Project description:Monodisperse alginate microgels (10-50 μm) are created via droplet-based microfluidics by a novel crosslinking procedure. Ionic crosslinking of alginate is induced by release of chelated calcium ions. The process separates droplet formation and gelation reaction enabling excellent control over size and homogeneity under mild reaction conditions. Living mesenchymal stem cells are encapsulated and cultured in the generated 3D microenvironments.
Project description:Microbubbles have various applications including their use as carrier agents for localized delivery of genes and drugs and in medical diagnostic imagery. Various techniques are used for the production of monodisperse microbubbles including the Gyratory, the coaxial electro-hydrodynamic atomization (CEHDA), the sonication methods, and the use of microfluidic devices. Some of these techniques require safety procedures during the application of intense electric fields (e.g., CEHDA) or soft lithography equipment for the production of microfluidic devices. This study presents a hybrid manufacturing process using micropipettes and 3D printing for the construction of a T-Junction microfluidic device resulting in simple and low cost generation of monodisperse microbubbles. In this work, microbubbles with an average size of 16.6 to 57.7 μm and a polydispersity index (PDI) between 0.47% and 1.06% were generated. When the device is used at higher bubble production rate, the average diameter was 42.8 μm with increased PDI of 3.13%. In addition, a second-order polynomial characteristic curve useful to estimate micropipette internal diameter necessary to generate a desired microbubble size is presented and a linear relationship between the ratio of gaseous and liquid phases flows and the ratio of microbubble and micropipette diameters (i.e., Qg/Ql and Db/Dp) was found.
Project description:Droplet-based microfluidic systems have received much attention as promising tools for fabricating monodisperse microspheres of alginate solutions with high accuracy and reproducibility. The immediate and simple ionotropic gelation of alginate, its biocompatibility, and its tunability of mechanical properties make it a favorable hydrogel in the biomedical and tissue engineering fields. In these fields, micron-sized alginate hydrogel spheres have shown high potential as cell vehicles and drug delivery systems. Although on-chip microfluidic gelation of the produced alginate droplets is common, several challenges remain. Complicated chemical and microfabrication processes are required, and the risk of microchannel clogging is high. In the current study, we present an easy-to-use microfluidic external gelation process to produce highly spherical and monodisperse microspheres from very low-concentrated alginate-RGD solution [0.5% (w/v)]. To accomplish this, gelatin, a thermo-sensitive and inexpensive biomaterial, was incorporated into the alginate solution as a sacrificial biomaterial that mediates the off-chip external gelation of the alginate with Ca2+, and avoids droplet coalescence. Utilizing the methodology mentioned above, we successfully generated monodisperse alginate microspheres (AMs) with diameters ranging from 27 μm to 46 μm, with a coefficient of variation of 0.14, from a mixture of Arg-Gly-Asp (RGD)-modified very low viscosity alginate and gelatin. These RGD-AMs were used as microcarriers for human umbilical vein endothelial cells. The described easy-to-use and cost-effective microfluidic off-chip external gelation strategy exhibits comparable advantages to on-chip external gelation and demonstrates superiority over the latter since clogging is impossible.
Project description:Droplet based microfluidic systems provide an ideal platform for partitioning and manipulating aqueous samples for analysis. Identifying stable operating conditions under which droplets are generated is challenging yet crucial for real-world applications. A novel three-dimensional microfluidic platform that facilitates the consistent generation and gelation of alginate-calcium hydrogel microbeads for microbial encapsulation, over a broad range of input pressures, in the absence of surfactants is described. The unique three-dimensional design of the fluidic network utilizes a height difference at the junction between the aqueous sample injection and organic carrier channels to induce droplet formation via a surface tension enhanced self-shearing mechanism. Combined within a flow-focusing geometry, under constant pressure control, this arrangement facilitates predictable generation of droplets over a much broader range of operating conditions than that of conventional two-dimensional systems. The impact of operating pressures and geometry on droplet gelation, aqueous and organic material flow rates, microbead size, and bead generation frequency are described. The system presented provides a robust platform for encapsulating single microbes in complex mixtures into individual hydrogel beads, and provides the foundation for the development of a complete system for sorting and analyzing microbes at the single cell level.
Project description:Cell and islet microencapsulation in synthetic hydrogels provides an immunoprotective and cell-supportive microenvironment. A microfluidic strategy for the genaration of biofunctionalized, synthetic microgel particles with precise control over particle size and molecular permeability for cell and protein delivery is presented. These engineered capsules support high cell viability and function of encapsulated human stem cells and islets.
Project description:Here we develop a microfluidic device to generate monodispersion sub-nanoliter size droplets. Our system reaches steady state within 3 s after the flow starts and generates 100,000 droplets in 28 s with high size consistency (CV < 8%). This low cost device is composed with a microfluidic chip, 2 tubings, a collection vial, a syringe and a station; and is in the size of an iPad Mini (4" × 6" × 3/4"). In this system, all incoming reagents share the same pressure drop across the fluidic passage to generator droplets. A single source negative pressure is applied to the fluids to create the flow by a vacuum at the exit end of the device. The vacuum is generated on-site by pulling the plunger of a syringe. The position of the plunger before and after pulling determines the degree of vacuum. A fixture is used to hold the plunger after it is pulled to maintain its vacuum. Although this system loses vacuum gradually as the liquid filling in, it maintains a flow rates with the changes less than 10% and droplet sizes changes less than 2% during the course of generating 150,000 droplets. The pressure drop across the chip, the flow rates of all reagents, the droplet size and generation frequency are predictable, programmable, and reproducible. This device is designed for generating droplets for single cell genome profiling application but can be also used for digital PCR or other droplet-based applications.
Project description:Microencapsulation of biocides is used in long-life antifouling coating paints for marine applications and building materials. Here, we report the microfluidic production of calcium alginate (Ca-alginate) hydrogel particles to modulate the release of the encapsulated drug Irgarol (N-cyclopropyl-N'-(1,1-dimethylethyl)-6-(methylthio)-1,3,5-triazine-2,4-diamine), which is a hydrophobic and specifically phytotoxic antifoulant that inhibits photosystem II in aquatic plant species. We first encapsulated the drug inside the highly spherical Ca-alginate hydrogels of an average diameter ∼160 μm with a coefficient of variation of less than 4% and an average roundness of more than 0.96. The release speeds of the encapsulated and nonencapsulated drugs in pure water were measured separately by ultraviolet-visible spectroscopy. A stable and controllable release rate of the loaded drug was achieved by hydrophilic encapsulation. In addition, cellulose fibers were incorporated to enhance the mechanical strength of the hydrogels. Finally, the antifouling effect of the encapsulated drug was demonstrated using water grass (Bacopa monnieri).
Project description:The partitioned EDGE droplet generation device is known for its' high monodisperse droplet formation frequencies in two distinct pressure ranges, and an interesting candidate for scale up of microfluidic emulsification devices. In the current study, we test various continuous and dispersed phase properties and device geometries to unravel how the device spontaneously forms small monodisperse droplets (6-18 μm) at low pressures, and larger monodisperse droplets (>28 μm) at elevated pressures. For the small droplets, we show that the continuous phase inflow in the droplet formation unit largely determines droplet formation behaviour and the resulting droplet size and blow-up pressure. This effect was not considered as a factor of significance for spontaneous droplet formation devices that are mostly characterised by capillary numbers in literature. We then show for the first time that the formation of larger droplets is caused by physical interaction between neighbouring droplets, and highly dependent on device geometry. The insights obtained here are an essential step toward industrial emulsification based on microfluidic devices.
Project description:Microbubbles are used as contrast enhancing agents in ultrasound sonography and more recently have shown great potential as theranostic agents that enable both diagnostics and therapy. Conventional production methods lead to highly polydisperse microbubbles, which compromise the effectiveness of ultrasound imaging and therapy. Stabilizing microbubbles with surfactant molecules that can impart functionality and properties that are desirable for specific applications would enhance the utility of microbubbles. Here we generate monodisperse microbubbles with a large potential for functionalization by combining a microfluidic method and recombinant protein technology. Our microfluidic device uses an air-actuated membrane valve that enables production of monodisperse microbubbles with narrow size distribution. The size of microbubbles can be precisely tuned by dynamically changing the dimension of the channel using the valve. The microbubbles are stabilized by an amphiphilic protein, oleosin, which provides versatility in controlling the functionalization of microbubbles through recombinant biotechnology. We show that it is critical to control the composition of the stabilizing agents to enable formation of highly stable and monodisperse microbubbles that are echogenic under ultrasound insonation. Our protein-shelled microbubbles based on the combination of microfluidic generation and recombinant protein technology provide a promising platform for ultrasound-related applications.
Project description:Encapsulation of cells inside microfluidic droplets is central to several applications involving cellular analysis. Although, theoretically the encapsulation statistics are expected to follow a Poisson distribution, experimentally this may not be achieved due to lack of full control of the experimental variables and conditions. Therefore, there is a need for automatic detection of droplets and cell count enumeration within droplets so a process control feedback to adjust experimental conditions can be implemented. In this study, we use a deep learning object detector called You Only Look Once (YOLO), an influential class of object detectors with several benefits over traditional methods. This paper investigates the application of both YOLOv3 and YOLOv5 object detectors in the development of an automated droplet and cell detector. Experimental data was obtained from a microfluidic flow focusing device with a dispersed phase of cancer cells. The microfluidic device contained an expansion chamber downstream of the droplet generator, allowing for visualization and recording of cell-encapsulated droplet images. In the procedure, a droplet bounding box is predicted, then cropped from the original image for the individual cells to be detected through a separate model for further examination. The system includes a production set for additional performance analysis with Poisson statistics while providing an experimental workflow with both droplet and cell models. The training set is collected and preprocessed before labeling and applying image augmentations, allowing for a generalizable object detector. Precision and recall were utilized as a validation and test set metric, resulting in a high mean average precision (mAP) metric for an accurate droplet detector. To examine model limitations, the predictions were compared to ground truth labels, illustrating that the YOLO predictions closely matched with the droplet and cell labels. Furthermore, it is demonstrated that droplet enumeration from the YOLOv5 model is consistent with hand counted ratios and the Poisson distribution, confirming that the platform can be used in real-time experiments for cell encapsulation optimization.