Micromachines

Continuous innovations in welding and additive manufacturing (AM) technologies have introduced challenges related to process stability and uncertainties in ensuring high quality. Given the high complexity and transient nature of these processes, effective online acoustic monitoring is crucial for ensuring manufacturing quality and improving processing efficiency. This paper first elucidates the principles of acoustic signal generation in welding and additive manufacturing. It then provides a comprehensive review of the application of acoustic methods for quality monitoring in these processes, covering both structural acoustic emission (AE) and airborne acoustic monitoring techniques. Finally, it summarizes the current challenges and issues faced by acoustic monitoring technologies in welding and additive manufacturing and outlines potential future development directions.

Gas sensors based on metal oxide semiconductors (MOS) have attracted significant attention in monitoring of methane emission and leakage monitoring due to their high sensitivity, fast response time, simple structure and low cost. However, the high power consumption caused by long-term high-temperature operation of MOS sensors restricts their application in mobile and portable devices. In this study, MOF-derived Co₃O₄ dodecahedrons for low-concentration methane detection at room temperature was prepared using Zeolitic Imidazolate Framework-67 (ZIF-67) as a template and with various calcination temperatures. Among them, the Co₃O₄-350 calcined at 350 °C exhibited the optimal CH₄ sensing performance at room temperature, with a response of R_g/R_a = 1.53 to 2000 ppm CH₄. This enhanced gas sensing performance is attributed to the highest Co³⁺ proportions and the largest specific surface area in Co₃O₄-350 nanomaterials, which provided more active sites for gas adsorption and reaction. To address the challenge of slow response speed and irrecoverability during CH₄ detection at room temperature, the Co₃O₄ nanomaterials were printed onto a micro-heater plate (MHP) to form a MEMS gas sensor. By introducing a pulse heating mode to the MEMS sensor, the response and recovery time were significantly reduced to 26 s and 21 s, respectively. This enhancement improves both the efficiency and reliability of the MEMS gas sensor for early-stage detection of CH₄ leaks in various industrial applications.

Accurate monitoring of intracranial pressure (ICP) is critical for the diagnosis and management of neurological disorders. Although various ICP sensors have been developed, their sensitivity is often limited, restricting their ability to detect subtle pressure variations. Therefore, there is a pressing need to develop ICP sensors with enhanced sensitivity to improve measurement accuracy and patient outcomes. In this paper, a highly sensitive and precise pressure sensor for intracranial pressure (ICP) monitoring was proposed. Theoretically, the beam-membrane-island structure was introduced and optimized to improve sensitivity and linearity compared to a flat membrane structure. The notches etched at beam end were designed for further improving sensitivity. Experimentally, the designed sensor achieved a sensitivity of 1.59 mV/V//kPa and a nonlinearity of −0.22% F.S. Additionally, the sensor can detect pressure with centimeter water column (cm H₂O) resolution, making it suitable for ICP monitoring. This technology holds broad application prospects in the field of medical devices.