A piezoelectrically actuated valveless micropump has been designed and developed. The principle components of this system are piezoelectrically actuated (PZT) metal diaphragms and a complete fluid flow system. The design of this pump mainly focuses on a cross junction, which is generated by a nozzle jet attached to a pump chamber and the intersection of two inlet channels and an outlet channel respectively. During each PZT diaphragm vibration cycle, the junction connecting the inlet and outlet channels with the nozzle jet permits consistencies in fluidic momentum and resistances in order to facilitate complete fluidic path throughout the system, in the absence of any physical valves. The entire micropump structure is fabricated as a plate-by-plate element of polymethyl methacrylate (PMMA) sheets and sandwiched to get required fluidic network as well as the overall device. In order to identify the flow characteristics, and to validate the test results with numerical simulation data, FEM analysis using ANSYS was carried out and an eigenfrequency analysis was performed to the PZT diaphragm using COMSOL Multiphysics. In addition, the control system of the pump was designed and developed to change the applied frequency to the piezoelectric diaphragms. The experimental data revealed that the maximum flow rate is 31.15 mL/min at a frequency of 100 Hz. Our proposed design is not only for a specific application but also useful in a wide range of biomedical applications.

This paper discusses an active droplet generation system, and the presented droplet generator successfully performs droplet generation using two fluid phases: continuous phase fluid and dispersed phase fluid. The performance of an active droplet generation system is analysed based on the droplet morphology using vision sensing and digital image processing. The proposed system in the study includes a droplet generator, camera module with image pre-processing and identification algorithm, and controller and control algorithm with a workstation computer. The overall system is able to control, sense, and analyse the generation of droplets. The main controller consists of a microcontroller, motor controller, voltage regulator, and power supply. Among the morphological features of droplets, the diameter is extracted from the images to observe the system performance. The MATLAB-based image processing algorithm consists of image acquisition, image enhancement, droplet identification, feature extraction, and analysis. RGB band filtering, thresholding, and opening are used in image pre-processing. After the image enhancement, droplet identification is performed by tracing the boundary of the droplets. The average droplet diameter varied from ~3.05 mm to ~4.04 mm in the experiments, and the average droplet diameter decrement presented a relationship of a second-order polynomial with the droplet generation time.