Micromixers, as crucial components of microfluidic devices, find widespread applications in the field of biochemistry. Due to the laminar flow in microchannels, mixing is challenging, and it significantly impacts the efficiency of rapid reactions. In this study, numerical simulations of four baffle micromixer structures were carried out at different Reynolds numbers (Re = 0.1, Re = 1, Re = 10, and Re = 100) in order to investigate the flow characteristics and mixing mechanism under different structures and optimize the micromixer by varying the vertical displacement of the baffle, the rotation angle, the horizontal spacing, and the number of baffle, and by taking into account the mixing intensity and pressure drop. The results indicated that the optimal mixing efficiency was achieved when the baffle’s vertical displacement was 90 μm, the baffle angle was 60°, the horizontal spacing was 130 μm, and there were 20 sets of baffles. At Re = 0.1, the mixing efficiency reached 99.4%, and, as Re increased, the mixing efficiency showed a trend of, first, decreasing and then increasing. At Re = 100, the mixing efficiency was 97.2%. Through simulation analysis of the mixing process, the structure of the baffle-type micromixer was effectively improved, contributing to enhanced fluid mixing efficiency and reaction speed.

The cleanliness of lubricating oil plays a key role in determining the operational health of mechanical systems, serving as a critical metric that delineates the extent of equipment wear. In this study, we present a magnetic-core-type planar coil particle detection sensor. The detection accuracy and detection limit are improved by optimizing the magnetic field inside the sensor. The optimization of the magnetic field is achieved through the finite element simulation analysis of the coil and the magnetic core. First, the finite element simulation software COMSOL 6.0 is used to model the sensor in three dimensions (3D). Then, we study the distribution of the magnetic field under different coil radii, core conductivity levels, and other parameters. We obtain the sensor structure after optimizing the magnetic field. The sensor is made using experimental methods, and the iron particles and copper particles are detected. The results show that the lower limit of detection of iron particles can reach 46 μm, and the lower limit of detection of copper particles can reach 110 μm.

Oil analysis is one of the main means to obtain the working status of important friction pairs in ship and Marine engineering equipment at present. Analyzing the wear mechanism by analyzing the particle size, morphology, properties and other characteristics of metal abrasive particles in the oil is an important basis for achieving health monitoring and scientific maintenance of ship and Marine engineering equipment. Classifying the abrasive particles in the oil according to their particle size is an important step in sample pretreatment. This paper proposes a two-stage sorting microfluidic chip for wear debris based on magnetophoresis. By setting up external permanent magnets in a stepwise manner in the primary and secondary sorting areas, gradient magnetic fields of different magnitudes were formed. The effects of different sample flow rates, sheath fluid flow rates and sheath flow ratios on the pre-focusing before sorting and the sorting effect were studied. The primary sorting of ferromagnetic metal wear particles larger than 50 µm and the secondary sorting of those smaller than 50 µm have been achieved. The primary sorting can serve as an early warning for abnormal equipment wear, while the secondary sorting can provide data support for the scientific formulation of maintenance plans based on equipment requirements. This work provides a new idea and method for the rapid determination of lubricating oil contamination in engineering equipment.