Microelectromechanical Systems Pressure Sensor Research Articles

Floor level estimation using MEMS pressure sensors

Enhanced 911 systems aim to increase the efficiency of first responders by automatically locating the origin of a 911 call even if the caller is unable to provide it. However, in a high-rise building, the location of a cell phone call would appear the same to dispatchers regardless of elevation. If emergency services had more accurate location information, they could save countless more lives. In this study, we compared multiple methods for determining a caller’s floor level inside a building, including GPS, WiFi, a magnetic sensor, and a micro-electromechanical system (MEMS) pressure sensor. GPS provided a reasonable estimate of vertical height, but accuracy was strongly dependent on the reception, which was often poor inside the building. WiFi signals and magnetic fields were not strong predictors of vertical height. WiFi was limited by short signal range, need for network access, and knowledge of router locations. Magnetic sensor readings required a pre-existing magnetic field contour map of the building in order to interpret the data. The MEMS pressure sensor was the most accurate predictor of elevation and does not rely on communication with other equipment. A detection accuracy of ±1 floor can be achieved using the MEMS pressure sensor after correcting the output using publicly available data and assuming an average floor height. The proposed technique provides a self-contained solution, using a sensor available in most smartphones, to determine the floor of a caller. Adding floor level data to emergency call locations would provide valuable information to first responders in densely populated urban areas.

Research on a capacitive MEMS pressure sensor based on through glass via

AbstractThe paper reports the fabrication and characterization of a capacitive Microelectro Mechanical Systems pressure sensor based on through glass vias (TGV), which had a large dynamic range by operating in touch mode. The substrate with TGV offers the advantage of elimination of parasitic capacitances owing to the superior insulation property of glass. The fabrication process was introduced. In particular, anodic bonding was applied in high vacuum to realize the hermetic package to obtain large operating range and high sensitivity. The performance of the sensor with a sensitive diaphragm of 700 μm × 1400 μm was characterized in the pressure range from −80 to 180 kPa. The sensitivity was determined as 0.072 pF/kPa over the range of 160 kPa with a good linearity of 97%.

Development of IOT-based low-cost MEMS pressure sensor for groundwater level monitoring

Groundwater level monitoring is critical to the protection and management of groundwater resources. Properly designed and executed instrumentation can play an important role in increasing the quality and reliability of collected data and reducing total monitoring costs. The efficiency of the instrumentation depends mainly on the accuracy and reliability of the installed sensors. This study presents the testing and application of a cost-effective pressure sensor (0–689 kPa range) for water level monitoring based on microelectromechanical system (MEMS) technology and the internet of things concept. The sensor performance, in terms of accuracy, precision, repeatability, and temperature, was investigated in laboratory columns (with constant water level, increasing and decreasing water levels at various rates) and in situ conditions in an observation bore (with natural groundwater level fluctuations). The results show that the MEMS sensor is capable of providing a reliable and adequate monitoring scheme with an accuracy of 0.31% full scale (FS) (2.13 kPa).

Wearable Multi-Channel Pulse Signal Acquisition System Based on Flexible MEMS Sensor Arrays with TSV Structure.

Micro-electro-mechanical system (MEMS) pressure sensors play a significant role in pulse wave acquisition. However, existing MEMS pulse pressure sensors bound with a flexible substrate by gold wire are vulnerable to crush fractures, leading to sensor failure. Additionally, establishing an effective mapping between the array sensor signal and pulse width remains a challenge. To solve the above problems, we propose a 24-channel pulse signal acquisition system based on a novel MEMS pressure sensor with a through-silicon-via (TSV) structure, which connects directly to a flexible substrate without gold wire bonding. Firstly, based on the MEMS sensor, we designed a 24-channel pressure sensor flexible array to collect the pulse waves and static pressure. Secondly, we developed a customized pulse preprocessing chip to process the signals. Finally, we built an algorithm to reconstruct the three-dimensional pulse wave from the array signal and calculate the pulse width. The experiments verify the high sensitivity and effectiveness of the sensor array. In particular, the measurement results of pulse width are highly positively correlated with those obtained via infrared images. The small-size sensor and custom-designed acquisition chip meet the needs of wearability and portability, meaning that it has significant research value and commercial prospects.

Exploring the nonlinear piezoresistive effect of 4H-SiC and developing MEMS pressure sensors for extreme environments

Microelectromechanical system (MEMS) pressure sensors based on silicon are widely used and offer the benefits of miniaturization and high precision. However, they cannot easily withstand high temperatures exceeding 150 °C because of intrinsic material limits. Herein, we proposed and executed a systematic and full-process study of SiC-based MEMS pressure sensors that operate stably from −50 to 300 °C. First, to explore the nonlinear piezoresistive effect, the temperature coefficient of resistance (TCR) values of 4H-SiC piezoresistors were obtained from −50 to 500 °C. A conductivity variation model based on scattering theory was established to reveal the nonlinear variation mechanism. Then, a piezoresistive pressure sensor based on 4H-SiC was designed and fabricated. The sensor shows good output sensitivity (3.38 mV/V/MPa), accuracy (0.56% FS) and low temperature coefficient of sensitivity (TCS) (−0.067% FS/°C) in the range of −50 to 300 °C. In addition, the survivability of the sensor chip in extreme environments was demonstrated by its anti-corrosion capability in H2SO4 and NaOH solutions and its radiation tolerance under 5 W X-rays. Accordingly, the sensor developed in this work has high potential to measure pressure in high-temperature and extreme environments such as are faced in geothermal energy extraction, deep well drilling, aeroengines and gas turbines.

Numerical Simulation of a Striated Piezoresistive MEMS Pressure Sensor on Circular Silicon Diaphragm: A Finite Element Method-Based Study

Micro-Electro-Mechanical Systems (MEMS) technology has been heavily incorporated into fabrication of sensors due to its undoubtful advantages such as efficient form-factor, low-power consumption and less bulk manufacturing cost. One of the first sensors to undergo transformation in the micro-scale has been the pressure sensor. Pressure sensors are used excessively in various fields such as automobile, aerospace, aviation, biomedical, consumer electronics, etc. Various researches are being conducted to optimize the design of MEMS-based pressure sensors to meet the specific requirements of different fields. This work presents a piezoresistive pressure sensor design with striated-shaped piezoresistors instead of the conventional bar-shaped piezoresistors. Such a configuration allows positioning the short arms of the striated design effectively on the narrow high stress regions. The piezoresistors are embedded on a circular diaphragm. The performance advantage of such a design is validated through analytical models and numerical simulations. Finite Element Analysis (FEA) is deployed using COMSOL Multiphysics software to achieve precise simulation results. The results are then compared to the existing literature. The proposed design achieves a sensitivity of 40.365 mV/V/MPa under a pressure range of 0–1 MPa. The proposed design performs better than existing literature and can be used in applications that require high sensitivity over a long pressure range, for example, in barometric altimeters.

An Artificial Neural Network Method for High-Accurate and High-Efficient MEMS Pressure Sensor Design

Microelectromechanical system (MEMS) devices have numerous advantages including small sizes, high performance, and easy integration capability and thus have been widely used in the Internet of Things (IoT). A typical MEMS device usually includes a set of performance parameters, and each parameter is sensitive to the device geometries but with different regularities and weights, thus resulting in the complexity of MEMS device design. The conventional design method is mainly based on iterative finite-element (FE) simulation and optimization, which is time-consuming and inefficient. To address the above issues, a bidirectional artificial neural network (ANN)-based method is explored and used as the design method by using an MEMS pressure sensor as a design example. First, a forward ANN with the geometries and performance as the input and output, respectively, is trained and constructed, which can accurately predict the performance. Then, an inverse ANN with the performance and geometries as the input and output, respectively, is also investigated. By means of a tandem network, the nonuniqueness issue of the inverse ANN caused by a one-to-many response from the input to the output can be well addressed. This tandem network can output the corresponding geometries instantly according to the target performance. This work demonstrates the great potential of the ANN as a new and facile strategy in MEMS device design.

Improving the Sensing Properties of Graphene MEMS Pressure Sensor by Low-Temperature Annealing in Atmosphere.

The high demand for pressure devices with miniaturization and a wide bearing range has encouraged researchers to explore new high-performance sensors from different approaches. In this study, a sensitive element based on graphene in-plane compression properties for realizing pressure sensing is experimentally prepared using microelectromechanical systems (MEMS) fabrication technology; it consists of a 50 µm thick, 1400 µm wide square multilayer component membrane and a graphene monolayer with a meander pattern. The prepared sample is extensively characterized and analyzed by using various techniques, including atomic force microscopy, Raman spectroscopy, infrared spectroscopy, X-ray photoelectron spectroscopy, COMSOL finite element method, and density functional theory. The sensing performance of the new pressure sensor based on the sensitive element are obtained by theoretical analysis for electromechanical measurements of the sensitive element before and after low-temperature annealing in atmosphere. Results demonstrate that atmospheric annealing at 300 °C enhances the pressure sensing sensitivity by 4 times compared to pristine graphene without annealing, which benefits from the desorption of hydroxyl groups on the graphene surface during annealing. The sensitivity is comparable and even better than that of previous sensors based on graphene in-plane properties. Our results provide new insights into realizing high-performance MEMS devices based on 2D sensitive materials.

Thermal fatigue analysis of gold wire bonding solder joints in MEMS pressure sensors by thermal cycling tests

Thermal fatigue is one of the main causes of device failure in micro-electro-mechanical systems (MEMS). Gold wire bonding plays the role of electrical connection and signal transmission, which is the key structure of MEMS pressure sensor. In this paper, the fatigue failure of gold wire bonding solder joints caused by the thermal cycling test was studied. The thermal cycling test on MEMS pressure sensor was conducted using a temperature chamber with the cycling temperature range from −40 °C to 150 °C. After 1600 cycles, the solder joints were found with significant resistance increase to about 25 Ω or even overrange value by electrical measurement. In addition, the computed tomography (CT) scanning results showed that the solder joints on the substrate underwent thermal fatigue failure and one joint was separated from the pad with a distance of 36 μm, while the solder joints on the chip were still in good bonding conditions. The mechanism of thermal fatigue failure can be summarized as the thermal mismatch of solder joint materials, residual stress due to the bonding process, and stress concentration caused by the wedge area.

A Novel High-Sensitivity MEMS Pressure Sensor for Rock Mass Stress Sensing.

This paper proposes a novel high-sensitivity micro-electromechanical system (MEMS) piezoresistive pressure sensor that can be used for rock mass stress monitoring. The entire sensor consists of a cross, dual-cavity, and all-silicon bulk-type (CCSB) structure. Firstly, the theoretical analysis is carried out, and the relationship between the structural parameters of the sensor and the stress is analyzed by finite element simulation and curve-fitting prediction, and then the optimal structural parameters are also analyzed. The simulation results indicate that the sensor with the CCSB structure proposed in this article obtained a high sensitivity of 87.74 μV/V/MPA and a low nonlinearity error of 0.28% full-scale span (FSS) within the pressure range of 0–200 MPa. Compared with All-Si Bulk, grooved All-Si Bulk, Si-Glass Bulk, silicon diaphragm, resistance strain gauge, and Fiber Bragg grating structure pressure sensors, the designed sensor has a significant improvement in sensitivity and nonlinearity error. It can be used as a new sensor for rock disaster (such as collapse) monitoring and forecasting.

High-Performing Polycrystalline MoS2-Based Microelectromechanical Piezoresistive Pressure Sensor

The research toward high-performing pressure sensors has been going on for more than two decades, with the goal of improving key parameters, namely the high gauge factor (GF) and device stability for future applications. In the present work, the piezoresistivity of the polycrystalline molybdenum disulfide (MoS2) is harnessed for pressure sensing applications with very low noise levels. The fabricated microelectromechanical systems (MEMS) pressure sensor exhibits a high GF of ~92 with pressure sensitivity of ~ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.46 \mu \text{A}$ </tex-math></inline-formula> /Pa and a low nonlinearity of ~12% in the applied pressure range 0–20 kPa. This exceptional performance is explained based on fluctuation-induced tunneling in the polycrystalline MoS2-based pressure sensor. The tunneling barrier between two grains gets modified with the application of external pressure. Furthermore, the noise analysis of the fabricated MEMS pressure sensor shows that the noise level gets altered with the applied stress due to the modified barrier potential.

Digital twin-driven intelligent production line for automotive MEMS pressure sensors

The equipment and technological processes used in manufacturing electronic products are gradually being automated and networked. Currently, digital twin technology continues to evolve and mature. The electronics manufacturing industry is undergoing an intelligent and digital transformation. Micro-electro-mechanical system (MEMS) sensors have been widely used in the automotive field due to their small size, low cost, and high reliability. In this study, a new intelligent production line for automotive MEMS pressure sensors driven by digital twin is individually designed. The intelligent production line system consists of physical production lines, digital production lines, twin data, and data service systems. The technology of multi-source heterogeneous data acquisition is used to process and analyze data collected in real time in a physical production line. Based on the technology of parallel control, the physical and digital production lines are synchronized. To obtain optimal process parameters, a process database is established through the analysis of the key processes of the production line. Three types of automotive MEMS pressure sensors are successfully manufactured in the constructed digital twin-driven intelligent production line. The intelligent production line can realize 24-h unattended operation. The product yield is above 98 %, and the takt time is less than 16 s.

A Novel Defect Inspection System Using Convolutional Neural Network for MEMS Pressure Sensors.

Defect inspection using imaging-processing techniques, which detects and classifies manufacturing defects, plays a significant role in the quality control of microelectromechanical systems (MEMS) sensors in the semiconductor industry. However, high-precision classification and location are still challenging because the defect images that can be obtained are small and the scale of the different defects on the picture of the defect is different. Therefore, a simple, flexible, and efficient convolutional neural network (CNN) called accurate-detection CNN (ADCNN) to inspect MEMS pressure-sensor-chip packaging is proposed in this paper. The ADCNN is based on the faster region-based CNN, which improved the performance of the network by adding random-data augmentation and defect classifiers. Specifically, the ADCNN achieved a mean average precision of 92.39% and the defect classifier achieved a mean accuracy of 97.2%.

Design, development and testing of digital MEMS pressure sensor array for full-scale vibroacoustic measurements

This manuscript addresses design, development, and application of micro-electro-mechanical systems (MEMS) based digital pressure sensor array for vibroacoustic measurements. These vibroacoustic measurements were conducted on a A320 type single aisle aircraft demonstrator subjected to broadband as well as tonal excitations. Cabin noise levels were measured with both condenser microphones as well as digital MEMS pressure sensor array. The measured cabin noise shows strong qualitative as well as quantitative agreement between both type of measurement devises for full scale cabin noise measurements inside an aircraft demonstrator. The observed strong agreement is valid for both single wall (fuselage with thermal insulation) and double wall (fuselage with thermal insulation and trim panel) cabin noise measurements. Such strong agreement within 1.0 dB tolerance is significantly motivating for further development of reliable but low-cost MEMS based measurement devises and corresponding efficient data post-processing algorithms for full scale vibroacoustic measurements in general. Additionally, it is also demonstrated that the large number of MEMS based digital pressure sensors can be used in areas where the physical space constraints are high. This demonstration shows strong potential to derive additional vibroacoustic indicator for the development and the testing of future noise control solutions in a non-traditional way.

A Simulation Approach to Study the Effect of SiC Polytypism Factor on Sensitivity of Piezoresistive MEMS Pressure Sensor

SiC is a well known wide band gap semiconductor explored for realizing the piezoresistive micro-electro-mechanical systems (MEMS) pressure sensors for harsh environments. In this work a thin SiC diaphragm based piezoresistive pressure sensor was designed by locating the resistors of different SiC polytypes such as 3C, 4H, and 6H-SiC, on highly stressed zone of the diaphragm and analyzed. The sensor design parameters were extensively studied by executing the finite element method (FEM) and piezoresistive simulation using device simulation software. The sensor characteristics were measured for different SiC polytypes and compared for different design parameter variations to obtain the optimum sensor performance under the influence of the pressure upto 8 MPa. Influence of temperature for heavily doped SiC polytypes is also studied. The simulation results shows that the pressure sensor with 3C-SiC polytype offers higher sensitivity 7.3 μV/V/KPa as compared to 4H-SiC and 6H-SiC polytypes.

The design and simulation of a MOSFET-based MEMS pressure sensor using an integrated simulation approach

A novel integrated design and simulation approach is applied to analyze the performance of a metal–oxide–semiconductor field-effect transistor (MOSFET)-based microelectromechanical systems (MEMS) pressure sensor circuit while varying circuit and CMOS parameters, viz. the supply voltage and threshold voltage (Vt), respectively. For effective mechanical pressure sensing, a sensor MOSFET is integrated near the fixed edge of a deformable silicon diaphragm for maximum stress exposure. The stress value where the sensor MOSFET is located on the diaphragm surface is calculated using the finite-element method (FEM). Additionally, the threshold voltage required to activate the sensor MOSFET is also extracted using the FEM. The extracted value of Vt along with the corresponding gate oxide thickness are used to design and simulate the sensor circuit in the SPICE tool. The FEM-based multiphysics simulation is linked to a standard direct-current (DC) model SPICE simulation using our proposed carrier mobility model for a MOSFET under mechanical stress. All the FEM computations are performed using COMSOL Multiphysics, all the electrical simulations are performed using LT-SPICE, and the full sensor circuit is designed and simulated by integrating COMSOL Multiphysics and LT-SPICE via a MATLAB script. The validity of the design is confirmed by comparing these results with analytical computations. The results obtained using the integrated simulation approach confirm that the design is reliable and enable the sensor performance to be examined in terms of its sensitivity, yielding a value of 30 mV/MPa.

Investigation of Potting-Adhesive-Induced Thermal Stress in MEMS Pressure Sensor

Thermal stress is one of the main sources of micro-electro-mechanical systems (MEMS) devices error. The Wheatstone bridge is the sensing structure of a typical piezoresistive MEMS pressure sensor. In this study, the thermal stress induced by potting adhesive in MEMS pressure sensor was investigated by experiments, calculated by analytics and analyzed by simulations. An experiment system was used to test the sensor at different air pressures and temperatures. The error becomes greater with the decrease in pressure. A set of novel formulas were proposed to calculate the stress–strain on Wheatstone bridge. The error increases with the temperature deviating from 25 °C. A full-scale geometric model was developed, and finite element simulations were performed, to analyze the effect of the stress on MEMS pressure sensor induced by different temperatures and thicknesses of potting adhesive. Simulation results agree well with the experiments, which indicated that there is a 3.48% to 6.50% output error in 0.35 mm potting adhesive at 150 °C. With the thickness of potting adhesive increasing, the variations of output error of the Wheatstone bridge present an N-shaped curve. The output error meets a maximum of 5.30% in the potting adhesive of 0.95 mm and can be reduced to 2.47%, by increasing the potting adhesive to 2.40 mm.

Using non-invasive MEMS pressure sensors for measuring building envelope air leakage

Micro-electromechanical systems (MEMS)-based sensors have seen significant improvements in accuracy and cost over the past several years, and due to the need for altitude sensing in unmanned aerial vehicles and wearable technologies, absolute pressure sensors have shown the most dramatic improvements. This paper investigates applications of MEMS sensors in commercial buildings, including pairing two absolute pressure sensors to determine differential pressures between different locations in and around buildings. Differential pressure measurements are commonly made in commercial buildings for a number of applications, including static pressure measurements for variable-speed supply fan control, air balancing in hospitals, and for envelope and duct air leakage testing. This paper focuses specifically on envelope air-leakage testing applications of these sensors. The use of continuous pressure measurements in addition to one-time non-intrusive outdoor airflow measurements of rooftop packaged units is investigated. A comparison with standardized leakage testing indicated that continuous measurements with MEMS pressure-sensors were able to estimate envelope leakage to within 3–16% of the standardized test result. In addition, the magnitude and stability of differential pressure differences that can be resolved with absolute pressure sensors are also investigated in the laboratory and the field. Results show that the sensors can be effectively used for pressures seen in low rise buildings with rooftop units.

A Semi-Analytical and Computationally Efficient Method to Calculate the Touch-Point Pressure and Pull-In Voltage of a MEMS Pressure Sensor With a Circular Diaphragm

Micro-Electromechanical Systems (MEMS) based capacitive pressure transducers have a pivotal role in transducer devices for real-world applications. Thus, the efficient analysis for modelling these transducers is increasingly becoming important. These transducers use diaphragms of various geometries, however for the same active area, circular diaphragms are more sensitive as compared to square diaphragms. Pull-in voltage and touch-point pressure are two parameters which determine the performance of a micro- electromechanical systems device. In this work a complete analysis is presented for evaluating these parameters along with the mechanical and capacitive sensitivity for a circular diaphragm based capacitive pressure transducer. The effect of thickness and radius of the diaphragm has been illustrated, as they form the essential design parameters for fabricating the micro-electromechanical systems devices. Literature review suggests that relatively less work has been reported for this analysis and more complicated and computationally complex methods have been used. The semi-analytical approach presented in this research is less complex and computationally efficient, in comparison to finite element method (FEM). Critical differentiator of this formulation is related to its applicability for analysing sensor parameters with or without considering the effect of electrostatic pressure on diaphragm deflection. Furthermore, this analysis eliminates the need for determining spring constant k which is used in lumped element methods. MATLAB has been used to compute and simulate the results. The mathematical model developed is verified with a standard Finite Element Analysis (FEM) using COMSOL v5.5.

Long-term Stability Enabling Technology of Silicon-Based Piezoresistive MEMS Pressure Sensor

Silicon-based piezoresistive microelectromechanical systems (MEMS) pressure sensor is one of the best studied and commercialized devices among all MEMS devices due to simple structure, easy reading circuit, strong batch fabrication capability and low price. The biggest technical bottleneck of this sensor for high-end applications such as aerospace is long-term stability after packaging. Therefore, long-term stability improvement technologies, as the common key technologies, have been widely concerned by academia and industry. In this paper, three common enabling technologies including pulsating fatigue, thermal-cold cycling and vibration aging are adopted to evaluate the effect of long-term stability of silicon-based piezoresistive MEMS pressure sensors by using control variable method and orthogonal test (OT) method. The comparative test results indicate that all these three technologies can improve the long-term stability of the pressure sensor. In addition, an optimized combination of environmental stress parameters is found to improve the stability more than 90% higher than before the test. The long-term stability of the sensors through the optimal parameter combination aging method is better than the original factory method. The research results can be used for reference to improve the long-term stability of various silicon-based pressure sensors.