This work proposes a design for a direct-reading conductivity sensor with a parallel symmetrical four-electrode structure, which integrates a silicon-based platinum thin-film strip electrode and a serpentine temperature compensation electrode. The optimal structural parameters of the electrode were determined by finite element simulations performed via COMSOL Multiphysics. Next, the designed conductivity sensor chip was fabricated using MEMS technology, and subsequently, the conductivity measurement circuit was designed to test the fabricated sensor’s performance. In laboratory tests, the optimal AC excitation frequency was observed to be 1.067 kHz, while the maximum measurement range was 0–107.41 mS/cm and the measurement precision in low concentration range (0–76.422 mS/cm) was ±0.1 mS/cm. Furthermore, the maximum measurement error of the sensor evaluated using the National Center of Ocean Standards and Metrology was ±0.073 mS/cm. The designed sensor possesses the characteristics of high accuracy, high range, and miniaturization, and enables real-time reading of conductivity value and temperature compensation, which is of great significance for the on-site observation of the physical parameters of marine environment.

In this work, a capacitive pH sensor consisting of Ta₂O₅ functional film is designed and fabricated by employing MEMS-based procedures. The Ta₂O₅ thin film has an amorphous microstructure, and its surface roughness is less than 3.17 nm. A signal processing circuit and a software filtering algorithm are also designed to measure the pH value, thus improving the detection accuracy and anti-interference ability. Good linearity (R² = 0.99904) and sensitivity (63.12 mV/pH) are recorded for the proposed sensing element in the range of pH 2~12. In addition, the sensor’s drift and hysteresis are equal to 5.1 mV and 5.8 mV, respectively. The enhanced sensing performance in combination with the facile miniaturization process, low fabrication cost, and suitability for mass production render the fabricated sensor attractive for applications where pH change measurements in a water environment are required.

Microelectromechanical system (MEMS) pressure sensors have a wide range of applications based on the advantages of mature technology and easy integration. Among them, piezoresistive sensors have attracted great attention with the advantage of simple back-end processing circuits. However, less research has been reported on the performance of piezoresistive pressure sensors in dynamic environments, especially considering the vibrations and shocks frequently encountered during the application of the sensors. To address these issues, this paper proposes a design method for a MEMS piezoresistive pressure sensor, and the fabricated sensor is evaluated in a series of systematic dynamic environmental adaptability tests. After testing, the output sensitivity of the sensor chip was 9.21 mV∙bar⁻¹, while the nonlinearity was 0.069% FSS. The sensor overreacts to rapidly changing pressure environments and can withstand acceleration shocks of up to 20× g. In addition, the sensor is capable of providing normal output over the vibration frequency range of 0–5000 Hz with a temperature coefficient sensitivity of −0.30% FSS °C⁻¹ over the temperature range of 0–80 °C. Our proposed sensor can play a key role in applications with wide pressure ranges, high-frequency vibrations, and high acceleration shocks, as well as guide MEMS-based pressure sensors in high pressure ranges and complex environmental adaptability in their design.

Pressure measurement is of great importance due to its wide range of applications in many fields. AT-cut quartz, with its exceptional precision and durability, stands out as an excellent pressure transducer due to its superior accuracy and stable performance over time. However, its intrinsic temperature dependence significantly hinders its potential application in varying temperature environments. Herein, three different learning algorithms (i.e., multivariate polynomial regression, multilayer perceptron networks, and support vector regression) are elaborated in detail and applied to establish the prediction models for compensating the temperature effect of the resonant pressure sensor, respectively. The AC-cut quartz, which is sensitive to temperature variations, is paired with the AT-cut quartz, providing the essential temperature information. The output frequencies derived from the AT-cut and AC-cut quartzes are selected as input data for these learning algorithms. Through experimental validation, all three methods are effective, and a remarkable improvement in accuracy can be achieved. Among the three methods, the MPR model has exceptionally high accuracy in predicting pressure. The calculated residual error over the temperature range of −10–40 °C is less than 0.008% of 40 MPa full scale (FS). An intelligent automatic compensation and real-time processing system for the resonant pressure sensor is developed as well, which may contribute to improving the efficiency in online calibration and large-scale industrialization. This paper paves a promising way for the temperature compensation of resonant pressure sensors.

This study presents the design and fabrication of an ultra-high-precision platinum thin-film temperature sensor without an adhesion layer, which effectively eliminates the performance degradation caused by adhesion layer diffusion during high-temperature annealing. A 1 μm thick platinum film was deposited on an alumina substrate via segmented magnetron sputtering, followed by annealing in air at temperatures ranging from 500 °C to 900 °C. The resistance-temperature relationships of the sensor were characterized over the 0 °C to 35 °C range under various annealing conditions, with a particular focus on the temperature coefficient of resistance (TCR). Morphological and grain size analyses of the platinum film were conducted using X-ray diffraction and scanning electron microscopy. Results indicate that optimal sensor performance was achieved with an annealing temperature of 800 °C for 2 hours, which leads to an increase in the TCR from 2.36×10⁻³/°C to 3. 65×10⁻³/°C. Precision calibration and stability tests show that the sensor achieved an excellent measurement accuracy of 0.0019 °C and a maximum temperature drift of only 0.0009 °C per month over a six-month period. These results indicate that the platinum thin-film sensor exhibits outstanding performance, making it particularly suitable for high-precision ocean temperature measurement applications.

Packaged temperature sensors exhibit significant thermal hysteresis effects, which directly impact their dynamic performance and accuracy during rapid temperature variations in marine environments. This paper focuses on platinum resistance thermometers (PRTs), which are commonly used in oceanic applications, and a dynamic testing method was proposed that employs temperature step excitation within a fully liquid environment, along with a full range dynamic error compensation approach based on the fireworks algorithm. Initially, a dynamic testing system was developed, and its testing repeatability was verified. Subsequently, a sample database for PRTs at various temperature steps was created. By optimizing the fitness function, the fireworks algorithm was utilized on sample database during the iterative process to design a dynamic error compensation filter. The resulting compensation filter demonstrated enhanced universality across various temperature step sizes within the sensor measurement range. Through the filter’s compensation, the rise time of the packaged PRT was reduced from an average of 477 ms to 121 ms within the measurement range. Furthermore, the dynamic response characteristics of the packaged PRT closely resembled those of the bare PRT. The dynamic testing method, which simulates heat transfer in real-world scenarios, in conjunction with the dynamic compensation method introduced in this paper, can also be employed to achieve dynamic compensation for sensors operating under diverse testing principles.