Microelectromechanical Systems Devices Research Articles

Effect of laser power on structural and magnetic properties of anisotropic Nd-Fe-B film magnets prepared by PLD method

Anisotropic Nd-Fe-B film magnets are applied to miniaturized electronic devices and MEMS (Micro Electro Mechanical Systems) devices have been prepared by the sputtering method. However, the thickness of each film is mainly less than 20 μm. We have already fabricated anisotropic rare-earth film magnets by pulsed laser deposition (PLD) technique. In this study, an investigation has been carried out on increasing laser beam power for a high deposition rate. Although the thickness of the films increases as laser power increases, it is suggested that the residual magnetic polarization ratio and coercivity values of anisotropic Nd-Fe-B film magnets are not allowed to deteriorate with increasing laser power or deposition rate. These results suggest that we have the facility in obtaining perpendicularly anisotropic Nd-Fe-B thick-film magnets using the PLD method.

Design of MEMS capacitive comb accelerometer with perforated proof mass for seismic applications

Micro Electro Mechanical System (MEMS) sensors are characterized by their small size, but their performances exceed that of their macro-scale counterparts. The small size of MEMS devices and their integration with microelectronics proves a major advantage. In this paper, a design of MEMS capacitive comb accelerometer for seismology application using COMSOL Multiphysics platform is presented. A seismometer (also known as a seismograph) is a device that is used to measure and record the behavior of seismic waves. With this data, the location and measure of earthquakes can be detected. This seismic device has a large frequency band, compared to traditional geophones and seismographs. In this paper, a study to measure amplitudes and frequencies of vibrations is presented, and the results are analyzed and compared for perforated mass and solid proof mass. The effect of the size of etch hole for perforation is also studied.The displacement sensitivity and capacitive sensitivity of accelerometer are found to be 1.188 × 10-9m/g and 1.093 × 10-21F, respectively.

Design and Development of a MOEMS Accelerometer Using SOI Technology.

The micro-electromechanical system (MEMS) sensors are suitable devices for vibrational analysis in complex systems. The Fabry-Pérot interferometer (FPI) is used due to its high sensitivity and immunity to electromagnetic interference (EMI). Here, we present the design, fabrication, and characterization of a silicon-on-insulator (SOI) MEMS device, which is embedded in a metallic package and connected to an optical fiber. This integrated micro-opto-electro-mechanical system (MOEMS) sensor contains a mass structure and handle layers coupled with four designed springs built on the device layer. An optical reading system using an FPI is used for displacement interrogation with a demodulation technique implemented in LabVIEW®. The results indicate that our designed MOEMS sensor exhibits a main resonant frequency of 1274 Hz with damping ratio of 0.0173 under running conditions up to 7 g, in agreement with the analytical model. Our experimental findings show that our designed and fabricated MOEMS sensor has the potential for engineering application to monitor vibrations under high-electromagnetic environmental conditions.

Thermoelastic damping in MEMS gyroscopes at high frequencies

Microelectromechanical systems (MEMS) gyroscopes are widely used, e.g., in modern automotive and consumer applications, and require signal stability and accuracy in rather harsh environmental conditions. In many use cases, device reliability must be guaranteed under large external loads at high frequencies. The sensitivity of the sensor to such external loads depends strongly on the damping, or rather quality factor, of the high-frequency mechanical modes of the structure. In this paper, we investigate the influence of thermoelastic damping on several high-frequency modes by comparing finite element simulations with measurements of the quality factor in an application-relevant temperature range. We measure the quality factors over different temperatures in vacuum, to extract the relevant thermoelastic material parameters of the polycrystalline MEMS device. Our simulation results show a good agreement with the measured quantities, therefore proving the applicability of our method for predictive purposes in the MEMS design process. Overall, we are able to uniquely identify the thermoelastic effects and show their significance for the damping of the high-frequency modes of an industrial MEMS gyroscope. Our approach is generic and therefore easily applicable to any mechanical structure with many possible applications in nano- and micromechanical systems.

A validated modeling strategy for piezoelectric MEMS loudspeakers including viscous effects

Piezoelectric micro-electro-mechanical system (MEMS) loudspeakers are drawing more interest due to their applications in new-developing audio technologies. MEMS devices’ small dimensions necessitate including thermal and viscous effects in the surrounding air when simulating their behaviors. Thus, the linearized mass, momentum and energy conservation equations are used to describe these effects. These formulations are implemented in our open-source finite element program openCFS. In this article, we model a 3D piezoelectric MEMS loudspeaker in two configurations: open and closed back-volume, which behave differently due to the effects of air viscosity and pressure forces between the cantilever and the closed back-volume. Furthermore, using a customized vacuum chamber, the atmospheric pressure is varied and its effects are studied in these two configurations, numerically and experimentally. Experimental results prove that our model predicts the behavior of the piezoelectric MEMS loudspeaker in various configurations very well. Additional simulations illustrate the effect of the slit thickness and thermal losses.

Intra-unit reliability and movement variability of submission grappling external load as measured by torso mounted accelerometery.

Submission grappling consists of skills and movements used in combat sports to physically control opponents whilst trying to apply choke holds and joint locks. There is currently no accepted method of monitoring external load in grappling-based sports due to the absence of key variables such as distance, velocity or time. The primary aim of this study was to determine whether PlayerLoad is a reliable variable for measuring external load of submission grappling movements, with a secondary aim of determining the between repetition variance of submission grappling movements. 7 experienced submission grapplers were recruited. Each wore a torso mounted Catapult® Optimeye S5 microelectromechanical systems (MEMS) device and completed 5 repetitions of each of the following: 4 submission techniques; 5 transition techniques; 2 guard pass techniques; 2 takedown techniques. Accumulated PlayerLoad (PLdACC) was recorded as a marker of absolute load, with accumulated PlayerLoad per minute (PLdACC∙min-1) representing relative load. Reliability of each was assessed using intraclass correlation coefficient (ICC(3,1)) (≥ 0.70). Between repetition movement variation was assessed via coefficient of variation with 95% confidence intervals (CV, 95%CI) (acceptable ≤ 15%, good ≤ 10%). PLdACC ICC(3,1) range = 0.78-0.98, with CV range = 9-22%. PLdACC∙min-1 ICC(3,1) range = 0.83-0.98, with CV range = 11-19%. Though several variables displayed CV > 15%, all had 95%CI lower boundaries ≤ 15%. Whilst PlayerLoad was found to be a reliable measure for submission grappling, relatively high CVs across most techniques examined suggest PlayerLoad may not be appropriate for measuring changes in external load for individual movements in submission grappling. However, it may prove a useful tool for monitoring the external load of full, grappling-based, training sessions within an individual.

An Improved Optimization Model to Predict the Deposition Rate and Smoothness of Ni Pulse-Reverse Electroplating Based on ANN and Experimental Results

The metallic layers are an essential part of MEMS (micro electromechanical system) devices, and their deposition process must be accurately controlled; this may lead to difficulties as there are many input parameters for such a process. This research focuses on the input parameters’ effects on the Ni pulse-reverse electroplating. A neural network was constructed to characterize the pulse-reverse nickel electroforming process parameters. The sample training has accurately established the mapping relationship between input and output parameters. The nickel layer thickness and surface roughness prediction in the pulse-reverse electroplating process was realized and verified by experimental tests with a test error of 3.3%. Then, the effect of direct and reverse current density, deposition time, structure width, and stirring speed as input parameters on the thickness and surface roughness are investigated. Finally, a novel 4D diagram has been developed to derive the optimal values of direct and reverse current density relative to thickness, surface roughness, and deposition time. This diagram can help researchers and industries find suitable parameters to achieve the desired deposited Ni layer’s properties.

Structural Optimization and Mechanical Simulation of MEMS Thin-Film Getter-Heater Unit.

A MEMS thin-film getter-heater unit has been previously proposed for the vacuum packaging of a Micro-Electro-Mechanical System (MEMS) device, where the floating structure (FS) design is found to be obviously more power-efficient than the solid structure (SS) one by heat transfer capacity simulation. However, the mechanical strength of the FS is weaker than the SS by nature. For high temperature usage, the unit structure must be optimized in order to avoid fracture of the cantilever beam or film delamination due to strong excessive stress caused by heating. In this paper, COMSOL is used to simulate the stress and deformation of the MEMS thin-film getter-heater unit with the cantilever structure. By comparing various cantilever structures, it is found that a model with a symmetrically-shaped heater and edge-center-located cantilever model (II-ECLC model) is the most suitable. In this model, even when the structure is heated to about 600 °C, the maximum stress of the cantilever beam is only 455 MPa, much lower than the tensile strength of silicon nitride (Si3N4, 12 GPa), and the maximum deformation displacement is about 200 μm. Meanwhile, the interfacial stress between the getter and the insulating layer is 44 MPa, sufficiently lower than the adhesion strength between silicon nitride film and titanium film (400-1850 MPa). It is further found that both the stress of the cantilever structure and the interfacial stress between the getter and the insulating layer beneath increase linearly with temperature; and the deformation of the cantilever structure is proportional to its stress. This work gives guidance on the design of MEMS devices with cantilever structures and works in high temperature situations.

The Design and Fabrication of a MEMS Electronic Calibration Chip.

During the test of microelectromechanical system (MEMS) devices, calibration of test cables, loads and test instruments is an indispensable step. Calibration kits with high accuracy, great operability and small loss can reduce the systematic errors in the test process to the greatest extent and improve the measurement accuracy. Aiming at the issues of the conventional discrete calibration piece unit, which presents cumbersome calibration steps and large system loss, an integrated electronic calibration chip based on frequency microelectromechanical system (RF MEMS) switches is designed and fabricated. The short-open-load-through (SOLT) calibration states can be completed on a single chip, step by step, by adjusting the on-off state of the RF MEMS switches. The simulation results show that the operating frequency of the electronic calibration piece covers the range of DC~26.5 GHz, the insertion loss in through (thru) state is less than 0.2 dB, the return loss is less than 1.0 dB in short-circuit and open-circuit states, the return loss under load-circuit state is less than 20 dB and its size is only 2.748 mm × 2.2 mm × 0.5 mm. This novel calibration chip design has certain esteem for advancing calibration exactness and effectiveness.

Defect Detection of MEMS Based on Data Augmentation, WGAN-DIV-DC, and a YOLOv5 Model

Surface defect detection of micro-electromechanical system (MEMS) acoustic thin film plays a crucial role in MEMS device inspection and quality control. The performances of deep learning object detection models are significantly affected by the number of samples in the training dataset. However, it is difficult to collect enough defect samples during production. In this paper, an improved YOLOv5 model was used to detect MEMS defects in real time. Mosaic and one more prediction head were added into the YOLOv5 baseline model to improve the feature extraction capability. Moreover, Wasserstein divergence for generative adversarial networks with deep convolutional structure (WGAN-DIV-DC) was proposed to expand the number of defect samples and to make the training samples more diverse, which improved the detection accuracy of the YOLOv5 model. The optimal detection model achieved 0.901 mAP, 0.856 F1 score, and a real-time speed of 75.1 FPS. As compared with the baseline model trained using a non-augmented dataset, the mAP and F1 score of the optimal detection model increased by 8.16% and 6.73%, respectively. This defect detection model would provide significant convenience during MEMS production.

Investigation of temperature sensitivity of a MEMS gravimeter based on geometric anti-spring.

This paper describes a technique for temperature sensitivity or thermal sag measurements of a geometric anti-spring based microelectromechanical system (MEMS) gravimeter (Wee-g). The Wee-g MEMS gravimeter is currently fabricated on a (100) silicon wafer using standard micro-nano fabrication techniques. The thermal behavior of silicon indicates that the Young's modulus of silicon decreases with increase in temperature (∼64 ppm/K). This leads to a softening of the silicon material, resulting in the proof mass displacing (or sagging) under the influence of increasing temperature. It results in a change in the measured gravity, which is expressed as temperature sensitivity in terms of change in gravity per degree temperature. The temperature sensitivity for the silicon based MEMS gravimeter is found to be 60.14-64.87, 61.76, and 62.76 µGal/mK for experimental, finite element analysis (FEA) simulation, and analytical calculations, respectively. It suggests that the gravimeter's temperature sensitivity is dependent on the material properties used to fabricate the MEMS devices. In this paper, the experimental measurements of thermal sag are presented along with analytical calculations and simulations of the effect using FEA. The bespoke optical measurement system to quantify the thermal sag is also described. The results presented are an essential step toward the development of temperature insensitive MEMS gravimeters.

Unlocking the potential of piezoelectric films grown on vertical surfaces for inertial MEMS

Devices based on piezoelectric actuation are some of the most promising among the microelectromechanical systems (MEMS). Commonly, piezoelectric materials, such as aluminum nitride (AlN), are utilized to perform out-of-the-plane motion due to a clear and simple fabrication process. However, in-plane actuation is essential for inertial sensors, such as gyroscopes, where actuation and sensing directions are strongly perpendicular. Moreover, in-plane actuation and sensing can also find applications beyond inertial sensors. This paper presents the finite-element-modeling (FEM) of the MEMS gyroscope with the AlN thin films on vertical sidewalls that demonstrate in-plane actuation and unleash the full potential of piezoelectric AlN MEMS devices. Current work focuses on inertial sensing with the half-fork MEMS gyroscope’s FEM simulation. This device has a significant advantage in scaling, while its output is in a competitive range among existing commercial angular rate sensors. The FEM simulations in COMSOL Multiphysics (COMSOL) allow to measure the angular rate sensitivity and perform further design optimization. Ultimately, this research shows the potential of the AlN sidewall structures in MEMS gyroscopes by optimizing the angular rate sensitivity in the range of [− 64.64] degrees per second (dps) with the peak value of 1 mV/dps.

Hybrid Model-Based and Data-Driven Solution for Uncertainty Quantification at the Microscale

Background: Due to their size, microelectromechanical systems (MEMS) display performance indices affected by uncertainties linked to the mechanical properties and to the geometry of the films constituting their movable parts. Objective: In this perspective, a recently proposed multiscale and hybrid solution for uncertainty quantification is discussed. Methods: The proposed method is based on the (deep) learning of the morphology-affected elasticity of the polycrystalline films and of the microfabrication-induced defective geometry of the devices. The results at the material and at the device levels are linked through a reduced-order representation of the response of the entire device to the external stimuli, foreseen to finally feed a Monte Carlo uncertainty quantification engine. Results: Preliminary results relevant to a single-axis resonant Lorentz force micro-magnetometer have shown a noteworthy capability of the proposed multiscale deep learning method to account for the mentioned uncertainty sources at the microscale. Conclusion: A promising two-scale deep learning approach has been proposed for polysilicon MEMS sensors to account for both materials- and geometry-governed uncertainties and to properly describe the scale-dependent response of MEMS devices.

Thermomechanical properties of aluminum oxide thin films made by atomic layer deposition

In microelectromechanical system devices, thin films experience thermal processing at temperatures some cases exceeding the growth or deposition temperature of the film. In the case of the thin film grown by atomic layer deposition (ALD) at relatively low temperatures, post-ALD thermal processing or high device operation temperature might cause performance issues at device level or even device failure. In this work, residual stress and the role of intrinsic stress in ALD Al2O3 films grown from Me3Al and H2O, O3, or O2 (plasma ALD) were studied via post-ALD thermal processing. Thermal expansion coefficient was determined using thermal cycling and the double substrate method. For some samples, post-ALD thermal annealing was done in nitrogen at 300, 450, 700, or 900 °C. Selected samples were also studied for crystallinity, composition, and optical properties. Samples that were thermally annealed at 900 °C had increased residual stress value (1400–1600 MPa) upon formation of denser Al2O3 phase. The thermal expansion coefficient varied somewhat between Al2O3 made using different oxygen precursors. For thermal-Al2O3, intrinsic stress decreased with increasing growth temperature. ALD Al2O3 grown with plasma process had the lowest intrinsic stress. The results show that ALD Al2O3 grown at 200 and 300 °C is suitable for applications, where films are exposed to post-ALD thermal processing even at temperature of 700 °C without a major change in optical properties or residual stress.

Radially symmetric stationary solutions for a MEMS type reaction–diffusion equation with fringing field

Radially symmetric stationary solutions for a micro-electro-mechanical system (MEMS) type reaction–diffusion equation with fringing field are considered. This equation arises in the study of the MEMS devices. This paper is devoted to the study of the existence of these solutions, information about their shape, and their asymptotic behaviour. These are studied by applying the framework that combines Poincaré type compactification, classical dynamical systems theory, and geometric methods for desingularization of vector fields called the blow-up technique.

Research on a Distributed Calibration Method Based on Specific Force Measurement

Micro-electro-mechanical system (MEMS) inertial devices are small volume, lightweight, low cost, and have mass-production characteristics. The development trend of inertial modules is to reduce cost and improve accuracy, and batch calibration of MEMS devices is one of the most feasible solutions to reduce cost. In this paper, we propose a distributed calibration method based on system-level, discrete calibration. The distributed calibration method requires only one or a few rotations of the combined and arranged devices to excite the individual error parameters of the inertial instruments. In this study, the relationship between the error parameters and the navigation error was rewritten using equivalence transformation, and the 24 error parameters of the device were identified by the distributed least-squares estimation using the velocity error as the observed quantity. In simulation experiments, this method could calibrate more MEMS devices simultaneously than the traditional calibration method with the exact accuracy requirement.

Nondestructive Wafer Level MEMS Piezoelectric Device Thickness Detection.

This paper introduces a novel nondestructive wafer scale thin film thickness measurement method by detecting the reflected picosecond ultrasonic wave transmitting between different interfacial layers. Unlike other traditional approaches used for thickness inspection, this method is highly efficient in wafer scale, and even works for opaque material. As a demonstration, we took scandium doped aluminum nitride (AlScN) thin film and related piezoelectric stacking layers (e.g. Molybedenum/AlScN/Molybdenum) as the case study to explain the advantages of this approach. In our experiments, a laser with a wavelength of 515 nm was used to first measure the thickness of (1) a single Molybdenum (Mo) electrode layer in the range of 100-300 nm, and (2) a single AlScN piezoelectric layer in the range of 600-1000 nm. Then, (3) the combined stacking layers were measured. Finally, (4) the thickness of a standard piezoelectric composite structure (Mo/AlScN/Mo) was characterized based on the conclusions and derivation extracted from the aforementioned sets of experiments. This type of standard piezoelectric composite has been widely adopted in a variety of Micro-electromechanical systems (MEMS) devices such as the Piezoelectric Micromachined Ultrasonic Transducer (PMUT), the Film Bulk Acoustic Resonator (FBAR), the Surface Acoustic Wave (SAW) and more. A comparison between measurement data from both in-line and off-line (using Scanning Electron Microscope) methods was conducted. The result from such in situ 8-inch wafer scale measurements was in a good agreement with the SEM data.

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.

Frequency combs in a MEMS resonator featuring 1:2 internal resonance: ab initio reduced order modelling and experimental validation

This paper is devoted to a detailed analysis of the appearance of frequency combs in the dynamics of a micro-electro-mechanical systems (MEMS) resonator featuring 1:2 internal resonance. To that purpose, both experiments and numerical predictions are reported and analysed to predict and follow the appearance of the phononic frequency comb arising as a quasi-periodic regime between two Neimark-Sacker bifurcations. Numerical predictions are based on a reduced-order model built thanks to an implicit condensation method, where both mechanical nonlinearities and electrostatic forces are taken into account. The reduced order model is able to predict a priori, i.e. without the need of experimental calibration of parameters, and in real time, i.e. by solving one or two degrees-of-freedom system of equations, the nonlinear behaviour of the MEMS resonator. Numerical predictions show a good agreement with experiments under different operating conditions, thus proving the great potentiality of the proposed simulation tool. In particular, the bifurcation points and frequency content of the frequency comb are carefully predicted by the model, and the main features of the periodic and quasi-periodic regimes are given with accuracy, underlining that the complex dynamics of such MEMS device is effectively driven by the characteristics of the 1:2 internal resonance.

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.