An integrated microfluidic flow-focusing platform for on-chip fabrication and filtration of cell-laden microgels.

Microfluidic principles have been extensively utilized as powerful tools to fabricate controlled monodisperse cell-laden hydrogel microdroplets for various biological applications, especially tissue engineering. In this review, we report recent advances in microfluidic-based droplet fabrication and provide our rationale to justify the superiority of microfluidics-based techniques over other microtechnology methods in achieving the encapsulation of cells within hydrogels. The three main components of such a system—hydrogels, cells, and device configurations—are examined thoroughly. First, the characteristics of various types of hydrogels including natural and synthetic types, especially concerning cell encapsulation, are examined. This is followed by the elucidation of the reasoning behind choosing specific cells for encapsulation. Next, in addition to a detailed discussion of their respective droplet formation mechanisms, various device configurations including T-junctions, flow-focusing, and co-flowing that aid in achieving cell encapsulation are critically reviewed. We then present an outlook on the current applications of cell-laden hydrogel droplets in tissue engineering such as 3D cell culturing, rapid generation and repair of tissues, and their usage as platforms for studying cell–cell and cell–microenvironment interactions. Finally, we shed some light upon the prospects of microfluidics-based production of cell-laden microgels and propose some directions for forthcoming research that can aid in overcoming challenges currently impeding the translation of the technology into clinical success.

With the dramatic increment of complexity, more microfluidic devices require 3D structures, such as multi-depth and -layer channels. The traditional multi-step photolithography is time-consuming and labor-intensive and also requires precise alignment during the fabrication of microfluidic devices. Here, we present an inexpensive, single-step, and rapid fabrication method for multi-depth microfluidic devices using a high-resolution liquid crystal display (LCD) stereolithographic (SLA) three-dimensional (3D) printing system. With the pixel size down to 47.25 μm, the feature resolutions in the horizontal and vertical directions are 150 μm and 50 μm, respectively. The multi-depth molds were successfully printed at the same time and the multi-depth features were transferred properly to the polydimethylsiloxane (PDMS) having multi-depth channels via soft lithography. A flow-focusing droplet generator with a multi-depth channel was fabricated using the presented 3D printing method. Experimental results show that the multi-depth channel could manipulate the morphology and size of droplets, which is desired for many engineering applications. Taken together, LCD SLA 3D printing is an excellent alternative method to the multi-step photolithography for the fabrication of multi-depth microfluidic devices. Taking the advantages of its controllability, cost-effectiveness, and acceptable resolution, LCD SLA 3D printing can have a great potential to fabricate 3D microfluidic devices.

Microdroplets have been widely used in various biomedical applications. During droplet generation, parameters are manually adjusted to achieve the desired size of droplets. This process is tedious and time-consuming. In this paper, we present a fully automated system for controlling the size of droplets to optimize droplet generation parameters in a microfluidic flow-focusing device. The developed system employed a novel image processing program to measure the diameter of droplets from recorded video clips and correspondingly adjust the flow rates of syringe pumps to obtain the required diameter of droplets. The system was tested to generate phosphate-buffered saline and 8% polyethylene (glycol) diacrylate prepolymer droplets and regulate its diameters at various flow rates. Experimental results demonstrated that the difference between droplet diameters from the image processing and manual measurement is not statistically significant and the results are consistent over five repetitions. Taking the advantages of the accurate image processing method, the size of the droplets can be optimized in a precise and robust manner via automatically adjusting flow rates by the feedback control. The system was used to acquire quantitative data to examine the effects of viscosity and flow rates. Droplet-based experiments can be greatly facilitated by the automatic droplet generation and optimization system. Moreover, the system is able to provide quantitative data for the modelling and application of droplets with various conditions in a high-throughput way.