks in a 3cm long analysis channel.

Toward Embedded Sensing Automation and Miniaturization for Portable Smart Cost-Effective Algae Monitor

As an important indicator of water pollution, algae are highly sensitive to changes in their environment and respond to a wide range of pollutants, they provide an early caution signal of worsening ecological condition. In this article, a kind of portable microfluidic lensless depth neural network algae monitor is proposed. The lensless algae image acquisition module, algae segmentation and classification circuit, and touch panel were integrated into the equipment. Therefore, the equipment can collect and analyze algae automatically in wild water body without laboratory. In order to miniaturize the equipment and reduce the cost, lensless microfluidic channel sampling is adopted. In addition, a dual asymmetric quantization algorithm and circuit structure are proposed for the implementation of deep neural network hardware. Finally, the prototype system construction was completed. Compared with the current analysis equipment, the equipment size and hardware cost are greatly reduced, and the accuracy reduction is kept in a small range, which makes a better compromise between the accuracy, hardware cost and circuit power consumption. The performance of the equipment fully meets the needs of the current portable algae monitor equipment, and the cost is greatly reduced compared with the current equipment. The accuracy of the equipment achieves 94.27%, the size achieves 11 * 11 * 17.5cm. These advances in portability and cost are conducive to promoting the transformation of water algae analysis based on artificial intelligence from large servers in the laboratory to portable algae analysis equipment, and promoting the rapid early analysis of water monitoring.

High-temperature high-pressure microfluidic system for rapid screening of supercritical CO2 foaming agents

CO2 foam helps to increase the viscosity of CO2 flood fluid and thus improve the process efficiency of the anthropogenic greenhouse gas’s subsurface utilization and sequestration. Successful CO2 foam formation mandates the development of high-performance chemicals at close to reservoir conditions, which in turn requires extensive laboratory tests and evaluations. This work demonstrates the utilization of a microfluidic reservoir analogue for rapid evaluation and screening of commercial surfactants (i.e., Cocamidopropyl Hydroxysultaine, Lauramidopropyl Betaine, Tallow Amine Ethoxylate, N,N,N′ Trimethyl-N′-Tallow-1,3-diaminopropane, and Sodium Alpha Olefin Sulfonate) based on their performance to produce supercritical CO2 foam at high salinity, temperature, and pressure conditions. The microfluidic analogue was designed to represent the pore sizes of the geologic reservoir rock and to operate at 100 °C and 13.8 MPa. Values of the pressure drop across the microfluidic analogue during flow of the CO2 foam through its pore network was used to evaluate the strength of the generated foam and utilized only milliliters of liquid. The transparent microfluidic pore network allows in-situ quantitative visualization of CO2 foam to calculate its half-life under static conditions while observing if there is any damage to the pore network due to precipitation and blockage. The microfluidic mobility reduction results agree with those of foam loop rheometer measurements, however, the microfluidic approach provided more accurate foam stability data to differentiate the foaming agent as compared with conventional balk testing. The results obtained here supports the utility of microfluidic systems for rapid screening of chemicals for carbon sequestration or enhanced oil recovery operations.

Spacing Optimization for Active Droplet Sorting in Microfluidic Networks Using Genetic Algorithm

Sorting is an important operation in droplet microfluidics. In this paper, we propose a novel, active technique for sorting of drops. The technique involves sending of drops to a one-dimensional (1...

Microfluidic capillary networks are more sensitive than ektacytometry to the decline of red blood cell deformability induced by storage

Ektacytometry has been the primary method for evaluating deformability of red blood cells (RBCs) in both research and clinical settings. This study was designed to test the hypothesis that the flow of RBCs through a network of microfluidic capillaries could provide a more sensitive assessment of the progressive impairment of RBC deformability during hypothermic storage than ektacytometry. RBC units (n = 9) were split in half, with one half stored under standard (normoxic) conditions and the other half stored hypoxically, for up to 6 weeks. RBC deformability was measured weekly using two microfluidic devices, an artificial microvascular network (AMVN) and a multiplexed microcapillary network (MMCN), and two commercially available ektacytometers (RheoScan-D and LORRCA). By week 6, the elongation indexes measured with RheoScan-D and LORRCA decreased by 5.8–7.1% (5.4–6.9% for hypoxic storage). Over the same storage duration, the AMVN perfusion rate declined by 27.5% (24.5% for hypoxic) and the MMCN perfusion rate declined by 49.0% (42.4% for hypoxic). Unlike ektacytometry, both AMVN and MMCN measurements showed statistically significant differences between the two conditions after 1 week of storage. RBC morphology deteriorated continuously with the fraction of irreversibly-damaged (spherical) cells increasing significantly faster for normoxic than for hypoxic storage. Consequently, the number of MMCN capillary plugging events and the time MMCN capillaries spent plugged was consistently lower for hypoxic than for normoxic storage. These data suggest that capillary networks are significantly more sensitive to both the overall storage-induced decline of RBC deformability, and to the differences between the two storage conditions, than ektacytometry.

Programmable microfluidic flow for automatic multistep digital assay in a single-sheet 3-dimensional paper-based microfluidic device

A single-sheet 3-dimensional paper-based microfluidic analytical device (3D-μPAD) has a user-friendly compact format that eliminates any potential for user alignment error compared to the stacking and folding format. However, achieving sophisticated analysis is still a challenge because forming a complex 3D microfluidic network sufficient for performing analysis in a single sheet of paper is difficult. Here, we present the first report of automatic multistep digital analysis in a single-sheet 3D-μPAD created by controlling the penetration of different wax inks into paper. Simple printing of different wax inks with different spreading properties produces different dimension microchannels in paper. This controllable change in the dimensions of the microchannels results in different flow rates of fluid in each microchannel. Based on the spatial resolution of the microchannels, our strategy enables programming of microfluidic flow through manipulation of the fluidic time delay. This approach creates 3D-μPADs capable of sequential fluid delivery and multistep biochemical reactions with single loading of a sample solution. The methodology can be further expanded to combination with digital assays to measure the concentration of a target analyte by simply counting the number of colored bars at a fixed time. It does not require any external instruments to analyze the measurement of the target analyte concentration. The significance of this work lies in the promising potential for automatic multistep digital assays in a low-cost and easy-to-use paper-based format that can be integrated with a roll-to-roll process for commercial-scale manufacturing.

Integration of capillary–hydrodynamic logic circuitries for built-in control over multiple droplets in microfluidic networks

Here, we show the successful implementation of advanced sequential logic in droplet microfluidics, whose principles rely on capillary wells establishing stationary states, where droplets can communicate remotely via pressure impulses, influencing each other and switching the device states. All logic operations perform spontaneously due to the utilization of nothing more than capillary-hydrodynamic interactions, inherent for the confined biphasic flow. Our approach offers integration feasibility allowing to encode unprecedentedly long algorithms, e.g., 1000-droplet counting. This work has the potential for the advancement of liquid computers and thereby could participate in the development of the next generation of portable microfluidic systems with embedded control, enabling applications from single-cell analysis and biochemical assays to materials science.

Predicting the fluid behavior of random microfluidic mixers using convolutional neural networks.

With the various applications of microfluidics, numerical simulation is highly recommended to verify its performance and reveal potential defects before fabrication. Among all the simulation parameters and simulation tools, the velocity field and concentration profile are the key parts and are generally simulated using finite element analysis (FEA). In our previous work [Wang et al., Lab Chip, 2016, 21, 4212-4219], automated design of microfluidic mixers by pre-generating a random library with the FEA was proposed. However, the duration of the simulation process is time-consuming, while the matching consistency between limited pre-generated designs and user desire is not stable. To address these issues, we inventively transformed the fluid mechanics problem into an image recognition problem and presented a convolutional neural network (CNN)-based technique to predict the fluid behavior of random microfluidic mixers. The pre-generated 10 513 candidate designs in the random library were used in the training process of the CNN, and then 30 757 brand new microfluidic mixer designs were randomly generated, whose performance was predicted by the CNN. Experimental results showed that the CNN method could complete all the predictions in just 10 seconds, which was around 51 600× faster than the previous FEA method. The CNN library was extended to contain 41 270 candidate designs, which has filled up those empty spaces in the fluid velocity versus solute concentration map of the random library, and able to provide more choices and possibilities for user desire. Besides, the quantitative analysis has confirmed the increased compatibility of the CNN library with user desire. In summary, our CNN method not only presents a much faster way of generating a more complete library with candidate mixer designs but also provides a solution for predicting fluid behavior using a machine learning technique.

Distributed colorimetric interferometer for mapping the pressure distribution in a complex microfluidics network.

We demonstrate a novel platform for mapping the pressure distribution of complex microfluidics networks with high spatial resolution. Our approach utilizes colorimetric interferometers enabled by lossy optical resonant cavities embedded in a silicon substrate. Detection of local pressures in real-time within a fluid network occurs by monitoring a reflected color emanating from each optical cavity. Pressure distribution measurements spanning a 1 cm2 area with a spatial resolution of 50 μm have been achieved. We applied a machine-learning-assisted sensor calibration method to generate a dynamic measurement range from 0 to 5.0 psi, with 0.2 psi accuracy. Adjustments to this dynamic measurement range are possible to meet different application needs for monitoring flow conditions in complex microfluidics networks, for the timely detection of anomalies such as clogging or leakage at their occurring locations.

Application of centrifugal microfluidics in immunoassay, biochemical analysis and molecular diagnosis.

Rapid diagnosis plays a vital role in daily life and is effective in reducing treatment costs and increasing curability, especially in remote areas with limited availability of resources. Among the various common methods of rapid diagnosis, centrifugal microfluidics has many unique advantages, such as less sample consumption, more precise valve control for sequential loading of samples, and accurately separated module design in a microfluidic network to minimize cross-contamination. Therefore, in recent years, centrifugal microfluidics has been extensively researched, and it has been found to play important roles in biology, chemistry, and medicine. Here, we review the latest developments in centrifugal microfluidic platforms in immunoassays, biochemical analyses, and molecular diagnosis, in recent years. In immunoassays, we focus on the application of enzyme-linked immunosorbent assay (ELISA); in biochemical analysis, we introduce the application of plasma and blood cell separation; and in molecular diagnosis, we highlight the application of nucleic acid amplification tests. Additionally, we discuss the characteristics of the methods under each platform as well as the enhancement of the corresponding performance parameters, such as the limit of detection, separation efficiency, etc. Finally, we discuss the limitations associated with the existing applications and potential breakthroughs that can be achieved in this field in the future.

Evaluation of 3D printed microfluidic networks to study fluid flow in rocks

Visualizing fluid flow in porous media can provide a better understanding of transport phenomena at the pore scale. In this regard, transparent micromodels are suitable tools to investigate fluid flow in porous media. However, using glass as the primary material makes them inappropriate for predicting the natural behavior of rocks. Moreover, constructing these micromodels is time-consuming via conventional methods. Thus, an alternative approach can be to employ 3D printing technology to fabricate representative porous media. This study investigates fluid flow processes through a transparent microfluidic device based on a complex porous geometry (natural rock) using digital-light processing printing technology. Unlike previous studies, this one has focused on manufacturing repeatability. This micromodel, like a custom-built transparent cell, is capable of modeling single and multiphase transport phenomena. First, the tomographic data of a carbonate rock sample is segmented and 3D printed by a digital-light processing printer. Two miscible and immiscible tracer injection experiments are performed on the printed microfluidic media, while the experiments are verified with the same boundary conditions using a CFD simulator. The comparison of the results is based on Structural Similarity Index Measure (SSIM), where in both miscible and immiscible experiments, more than 80% SSIM is achieved. This confirms the reliability of printing methodology for manufacturing reusable microfluidic models as a promising and reliable tool for visual investigation of fluid flow in porous media. Ultimately, this study presents a novel comprehensive framework for manufacturing 2.5D realistic microfluidic devices (micromodels) from pore-scale rock images that are validated through CFD simulations.

Modeling-Guided Design of Paper Microfluidic Networks: A Case Study of Sequential Fluid Delivery.

Paper-based microfluidic devices are popular for their ability to automate multistep assays for chemical or biological sensing at a low cost, but the design of paper microfluidic networks has largely relied on experimental trial and error. A few mathematical models of flow through paper microfluidic devices have been developed and have succeeded in explaining experimental flow behavior. However, the reverse engineering problem of designing complex paper networks guided by appropriate mathematical models is largely unsolved. In this article, we demonstrate that a two-dimensional paper network (2DPN) designed to sequentially deliver three fluids to a test zone on the device can be computationally designed and experimentally implemented without experimental trial and error. This was accomplished by three new developments in modeling flow through paper networks: (i) coupling of the Richards equation of flow through porous media to the species transport equation, (ii) modeling flow through assemblies of multiple paper materials (test membrane and wicking pad), and (iii) incorporating limited-volume fluid sources. We demonstrate the application of this model in the optimal design of a paper-based signal-enhanced immunoassay for a malaria protein, PfHRP2. This work lays the foundation for the development of a computational design toolbox to aid in the design of paper microfluidic networks.

Evolution of Thin-Liquid Films Surrounding Bubbles in Microfluidics and Their Impact on the Pressure Drop and Fluid Movement.

The evolution of thin-liquid films in a microchannel is one of the most critical and intricate phenomena to understand two-phase movement, evaporation, micromixing, heat transfer, chemical synthesis, biological processes, and efficient energy devices. In this paper, we demonstrate experimentally the effect of a liquid film on the removal of an initially dry and lodged bubble in laser-etched poly(methyl methacrylate) microfluidic networks and discuss the evolution of the liquid film in accordance with the bubble superficial velocity and the effect of liquid properties and branch angle on the evolution of the liquid film and the pressure drop. During the removal of a dry bubble, four stages have been observed in the bubble velocity profile and they directly relate to the evolution of the liquid film. The correlation of maximum bubble velocity has been derived as a function of bubble length, fluid viscosity, surface tension, geometry of the cross-sectional area, and dimensions of the microchannel and agrees with the experimental results. The bubble moving distance required for the full deposition of a continuous and stable thin-liquid film is affected by the liquid viscosity and network branch angle. The liquid with a higher viscosity will increase the pressure drop for removing dry bubbles from microfluidic networks, while this effect will be hampered by increasing the microfluidic network complexity. The deposition of the thin-liquid film surrounding bubbles significantly decreases the pressure drop required to remove bubbles from microfluidics. Compared with deionized water, the glycerol solution is prone to acting as the lubricating liquid due to its strong H-bond interaction with the channel wall and the reduction in interfacial energy of the gas-water interface.

Organ‐on‐a‐Chip: A Preclinical Microfluidic Platform for the Progress of Nanomedicine

Despite the progress achieved in nanomedicine during the last decade, the translation of new nanotechnology-based therapeutic systems into clinical applications has been slow, especially due to the lack of robust preclinical tissue culture platforms able to mimic the in vivo conditions found in the human body and to predict the performance and biotoxicity of the developed nanomaterials. Organ-on-a-chip (OoC) platforms are novel microfluidic tools that mimic complex human organ functions at the microscale level. These integrated microfluidic networks, with 3D tissue engineered models, have been shown high potential to reduce the discrepancies between the results derived from preclinical and clinical trials. However, there are many challenges that still need to be addressed, such as the integration of biosensor modules for long-time monitoring of different physicochemical and biochemical parameters. In this review, recent advances on OoC platforms, particularly on the preclinical validation of nanomaterials designed for cancer, as well as the current challenges and possible future directions for an end-use perspective are discussed.

Contactless acoustic micro/nano manipulation: a paradigm for next generation applications in life sciences.

Acoustic actuation techniques offer a promising tool for contactless manipulation of both synthetic and biological micro/nano agents that encompass different length scales. The traditional usage of sound waves has steadily progressed from mid-air manipulation of salt grains to sophisticated techniques that employ nanoparticle flow in microfluidic networks. State-of-the-art in microfabrication and instrumentation have further expanded the outreach of these actuation techniques to autonomous propulsion of micro-agents. In this review article, we provide a universal perspective of the known acoustic micromanipulation technologies in terms of their applications and governing physics. Hereby, we survey these technologies and classify them with regards to passive and active manipulation of agents. These manipulation methods account for both intelligent devices adept at dexterous non-contact handling of micro-agents, and acoustically induced mechanisms for self-propulsion of micro-robots. Moreover, owing to the clinical compliance of ultrasound, we provide future considerations of acoustic manipulation techniques to be fruitfully employed in biological applications that range from label-free drug testing to minimally invasive clinical interventions.

Microchannels with Self-Pumping Walls.

When asymmetric Janus micromotors are immobilized on a surface, they act as chemically powered micropumps, turning chemical energy from the fluid into a bulk flow. However, such pumps have previously produced only localized recirculating flows, which cannot be used to pump fluid in one direction. Here, we demonstrate that an array of three-dimensional, photochemically active Au/TiO2 Janus pillars can pump water. Upon UV illumination, a water-splitting reaction rapidly creates a directional bulk flow above the active surface. By lining a 2D microchannel with such active surfaces, various flow profiles are created within the channels. Analytical and numerical models of a channel with active surfaces predict flow profiles that agree very well with the experimental results. The light-driven active surfaces provide a way to wirelessly pump fluids at small scales and could be used for real-time, localized flow control in complex microfluidic networks.

Microfluidic Biomaterials.

Since their initial description in 2005, biomaterials that are patterned to contain microfluidic networks ("microfluidic biomaterials") have emerged as promising scaffolds for a variety of tissue engineering and related applications. This class of materials is characterized by the ability to be readily perfused. Transport and exchange of solutes within microfluidic biomaterials is governed by convection within channels and diffusion between channels and the biomaterial bulk. Numerous strategies have been developed for creating microfluidic biomaterials, including micromolding, photopatterning, and 3D printing. In turn, these materials have been used in many applications that benefit from the ability to perfuse a scaffold, including the engineering of blood and lymphatic microvessels, epithelial tubes, and cell-laden tissues. This article reviews the current state of the field and suggests new areas of exploration for this unique class of materials.

Development of a pancreas-liver organ-on-chip coculture model for organ-to-organ interaction studies

Type 2 diabetes mellitus (T2DM) is a widespread chronic disease with a high prevalence of comorbidity and mortality. The exponential increase of TD2M represents an important public health challenge and leads a strong demand for the development of relevant in vitro models to improve mechanistic understanding of diabetes and identify new anti-diabetic drugs and therapies. These models involve considering the multi-organ characteristic of T2DM. The organ-on-chip technology has made it possible to connect several organs thanks to dedicated microbioreactors interconnected by microfluidic network. Here, we developed pancreas-liver coculture model in a microfluidic biochip, using rat islets of Langerhans and hepatocytes. The behavior and functionality of the model were compared to islets and hepatocytes (with/without insulin) monocultures. Compared to monoculture, the islets coculture presented high C-peptide and insulin secretions, and downregulation of Pdx1, Glut2, App, Ins1, Neurod, Neurog3 and Gcgr genes. In the hepatic compartment, the monocultures without insulin were negative to CK18 staining and displayed a weaker albumin production, compared to monoculture with insulin. The hepatocytes cocultures were highly positive to INSR, GLUT2, CK18 and CYP3A2 immunostaining and allowed to recover mRNA levels similar to monocultures with insulin. The result showed that islets could produce insulin to supplement the culture medium and recover hepatic functionality. This model illustrated the potential of organ-on-chip technology for reproducing crosstalk between liver and pancreas.

From CAD to microfluidic chip within one day: rapid prototyping of lab-on-chip cartridges using generic polymer parts

We report on a novel rapid prototyping approach for the manufacturing of highly individualized lab-on-chip (LoC) cartridges from generic polymer parts by laser micromachining and laser welding. The approach allows an immediate implementation of microfluidic networks, components, and functionalities into an existing LoC platform without the need for an expensive and time-consuming fabrication of production tools like molds or masks. We comprehensively describe the individual process steps of the rapid prototyping procedure including a wet-chemical treatment for an easy and effective surface polishing of laser micromachined polymer parts. For laying out, we introduce a generalized diagrammatic description of microfluidic functional units in order to design application-specific cartridges for molecular diagnostic workflows. We demonstrate the usability of our prototyped cartridges by performing microfluidic experiments within. Due to the use of generic polymer parts, our rapid prototyping approach combines a high degree of freedom with an intrinsic compatibility to an established and highly developed LoC system. By enabling an experimental testing within one day, the rapid prototyping procedure shortens development cycles and boosts the evolution of microfluidic networks as well as the implementation of novel microfluidic components and functionalities.