Increasing label-free stem cell sorting capacity to reach transplantation-scale throughput.

Dielectrophoresis (DEP) has proven an invaluable tool for the enrichment of populations of stem and progenitor cells owing to its ability to sort cells in a label-free manner and its biological safety. However, DEP separation devices have suffered from a low throughput preventing researchers from undertaking studies requiring large numbers of cells, such as needed for cell transplantation. We developed a microfluidic device designed for the enrichment of stem and progenitor cell populations that sorts cells at a rate of 150,000 cells/h, corresponding to an improvement in the throughput achieved with our previous device designs by over an order of magnitude.

Cavity-induced microstreaming for simultaneous on-chip pumping and size-based separation of cells and particles.

We present a microfluidic platform for simultaneous on-chip pumping and size-based separation of cells and particles without external fluidic control systems required for most existing platforms. The device utilizes an array of acoustically actuated air/liquid interfaces generated using dead-end side channels termed Lateral Cavity Acoustic Transducers (LCATs). The oscillating interfaces generate local streaming flow while the angle of the LCATs relative to the main channel generates a global bulk flow from the inlet to the outlet.

A microfabricated, optically accessible device to study the effects of mechanical cues on collagen fiber organization.

As the primary structural protein of our bodies, fibrillar collagen and its organizational patterns determine the biomechanics and shape of tissues. While the molecular assembly of individual fibrils is well understood, the mechanisms determining the arrangement of fibers and thus the shape and form of tissues remain largely unknown. We have developed a cell culture model that successfully recapitulates early tissue development and the de novo deposition of collagen fibers to investigate the role of mechanical cues on collagen fiber alignment.

A Laplace pressure based microfluidic trap for passive droplet trapping and controlled release.

Here, we present a microfluidic droplet trap that takes advantage of the net Laplace pressure force generated when a droplet is differentially constricted. Mathematical simulations were first used to understand the working range of the component; followed by finite element modeling using the CFD software package to further characterize the behavior of the system. Controlled release of the trapped droplets is also demonstrated through both a mechanical method and a chemical method that manipulates the total pressure exerted on the trapped droplet.

Novel on-demand droplet generation for selective fluid sample extraction.

A novel microfluidic device enabling selective generation of droplets and encapsulation of targets is presented. Unlike conventional methods, the presented mechanism generates droplets with unique selectivity by utilizing a K-junction design. The K-junction is a modified version of the classic T-junction with an added leg that serves as the exit channel for waste.

Machine Learning: A Crucial Tool for Sensor Design.

Sensors have been widely used for disease diagnosis, environmental quality monitoring, food quality control, industrial process analysis and control, and other related fields. As a key tool for sensor data analysis, machine learning is becoming a core part of novel sensor design. Dividing a complete machine learning process into three steps: data pre-treatment, feature extraction and dimension reduction, and system modeling, this paper provides a review of the methods that are widely used for each step.