Contributors: Tomasz Zablotny, Marie Hébert, William Baxter, David Wong, Carolyn L. Ren
Applications of microfluidics as a tool outside of the field are limited. End-users face too many barriers to easily incorporate microfluidic tools in their procedure. Consequently, the contribution of microfluidics outside of the development field itself is somewhat limited; its impact would be much greater if microfluidic tools could be inexpensive, repeatable, and accessible. The development of a platform for the active control of individual droplets is envisioned to lower the knowledge barrier by only requiring high-level information from the user to operate. The main projects are described in more detail below.
- Manual control with mouse movement
The proof-of-concept stage of the active droplet control platform involved the combination of a controller with pressure actuation and visual feedback. Droplets can be generated, trapped, split, and merged in any order according to the users’ instruction. The input from the user is acquired using a standard computer mouse.
(Caption) Step change of a droplet and interface position independently of each other enabled by the controller using visual feedback and pressure actuation. The coupled dynamics between the channels introduces a disturbance in the other channel. (Wong 2016)
- Semi-automated control
The accuracy and repeatability of the droplet manipulations are improved using an additional higher-level algorithm. The user can input the length of a droplet to generate for example. The algorithm then performs the required process to generate a droplet of the specified length. Splitting can also be achieved according to a specified ratio in percentage.
(Caption) Process of the automated generation of a droplet 500 μm long. (Hébert 2019)
(Caption) Accuracy performance for the automated generation of droplets. (Hébert 2019)
The ability of the semi-automated manipulations is confirmed using a sample drug screening assay. The introduction of an inhibitor (Orange G) is verified to decrease fluorescent intensity that is an indicator of aggregation. This part of the project is supported by Matthew Courtney.
(Caption) Fluorescent intensity indicative of the aggregation for drug screening purposes. Introducing an inhibitor (Orange G) is demonstrated to lower the intensity change, and thus, the aggregation. (Hébert 2019)
- Modular system
The semi-automated manipulations are implemented into modules that can be assembled to perform various tasks. The instructions required by the user are high-level procedures. Moreover, the standalone system is compact and lowers equipment costs. One part of the equipment cost reduction is provided by an open-source pressure pump (Gao 2020).
(Caption) Schematic representation of the different components of the open-source pressure pump for a microfluidic system. (Gao 2020)
3.1 Alterative Sensing
Conventional sensing in microfluidics offer severe limitations in terms of high cost, and large form factors. Alterative sensing techniques that remove the need for expensive sensors while providing comparable quality offer a solution. Using novel sensors and state of the art algorithms one can fit an entire alterative sensing system in the palm of your hand!
- Modelling the system
The understanding of the system through the model is improved using various approaches. A simple fabrication method for a soft strain sensor using graphene and Silly PuttyTM is developed to measure the strain of the soft air tubing. The tubing dynamics are quantified using pressure sensors. Further experimental methods are implemented for the experimental justification of the model used for controller design.
Bibliography
Gao, Run Ze, Hébert, Marie, Jan Huissoon, and Carolyn L. Ren "µPump: An Open-Source Pressure Pump for Precision Fluid Handling in Microfluidics." HardwareX (2020): e00096.
Hébert, Marie, Matthew Courtney, and Carolyn L. Ren. "Semi-automated on-demand control of individual droplets with a sample application to a drug screening assay." Lab on a Chip 19.8 (2019): 1490-1501.
Wong, David, and Carolyn L. Ren. "Microfluidic droplet trapping, splitting and merging with feedback controls and state space modelling." Lab on a Chip 16.17 (2016): 3317-3329.
Wong, Yuk Hei (David). Feedback Controls in Droplet Microfluidics. MS thesis. University of Waterloo, 2016.