Effects of the Gas Feed on Bubble Formation in a Microfluidic T-Junction: Constant-Pressure versus Constant-Flow-Rate Injection

Data-driven models for microfluidics: A short review

Microfluidic devices have many unique practical applications across a wide range of fields, making it important to develop accurate models of these devices, and many different models have been developed. Existing modeling methods mainly include mechanism derivation and semi-empirical correlations, but both are not universally applicable. In order to achieve a more accurate and general modeling process, the use of data-driven modeling has been studied recently. This review highlights recent advances in the application of data-driven modeling techniques for simulating and designing microfluidic devices. First, it introduces the application of traditional modeling approaches in microfluidics; subsequently, through different database sources, it reviews studies on data-driven modeling in three categories; and finally, it raises some open issues that require further investigation.

A general neural network model co-driven by mechanism and data for the reliable design of gas-liquid T-junction microdevices

In recent years, many models have been developed to describe the gas-liquid microdispersion process, which mainly rely on mechanistic analysis and may not be universally applicable. In order to provide a more comprehensive model and, most significantly, to provide a model for design, we have established a general database of microbubble generation in T-junction microdevices, including 854 data points from 12 pieces of literature. A neural network model that combines mechanistic and data modeling is developed. By transfer learning, more accurate results can be obtained. Additionally, we have proposed a design method that enables a relative deviation of less than 5% from the expected bubble size. A new device was designed and prepared to confirm the reliability of the method, which can prepare smaller bubbles than other common T-junction devices. In this way, a general and universal database and model are established and a design method for a gas-liquid T-junction microreactor is developed.

Closed-loop Control Systems for Pumps used in Portable Analytical Systems

The demand for accurate control of the flowrate/pressure in chemical analytical systems has given rise to the adoption of mechatronic approaches in analytical instruments. A mechatronic device is a synergistic system which combines mechanical, electronic, computer and control components. In the development of portable analytical devices, considering the instrument as a mechatronic system can be useful to mitigate compromises made to decrease space, weight, or power consumption. Fluid handling is important for reliability, however, commonly utilized platforms such as syringe and peristaltic pumps are typically characterized by flow/pressure fluctuations and slow responses. Closed loop control systems have been used effectively to decrease the difference between desired and realized fluidic output. This review discusses the way control systems have been implemented for enhanced fluidic control, categorized by pump type. Advanced control strategies used to enhance the transient and the steady state responses are discussed, along with examples of their implementation in portable analytical systems. The review is concluded with the outlook that the challenge in adequately expressing the complexity and dynamics of the fluidic network as a mathematical model has yielded a trend towards the adoption of experimentally informed models and machine learning approaches.

Quantitative study for control of air–liquid segmented flow in a 3D-printed chip using a vacuum-driven system

The formation of droplets or bubbles in a microfluidic system is a significant topic requiring device miniaturization and a small volume of samples. Especially, a two-phase segmented flow can be applied to micro-mixing for chemical reactions and the treatment of heat and mass transfer. In this study, a flow of liquid slugs and bubbles was generated in a 3D-printed chip and controlled by a single pump creating a vacuum at the outlet. The pump and chip device were integrated to form a simple and portable system. The size and flow rate of liquid slugs, obtained through image processing techniques, were analyzed considering several parameters related to hydraulic resistance and pressure drop. In addition, the effect of segmentation on mixing was observed by measuring the intensity change using two different colored inks. The hydraulic resistance of air and liquid flows can be controlled by changing the tube length of air flow and the viscosity of liquid flow. Because the total pressure drop along the channel was produced using a single pump at the outlet of the channel, the size and flow rate of the liquid slugs showed a near linear relation depending on the hydraulic resistances. In contrast, as the total pressure varied with the flow rate of the pump, the size of the liquid slugs showed a nonlinear trend. This indicates that the frequency of the liquid slug formation induced by the squeezed bubble may be affected by several forces during the development of the liquid slugs and bubbles. In addition, each volume of liquid slug segmented by the air is within the range of 10^–1 to 2 µL for this microfluidic system. The segmentation contributes to mixing efficiency based on the increased homogeneity factor of liquid. This study provides a new insight to better understand the liquid slug or droplet formation and predict the segmented flow based on the relationship between the resistance, flow rate, and pressure drop.