MEMS Accelerometers

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc

Spiral-Shaped Piezoelectric MEMS Cantilever Array for Fully Implantable Hearing Systems

Fully implantable, self-powered hearing aids with no external unit could significantly increase the life quality of patients suffering severe hearing loss. This highly demanding concept, however, requires a strongly miniaturized device which is fully implantable in the middle/inner ear and includes the following components: frequency selective microphone or accelerometer, energy harvesting device, speech processor, and cochlear multielectrode. Here we demonstrate a low volume, piezoelectric micro-electromechanical system (MEMS) cantilever array which is sensitive, even in the lower part of the voice frequency range (300–700 Hz). The test array consisting of 16 cantilevers has been fabricated by standard bulk micromachining using a Si-on-Insulator (SOI) wafer and aluminum nitride (AlN) as a complementary metal-oxide-semiconductor (CMOS) and biocompatible piezoelectric material. The low frequency and low device footprint are ensured by Archimedean spiral geometry and Si seismic mass. Experimentally detected resonance frequencies were validated by an analytical model. The generated open circuit voltage (3–10 mV) is sufficient for the direct analog conversion of the signals for cochlear multielectrode implants

Development and implementation of a deflection amplification mechanism for capacitive accelerometers

Micro-Electro-Mechanical-Systems (MEMS) and especially physical sensors are part of a flourishing market ranging from consumer electronics to space applications. They have seen a great evolution throughout the last decades, and there is still considerable research effort for further improving their performance. This is reflected by the plethora of commercial applications using them but also by the demand from industry for better specifications. This demand together with the needs of novel applications fuels the research for better physical sensors.Applications such as inertial, seismic, and precision tilt sensing demand very high sensitivity and low noise. Bulk micromachined capacitive inertial sensors seem to be the most viable solution as they offer a large inertial mass, high sensitivity, good noise performance, they are easy to interface with, and of low cost. The aim of this thesis is to improve the performance of bulk micromachined capacitive sensors by enhancing their sensitivity and noise floor.MEMS physical sensors, most commonly, rely on force coupling and a resulting deflection of a proof mass or membrane to produce an output proportional to a stimulus of the physical quantity to be measured. Therefore, the sensitivity to a physical quantity may be improved by increasing the resulting deflection of a sensor. The work presented in this thesis introduces an approach based on a mechanical motion amplifier with the potential to improve the performance of mechanical MEMS sensors that rely on deflection to produce an output signal.The mechanical amplifier is integrated with the suspension system of a sensor. It comprises a system of micromachined levers (microlevers) to enhance the deflection of a proof mass caused by an inertial force. The mechanism can be used in capacitive accelerometers and gyroscopes to improve their performance by increasing their output signal. As the noise contribution of the electronic read-out circuit of a MEMS sensor is, to first order, independent of the amplitude of its input signal, the overall signal-to-noise ratio (SNR) of the sensor is improved.There is a rather limited number of reports in the literature for mechanical amplification in MEMS devices, especially when applied to amplify the deflection of inertial sensors. In this study, after a literature review, mathematical and computational methods to analyse the behaviour of microlevers were considered. By using these methods the mechanical and geometrical characteristics of microlevers components were evaluated. In order to prove the concept, a system of microlevers was implemented as a mechanical amplifier in capacitive accelerometers.All the mechanical structures were simulated using Finite Element Analysis (FEA) and system level simulations. This led to first order optimised devices that were used to design appropriate masks for fabrication. Two main fabrication processes were used; a Silicon on Insulator (SOI) process and a Silicon on Glass (SoG) process. The SOI process carried out at the University of Southampton evolved from a one mask to a two mask dicing free process with a yield of over 95%, in its third generation. The SoG is a well-established process at the University of Peking that uses three masks.The sensors were evaluated using both optical and electrical means. The results from the first prototype sensor design (1HAN) revealed an amplification factor of 40 and a mechanically amplified sensitivity of 2.39V/g. The measured natural frequency of the first mode of the sensor was at 734Hz and the full-scale measurement range was up to 7g with a maximum nonlinearity of 2%. The measurements for all the prototype sensor designs were very close to the predicted values with the highest discrepancy being 22%. The results of this research show that mechanical amplification is a very promising concept that can offer increased sensitivity in inertial sensors without increasing the noise. Experimental results show that there is plenty of room for improvement and that viable solutions may be produced by using the presented approach. The applications of this scheme are not restricted only to inertial sensors but as the results show it can be used in a broader range of micromachined devices

A Resonant Based Test Methodology for Capacitive MEMs

This work presents a test method for capacitive Micro-Electro-Mechanical Systems (MEMS). A major class of MEMS sensors operate based on the principle of capacitance variation.The proposed test method in this work utilizes a resonant circuit to detect structural defects of capacitive MEMS sensors. It is shown that a small variation of MEMS capacitance due to a defect alters the resonance frequency considerably. It is also shown that the variation of the output amplitude can be observed for fault detection if an inductor with a high quality factor is employed in the test circuit. Mathematical approach is taken and verified to prove the validity of this work. The effects of structural defects such as short, broken and missing fingers of the MEMS comb-drive on the equivalent circuit models have been determined through frequency domain simulations.Simulation results and experimental measurements using an implemented MEMS comb drive indicate that the proposed method can detect common faults such as missing, broken and short fingers

A Review on Key Issues and Challenges in Devices Level MEMS Testing

The present review provides information relevant to issues and challenges in MEMS testing techniques that are implemented to analyze the microelectromechanical systems (MEMS) behavior for specific application and operating conditions. MEMS devices are more complex and extremely diverse due to the immersion of multidomains. Their failure modes are distinctive under different circumstances. Therefore, testing of these systems at device level as well as at mass production level, that is, parallel testing, is becoming very challenging as compared to the IC test, because MEMS respond to electrical, physical, chemical, and optical stimuli. Currently, test systems developed for MEMS devices have to be customized due to their nondeterministic behavior and complexity. The accurate measurement of test systems for MEMS is difficult to quantify in the production phase. The complexity of the device to be tested required maturity in the test technique which increases the cost of test development; this practice is directly imposed on the device cost. This factor causes a delay in time-to-market

A Review on Key Issues and Challenges in Devices Level MEMS Testing

The present review provides information relevant to issues and challenges in MEMS testing techniques that are implemented to analyze the microelectromechanical systems (MEMS) behavior for specific application and operating conditions. MEMS devices are more complex and extremely diverse due to the immersion of multidomains. Their failure modes are distinctive under different circumstances. Therefore, testing of these systems at device level as well as at mass production level, that is, parallel testing, is becoming very challenging as compared to the IC test, because MEMS respond to electrical, physical, chemical, and optical stimuli. Currently, test systems developed for MEMS devices have to be customized due to their nondeterministic behavior and complexity. The accurate measurement of test systems for MEMS is difficult to quantify in the production phase. The complexity of the device to be tested required maturity in the test technique which increases the cost of test development; this practice is directly imposed on the device cost. This factor causes a delay in time-to-market

FLEXIBLE LOW-COST HW/SW ARCHITECTURES FOR TEST, CALIBRATION AND CONDITIONING OF MEMS SENSOR SYSTEMS

During the last years smart sensors based on Micro-Electro-Mechanical systems (MEMS) are widely spreading over various fields as automotive, biomedical, optical and consumer, and nowadays they represent the outstanding state of the art. The reasons of their diffusion is related to the capability to measure physical and chemical information using miniaturized components. The developing of this kind of architectures, due to the heterogeneities of their components, requires a very complex design flow, due to the utilization of both mechanical parts typical of the MEMS sensor and electronic components for the interfacing and the conditioning. In these kind of systems testing activities gain a considerable importance, and they concern various phases of the life-cycle of a MEMS based system. Indeed, since the design phase of the sensor, the validation of the design by the extraction of characteristic parameters is important, because they are necessary to design the sensor interface circuit. Moreover, this kind of architecture requires techniques for the calibration and the evaluation of the whole system in addition to the traditional methods for the testing of the control circuitry. The first part of this research work addresses the testing optimization by the developing of different hardware/software architecture for the different testing stages of the developing flow of a MEMS based system. A flexible and low-cost platform for the characterization and the prototyping of MEMS sensors has been developed in order to provide an environment that allows also to support the design of the sensor interface. To reduce the reengineering time requested during the verification testing a universal client-server architecture has been designed to provide a unique framework to test different kind of devices, using different development environment and programming languages. Because the use of ATE during the engineering phase of the calibration algorithm is expensive in terms of ATE’s occupation time, since it requires the interruption of the production process, a flexible and easily adaptable low-cost hardware/software architecture for the calibration and the evaluation of the performance has been developed in order to allow the developing of the calibration algorithm in a user-friendly environment that permits also to realize a small and medium volume production. The second part of the research work deals with a topic that is becoming ever more important in the field of applications for MEMS sensors, and concerns the capability to combine information extracted from different typologies of sensors (typically accelerometers, gyroscopes and magnetometers) to obtain more complex information. In this context two different algorithm for the sensor fusion has been analyzed and developed: the first one is a fully software algorithm that has been used as a means to estimate how much the errors in MEMS sensor data affect the estimation of the parameter computed using a sensor fusion algorithm; the second one, instead, is a sensor fusion algorithm based on a simplified Kalman filter. Starting from this algorithm, a bit-true model in Mathworks Simulink(TM) has been created as a system study for the implementation of the algorithm on chip

Laterally Movable Gate Field Effect Transistor (LMGFET) for microsensor and microactuator applications

Laterally Movable Gate Field Effect Transistor (LMGFET) invented at LSU as a microactuator is the subject of study in this research. The gate moving in lateral direction in a LMGFET changes channel width but keeps the channel length and the gap between the metal gate and the gate oxide constant. LMGFET offers linear change in drain current with gate motion and a large displacement range. This research is the first demonstration of LMGFET. In this dissertation, a post-IC LIGA-like process for LMGFET microstructure fabrication has been developed that is compatible with monolithic integration with CMOS circuitry. A two-mask post-IC process has been developed in this research for LMGFET fabrication. This novel process utilizes S1813 photoresist as a sacrificial layer in conjunction with a thicker resist like AZ P4620 or SU-8 as an electroplating mold. New curing temperatures for the sacrificial layer photoresist have been determined for this purpose. LMGFET microstructures have been successfully integrated with CMOS circuitry on the same chip to form integrated microsystem. LMGFET microstructure driven by a comb-drive with serpentine retaining spring shows sensitivities Sel of 2 and 1.43 nA/V respectively at 5 and 25 Hz. These numbers reflect that LMGFET is capable of measuring nm range displacement. Electrical characteristics of a depletion type LMGFET structure are measured and show an average sensitivity Sl of - 4 µA/µm at drain to source voltage VDS of 10 V with the gate shorted to source. Several applications of microsystems utilizing LMGFET microstructures as a position sensor or an accelerometer, a spectrum analyzer or an electro-mechanical filter and a mechanical/optical switch are described

Development of a light-powered microstructure : enhancing thermal actuation with near-infrared absorbent gold nanoparticles.

Development of microscale actuating technologies has considerably added to the toolset for interacting with natural components at the cellular level. Small-scale actuators and switches have potential in areas such as microscale pumping and particle manipulation. Thermal actuation has been used with asymmetric geometry to create large deflections with high force relative to electrostatically driven systems. However, many thermally based techniques require a physical connection for power and operate outside the temperature range conducive for biological studies and medical applications. The work presented here describes the design of an out-of-plane bistable switch that responds to near-infrared light with wavelength-specific response. In contrast to thermal actuating principles that require wired conductive components for Joule heating, the devices shown here are wirelessly powered by near -infrared (IR) light by patterning a wavelength-specific absorbent gold nanoparticle (GNP) film onto the microstructure. An optical window exists which allows near-IR wavelength light to permeate living tissue, and high stress mismatch in the bilayer geometry allows for large actuation at biologically acceptable limits. Patterning the GNP film will allow thermal gradients to be created from a single laser source, and integration of various target wavelengths will allow for microelectromechanical (MEMS) devices with multiple operating modes. An optically induced temperature gradient using wavelength-selective printable or spinnable coatings would provide a versatile method of wireless and non-invasive thermal actuation. This project aims to provide a fundamental understanding of the particle and surface interaction for bioengineering applications based on a “hybrid” of infrared resonant gold nanoparticles and MEMS structures. This hybrid technology has potential applications in light-actuated switches and other mechanical structures. Deposition methods and surface chemistry are integrated with three-dimensional MEMS structures in this work. The long-term goal of this project is a system of light-powered microactuators for exploring cells\u27 response to mechanical stimuli, adding to the fundamental understanding of tissue response to everyday mechanical stresses at the molecular level

Towards reliable parameter extraction in MEMS final module testing using Bayesian inference

In micro-electro-mechanical systems (MEMS) testing high overall precision and reliability are essential. Due to the additional requirement of runtime efficiency, machine learning methods have been investigated in recent years. However, these methods are often associated with inherent challenges concerning uncertainty quantification and guarantees of reliability. The goal of this paper is therefore to present a new machine learning approach in MEMS testing based on Bayesian inference to determine whether the estimation is trustworthy. The overall predictive performance as well as the uncertainty quantification are evaluated with four methods: Bayesian neural network, mixture density network, probabilistic Bayesian neural network and BayesFlow. They are investigated under the variation in training set size, different additive noise levels, and an out-of-distribution condition, namely the variation in the damping factor of the MEMS device. Furthermore, epistemic and aleatoric uncertainties are evaluated and discussed to encourage thorough inspection of models before deployment striving for reliable and efficient parameter estimation during final module testing of MEMS devices. BayesFlow consistently outperformed the other methods in terms of the predictive performance. As the probabilistic Bayesian neural network enables the distinction between epistemic and aleatoric uncertainty, their share of the total uncertainty has been intensively studied