Capacitive MEMS Research Articles

Modeling and analysis of a capacitive MEMS with a microstructured gap subjected to a mechanical shock

Modeling and analysis of a capacitive MEMS with a microstructured gap subjected to a mechanical shock

Performance analysis of FEM simulated different shaped membranes based capacitive MEMS sensor

Performance analysis of FEM simulated different shaped membranes based capacitive MEMS sensor

Evaluation of the Diagnostic Sensitivity of Digital Vibration Sensors Based on Capacitive MEMS Accelerometers.

In recent years, there has been an increasing use of digital vibration sensors that are based on capacitive MEMS accelerometers for machine vibration monitoring and diagnostics. These sensors simplify the design of monitoring and diagnostic systems, thus reducing implementation costs. However, it is important to understand how effective these digital sensors are in detecting rolling bearing faults. This article describes a method for determining the diagnostic sensitivity of diagnostic parameters provided by commercially available vibration sensors based on MEMS accelerometers. Experimental tests were conducted in laboratory conditions, during which vibrations from 11 healthy and faulty rolling bearings were measured using two commercial vibration sensors based on MEMS accelerometers and a piezoelectric accelerometer as a reference sensor. The results showed that the diagnostic sensitivity of the parameters depends on the upper-frequency band limit of the sensors, and the parameters most sensitive to the typical fatigue faults of rolling bearings are the peak and peak-to-peak amplitudes of vibration acceleration. Despite having a lower upper-frequency range compared to the piezoelectric accelerometer, the commercial vibration sensors were found to be sensitive to rolling bearing faults and can be successfully used in continuous monitoring and diagnostics systems for machines.

The Effect of Compliant Backplate on Capacitive MEMS Microphones

The Effect of Compliant Backplate on Capacitive MEMS Microphones

Design and performance analysis of a MEMS Based Area-Variation Capacitive Accelerometer with Readout Circuit

The structural optimization of the device is used in the present work to demonstrate the improvement of the device sensitivity for a MEMS accelerometer based on capacitive principle due to overlap area change between electrodes. The proof mass of the device is made up of a few parallel fingers those are joined together. Proof mass is supported by flexible mechanical beams that resemble springs is suspended over fixed electrodes and are fastened to the substrate. The greatest displacement that the proof mass can suffer with application of acceleration is determined for the specific construction. The connected beams' width and length were changed, and ANSYS FEA software was used to model the reaction. Sensitivity of the device is analyzed and discussed based on the findings of various device geometry measurements, and suggestions for improving sensitivity are also made. Additionally, a signal conditioning circuit that changes the capacitance to voltage as a result of the proof mass deflecting differently is described. These discoveries might help designers to create capacitive MEMS accelerometers with increased sensitivity.

Effects of the Temperature-Dependent Behavior of the Gap-Filling PDMS on the Response of a Capacitive MEMS to the Electrostatic Actuation

In recent years, researchers have shown interest in using elastomers with high dielectric constant and good elasticity in capacitive MEMS. This paper aims to investigate how the performance of capacitive sensors/actuators is affected by the temperature-dependent behavior of gap-filling Polydimethylsiloxane (PDMS). As a case study, a model is created, consisting of a proof mass with two attached flexible microbeams parallel to a stationary electrode, under electrostatic actuation. The actuation is directly proportional to the temperature-dependent dielectric constant. To reduce resistance stiffness, the bulk PDMS was assumed to have porosity, resulting in a nonlinear displacement-dependent Young’s modulus. The system’s static and dynamic responses were obtained by solving the governing nonlinear equations using Galerkin-based numerical procedures. Additionally, a physically gradient-descent-based learning method was used to predict the nonlinear frequency response of the system. The results have shown that using PDMS instead of an air gap significantly reduces the required actuation voltage, although this difference is less pronounced at higher temperatures. In addition, the inclusion of PDMS alters the resonance behavior of the system and also reducing the temperature diminishes the nonlinear softening behavior of the system under specific bias and AC voltages.

A Novel Temperature Drift Error Estimation Model for Capacitive MEMS Gyros Using Thermal Stress Deformation Analysis.

Because the conventional Temperature Drift Error (TDE) estimation model for Capacitive MEMS Gyros (CMGs) has inadequate Temperature Correlated Quantities (TCQs) and inaccurate parameter identification to improve their bias stability, its novel model based on thermal stress deformation analysis is presented. Firstly, the TDE of the CMG is traced precisely by analyzing its structural deformation under thermal stress, and more key decisive TCQs are explored, including ambient temperature variation ∆T and its square ∆T2, as well its square root ∆T1/2; then, a novel TDE estimation model is established. Secondly, a Radial Basis Function Neural Network (RBFNN) is applied to identify its parameter accurately, which eliminates local optimums of the conventional model based on a Back-Propagation Neural Network (BPNN) to improve bias stability. By analyzing heat conduction between CMGs and the thermal chamber with heat flux analysis, proper temperature control intervals and reasonable temperature control periods are obtained to form a TDE precise test method to avoid time-consuming and expensive experiments. The novel model is implemented with an adequate TCQ and RBFNN, and the Mean Square Deviation (MSD) is introduced to evaluate its performance. Finally, the conventional model and novel model are compared with bias stability. Compared with the conventional model, the novel one improves CMG's bias stability by 15% evenly. It estimates TDE more precisely to decouple Si-based materials' temperature dependence effectively, and CMG's environmental adaptability is enhanced to widen its application under complex conditions.

Nonlinear Behavioral Model of Capacitive MEMS Microphone for Predicting Ultrasound Intermodulation Distortion

Nonlinear Behavioral Model of Capacitive MEMS Microphone for Predicting Ultrasound Intermodulation Distortion

MEMS capacitive accelerometer: A review

Micro-electro-mechanical systems sensors are integrated systems used in many fields such as consumer electronics, the automobile industry, and biomedical, and their dimensions change between micrometers and millimeters. MEMS capacitive accelerometers are the most widely used sensor type among MEMS accelerometer sensors. As a result of the external force applied to the capacitive accelerometer sensor, the proof mass inside the sensor moves, and the capacitive change is measured as an electrical signal using reading circuits. In this review paper, general information about MEMS sensors is given, and a comprehensive review is made of MEMS capacitive accelerometers. In the study, the dynamic circuit of the MEMS capacitive accelerometer is given, and the calculation of the important values for the mechanical and electronic structure during the design of the capacitive MEMS accelerometer is explained. In addition, information about the readout circuits used to convert the capacitive change to voltage is given. Finally, the fabrication processes used to produce the final product are explained, and the studies on sample fabrication processes found in the literature are mentioned.

Analysis of the Frequency-Dependent Vibration Rectification Error in Area-Variation-Based Capacitive MEMS Accelerometers.

The presence of strong ambient vibrations could have a negative impact on applications such as high precision inertial navigation and tilt measurement due to the vibration rectification error (VRE) of the accelerometer. In this paper, we investigate the origins of the VRE using a self-developed MEMS accelerometer equipped with an area-variation-based capacitive displacement transducer. Our findings indicate that the second-order nonlinearity coefficient is dependent on the frequency but the VRE remains constant when the displacement amplitude of the excitation is maintained at a constant level. This frequency dependence of nonlinearity is a result of several factors coupling with each other during signal conversion from acceleration to electrical output signal. These factors include the amplification of the proof mass's amplitude as the excitation frequency approaches resonance, the nonlinearity in capacitance-displacement conversion at larger displacements caused by the fringing effect, and the offset of the mechanical suspension's equilibrium point from the null position of the differential capacitance electrodes. Through displacement transducer and damping optimization, the second-order nonlinearity coefficient is greatly reduced from mg/g2 to μg/g2.

Tasarım optimizasyonu ile geliştirilmiş MEMS mikrofon frekans yanıtı

Microphone main characteristic is to faithfully detect and transform incoming acoustic signal in electric one. Semiconductor based capacitive MEMS microphones, despite their limited dimensions, offer remarkable performances (frequency response, SNR). The purpose of this article is to introduce some design optimizations in the current SDM (Sealed-Dual-Membrane) capacitive MEMS microphone mainly concerning the position of the ventilation hole. The effects of the suggested modifications on the microphone’s performances were evaluated using Lumped Model simulation tool. A clear improvement in the device frequency response within audio-band was obtained even if a less significant improvement in the general performances of microphone (SNR) was achieved.

A novel design of capacitive MEMS multi-range accelerometer; FEM and numerical approach

Sensing the acceleration with high dynamic range follows space and size limitations and many errors and inconveniences caused by using multiple accelerometers on a single structure. A novel MEMS capacitive accelerometer with a dual-spring system has been proposed to address this issue. Such a design is a single device with two sensitivities in different sensing ranges. It increases the dynamic range of the sensing by incorporating the supporting springs at high accelerations. Therefore, the sensor can sense a more comprehensive dynamic range while maintaining the required resolution in different ranges. The design parameters of the sensor, such as the thickness of the structural layer, the size of the sensor, and the width of the spring beams, have been investigated. The mechanical sensitivity in the first range is 0.082 μm g−1. For the second range, it is 0.0015 to 0.0091 μm g−1 depending on the supportive springs’ width. Moreover, the natural frequency of the device is 1740 Hz. The capacitance change of the proposed sensor is 7 fF g−1 on average for the first range and 0.08 to 0. 48 fF g−1 for different configurations in the second range. Utilizing such sensors with changeable stiffness in different ranges can reduce the sensor footprint and fabrication cost and increase reliability.

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%.

A study of field emission current in MEMS capacitors with bottom electrode covered by dielectric film

The potential distribution in a MEMS capacitor with a thin dielectric film on the bottom electrode and under the presence of field emission leakage current is presented for the first time. The paper also demonstrated the build-up of dielectric charging during this process. The investigation is based on obtaining current-voltage characteristics in clockwise and counter clockwise loops and analyzing the transport mechanisms in MIM capacitors. Same procedure is applied to monitor the dielectric charging build-up during field emission in MEMS capacitors. The data of pristine current-voltage characteristics in both MIM and MEMS are used to determine the Voltage drops across the dielectric film and the gap as well as their dependence on the flowing current.

Enhancing heart disease diagnosis through precise heart sound including infrasound

Recent research has been pushing the frontier of diagnosing cardiovascular diseases, which have a high mortality rate globally. The need for swift responses to acute diseases has underscored the importance of continuous health monitoring and the development of monitoring diagnostic technology. Our work focused on an overlooked aspect—the microphones used to measure heart sounds. Existing ones, particularly capacitive MEMS types, measure only heart sounds primarily within the audible frequency range, potentially limiting the diagnostic accuracy. To overcome these limitations, we used microphones capable of measuring down to infrasound areas. We also designed an experimental environment to capture the precise heart sounds. The crux of our approach was using the full information of heart sounds through infrasound measurements. A convolutional neural network-based deep learning model was employed for algorithm development and validated using the PhysioNet 2016 CinC’s open-source heart sound data. We conducted an experiment on the impact of low-frequency components on heart sound diagnosis using a new infrasound dataset measured at Seoul St. Mary's Hospital of the Catholic University of Korea. Accuracy and sensitivity, respectively, improved on average by 2% and 4%, showing that datasets including low-frequency components generally performed better.

The High-Efficiency Design Method for Capacitive MEMS Accelerometer.

In this research, a high-efficiency design method of the capacitive MEMS accelerometer is proposed. As the MEMS accelerometer has high precision and a compact structure, much research has been carried out, which mainly focused on the structural design and materials selection. To overcome the inconvenience and inaccuracy of the traditional design method, an orthogonal design and the particle swarm optimization (PSO) algorithm are introduced to improve the design efficiency. The whole process includes a finite element method (FEM) simulation, high-efficiency design, and verification. Through the theoretical analysis, the working mechanism of capacitive MEMS accelerometer is clear. Based on the comparison among the sweep calculation results of these parameters in the FEM software, four representative structural parameters are selected for further study, and they are le, nf, lf and wPM, respectively. le and lf are the length of the sensing electrode and fixed electrode on the right. nf is the number of electrode pairs, and wPM is the width of the mass block. Then, in order to reduce computation, an orthogonal design is adopted and finally, 81 experimental groups are produced. Sensitivity SV and mass Ma are defined as evaluation parameters, and structural parameters of experimental groups are imported into the FEM software to obtain the corresponding calculation results. These simulation data are imported into neural networks with the PSO algorithm. For a comprehensively accurate examination, three cases are used to verify our design method, and every case endows the performance parameters with different weights and expected values. The corresponding structural parameters of each case are given out after 24 iterations. Finally, the maximum calculation errors of SV and Ma are 1.2941% and 0.1335%, respectively, proving the feasibility of the high-efficiency design method.

Bottom-up micromachined PZT film-based ultrasonic microphone with compressible parylene tube

This paper reports on a micromachined ultrasonic microphone using a bottom-up fabrication scheme. Starting with a 4 μm-thick titanium foil as the substrate, each functional film and key element was added to the foil substrate to complete the ultrasonic microphone. The piezoelectric lead zirconate titanate film hydrothermally grown on the patterned substrate with low residual stress effectively deflected the unimorph-sensing cantilever array of the microphone under ultrasound pressure. The created cantilever array structure secured on a 250 μm-thick SU8 hollow plate formed an ultrasonic microphone plate that was tested with a sensitivity of −60 dBV Pa−1 at 21 kHz (with 0 dB gain amplification) and an operation bandwidth of 5–55 kHz. Different thicknesses of parylene films ranging from 0.5 to 2 μm overlaid over the entire sensing region and converted the cantilever-to-diaphragm-structured microphone for further investigation. An enhanced result was observed when the deposited parylene film thickness was in the submicron range. The sensitivity of the microphone can be further enhanced by up to 33% by adding a parylene-film-made compressible tube to act as a Helmholtz resonator (HR). The HR model was discussed and compared with the experimental results. The output amplitude of the developed microphone assembled with the compressible tube demonstrates a 15 dB increase compared to that of a commercial capacitive MEMS ultrasonic microphone.

Smoldering fire detection using low-power capacitive MEMS hydrogen sensor for future fire alarm

In this study, we demonstrated detection of a smoldering fire using a low-power hydrogen sensor. To detect the low levels of hydrogen gas generated by smoldering fires, we used a capacitive MEMS hydrogen sensor with a microheater. The microheater accelerates the reduction of palladium oxide on the surface of the sensing film by hydrogen. Thus, more hydrogen is entrapped within the sensing film, and the sensitivity to ppm amounts of hydrogen is improved. The low thermal capacity and high thermal resistance of the structure enabled localized heating of the sensitive film at high speed (1 ms), thereby achieving sub-mW low power consumption by intermittent sensing. The fabricated hydrogen sensor was installed in a small wireless module and placed on a ceiling 3 m from a smoldering cotton fire. Our hydrogen sensor successfully detected 66 ppm hydrogen generated by the fire, and also detected the decrease in hydrogen by room exhaust.

The Use of Shape Accel Array for Deformation Monitoring and Parameter Inversion of a 300 m Ultrahigh Rockfill Dam

The global construction of rockfill dams has now surpassed the 300 m height level. Despite great achievements in dam design and construction, monitoring techniques have lagged behind the development of high rockfill dams. Existing deformation monitoring techniques are ill-suited to the high earth and water pressures, and extended monitoring periods are required for ultrahigh rockfill dams. This study introduces, for the first time, the use of a shape accel array (SAA) to monitor internal displacement in a 300 m high earth core rockfill dam. The SAA employs a rope-like array of capacitive MEMS accelerometers for deformation measurement. Compared to conventional monitoring techniques, SAA is a data-intensive monitoring technique. Based on the intensive data obtained from SAA, we employed a parameter inversion method, utilizing multiobjective optimization algorithm, the nondominated sorting genetic algorithm-III (NSGA-III), to inverse the constitutive model parameters of the rockfill dam. The multiobjective parameter inversion method maximizes the use of multisource monitoring data for predicting rockfill dam deformation.

Highly Sensitive Capacitive MEMS for Photoacoustic Gas Trace Detection.

An enhanced MEMS capacitive sensor is developed for photoacoustic gas detection. This work attempts to address the lack of the literature regarding integrated and compact silicon-based photoacoustic gas sensors. The proposed mechanical resonator combines the advantages of silicon technology used in MEMS microphones and the high-quality factor, characteristic of quartz tuning fork (QTF). The suggested design focuses on a functional partitioning of the structure to simultaneously enhance the collection of the photoacoustic energy, overcome viscous damping, and provide high nominal capacitance. The sensor is modeled and fabricated using silicon-on-insulator (SOI) wafers. First, an electrical characterization is performed to evaluate the resonator frequency response and nominal capacitance. Then, under photoacoustic excitation and without using an acoustic cavity, the viability and the linearity of the sensor are demonstrated by performing measurements on calibrated concentrations of methane in dry nitrogen. In the first harmonic detection, the limit of detection (LOD) is 104 ppmv (for 1 s integration time), leading to a normalized noise equivalent absorption coefficient (NNEA) of 8.6 ⋅ 10-8 Wcm-1 Hz-1/2, which is better than that of bare Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS), a state-of-the-art reference to compact and selective gas sensors.