Design and simulation of a MEMS MIM capacitive pressure sensor with high sensitivity in low pressure range

In this paper, the improvement of the sensitivity of a capacitive MEMS pressure sensor is investigated. The proposed spring for the sensor can increase the sensitivity. Silicon is used as the substrate and gold and aluminium nitrate are used as the diaphragm and the dielectric layer, respectively. The dimensions of the diaphragm are 150 µm × 150 µm, which is suspended by four springs. The air gap between the diaphragm and the top electrode is 1.5 µm. The proposed structure is an efficient sensor for the pressures in the range of 1–20 kPa. By using the proposed design, the sensitivity of the MEMS sensor in 18 kPa has improved to 663 (× 10−3 pF/kPa).

Thermal Performance of a Capacitive Comb-Drive MEMS Accelerometer: Measurements vs. Simulation

In this work, we analysed the difference between the measurement and simulation results of thermal drift of a custom designed capacitive MEMS accelerometer. It was manufactured in X-FAB XMB10 technology together with a dedicated readout circuit in X-FAB XP018 technology. It turned out that the temperature sensitivity of the sensor’s output is nonlinear and particularly strong in the negative Celsius temperature range. It was found that the temperature drift is mainly caused by the MEMS sensor and the influence of the readout circuit is minimal. Moreover, the measurements showed that this temperature dependence is the same regardless of applied acceleration. Simulation of the accelerometer’s model allowed us to estimate the contribution of post-manufacturing mismatch on the thermal drift; for our sensor, the mismatch-induced drift accounted for about 6% of total thermal drift. It is argued that the remaining 94% of the drift could be a result of the presence of residual stress in the structure after fabrication.

Factory Oriented Technique for Thermal Drift Compensation in MEMS Capacitive Accelerometers

Capacitive MEMS accelerometers have a high thermal sensitivity that drifts the output when subjected to changes in temperature. To improve their performance in applications with thermal variations, it is necessary to compensate for these effects. These drifts can be compensated using a lightweight algorithm by knowing the characteristic thermal parameters of the accelerometer (Temperature Drift of Bias and Temperature Drift of Scale Factor). These parameters vary in each accelerometer and axis, making an individual calibration necessary. In this work, a simple and fast calibration method that allows the characteristic parameters of the three axes to be obtained simultaneously through a single test is proposed. This method is based on the study of two specific orientations, each at two temperatures. By means of the suitable selection of the orientations and the temperature points, the data obtained can be extrapolated to the entire working range of the accelerometer. Only a mechanical anchor and a heat source are required to perform the calibration. This technique can be scaled to calibrate multiple accelerometers simultaneously. A lightweight algorithm is used to analyze the test data and obtain the compensation parameters. This algorithm stores only the most relevant data, reducing memory and computing power requirements. This allows it to be run in real time on a low-cost microcontroller during testing to obtain compensation parameters immediately. This method is aimed at mass factory calibration, where individual calibration with traditional methods may not be an adequate option. The proposed method has been compared with a traditional calibration using a six-sided orthogonal die and a thermal camera. The average difference between the compensations according to both techniques is 0.32 mg/°C, calculated on an acceleration of 1 G; the maximum deviation being 0.6 mg/°C.