This paper comprehensively reviews the fundamental principles, innovative designs, and multidisciplinary applications of micromixers. First, it introduces the fundamental principles of fluid mixing in micromixers, including passive and active mixing mechanisms, and the flow characteristics of fluids at the microscale. Subsequently, it focuses on the innovative design of passive micromixers, covering a variety of designs, such as obstacle structures, curved serpentine structures, groove structures, separation and recombination structures, topology optimization structures, and baffle structures, and analyzes the effects of different structures on mixing efficiency and pressure drop. In addition, it also studies the innovative design of active micromixers, including magnetic field assistance, electric field assistance, surface acoustic wave assistance, and thermal effect assistance, and analyzes the effects of different driving modes on mixing efficiency. Finally, it outlines the multidisciplinary applications of micromixers in the fields of biomedicine, chemical analysis, environmental monitoring and control, and new energy. This review aims to provide a comprehensive reference for the research and application of micromixers and promote their application in more fields.

In the field of marine engineering, the friction and wear experienced by rotating mechanisms are recognized as significant contributors to the failure of marine machinery. In order to enhance the safety and dependability of marine ship operations, the implementation of on-line oil wear debris particle detection sensors enables the on-line monitoring of oil and facilitates the rapid identification of abnormal wear locations. This paper provides a critical review of the recent research progress and development trends in the field of sensors for on-line detection of oil wear debris particles. According to the method of sensor detection, wear debris particle detection sensors can be classified into two distinct categories: electrical and non-electrical sensors. Electrical sensors encompass a range of types, including inductive, capacitive, and resistive sensors. Non-electrical sensors encompass a range of technologies, such as image processing sensors, optical sensors, and ultrasonic sensors. Finally, this review addresses the future research directions for wear debris particle detection sensors in light of the challenging problems currently faced by these sensors.

Metallic contaminants (solid) are generated by friction pair, causing wear of equipment by enters the lubricating system. This poses a great potential threat to the normal operation of such machines. The timely analysis and detection of debris can lead to the avoidance of mechanical failures. Abnormal wear in machinery may produce debris exceeding 10 μm. The traditional inductance detection method has low sensitivity and cannot meet the actual detection requirements. To boost the sensitivity of the inductance sensor, the mutual inductance of coils and the strong magnetic conductivity of permalloy was utilized to design a high sensitivity inductance sensor for the detection of debris in lubricating oil. This design was able to detect 10–15 μm iron particles and 65–70 μm copper particles in the oil. The experimental results illustrate that low-frequency excitation is the best for detecting ferromagnetic particles, while high-frequency excitation has the best effect for detecting non-ferromagnetic particles. This paper demonstrates the significant advantages of coil mutual inductance, and strong magnetic conductivity of permalloy in improving the detection sensitivity of oil debris sensors. This will provide technical support for wear detection in mechanical equipment and fault diagnosis.

Shanhu Qiu, M.D., Ziwei Du, M.S., Wei Li , Ph.D., Juan Chen, Ph.D., Hang Wu, Ph.D., Jingbao Liu, M.S., Min Cai, M.S., Bei Wang, Ph.D., Haijian Guo, Ph.D., and Zilin Sun, M.D., Ph.D.. Ann Lab Med 2020;40:457-65. https://doi.org/10.3343/alm.2020.40.6.457

Most of the sensors currently used for wind turbine generator system oil detection can only perform measurements of a single physical quantity, and some sensors are capable of measuring multiple contaminants but require switching modes to achieve this, making it impossible to detect various oil contaminants simultaneously. These methods not only require the addition of numerous sensors and burden the wind turbine generator system piping, but also increase the time and cost of maintenance and inspection. In addition, it may be unable to respond quickly to specific emergencies. To address these limitations, this study proposes an LC-based passive dual solenoid coil multi-contaminant oil detection sensor. An analytical expression for the magnetic field strength of the dual solenoidal coil is derived, and a corresponding mathematical model is developed. The validity of the model is verified compared it with the finite element analysis results. An experimental verification was carried out. The experimental results show that the sensor can recognize multiple oil pollutants simultaneously according to different signal curves without switching modes. The sensor can detect iron particles with diameters larger than 38 μm, copper particles with diameters larger than 100 μm, liquid droplets with diameters larger than 100-110 μm, and air bubbles with diameters larger than 180-190 μm. By comparing with the existing sensors, the LC-based passive dual-coil multi-pollutant oil detection sensor proposed in this paper has a broad application prospect in real-time monitoring of wind turbine oil conditions.

An ultrasensitive debris sensor based on microfluidic technology is introduced in this article. The microsensor not only achieves the traditional inductance detection, but also proposes a resistance detection method based on coil. The magnetic field distribution in the detection region was obtained by simulation, and the magnetization and eddy current effects of metal particles in harmonic magnetic field were simulated. The frequency characteristics and signal characteristics of inductance and resistance detection were studied through experiments. High-frequency excitation can enhance the eddy current effect inside the metal particles, thereby helping to improve the resistance detection sensitivity, enhance the inductance detection effect of nonferromagnetic metal particles, and reduce the inductance detection effect of ferromagnetic metal particles. The research results showed that inductance parameter has stronger detection ability for ferromagnetic metals, and resistance parameter has stronger detection ability for nonferromagnetic metals. According to the characteristics of inductance and resistance signals, the accurate distinction of metal debris property and size can be realized. And the size measurement error caused by the debris shape can be reduced by the judgment method based on two parameters. This impedance detection based on inductance and resistance parameters provides a new method for high-sensitivity monitoring of metal debris. The debris microsensor can be used as a sensing element of portable oil monitoring devices, and provide technical support for health assessment, state warning, and fault diagnosis of mechanical equipment.