Electrostatic Discharge

As we enter the nanoelectronics era, electrostatic discharge (ESD) phenomena is an important issue for everything from micro-electronics to nanostructures. This book provides insight into the operation and design of micro-gaps and nanogenerators with chapters on low capacitance ESD design in advanced technologies, electrical breakdown in micro-gaps, nanogenerators from ESD, and theoretical prediction and optimization of triboelectric nanogenerators. The information contained herein will prove useful for for engineers and scientists that have an interest in ESD physics and design

System Integration of Flexible and Multifunctional Thin Film Sensors for Structural Health Monitoring

Greater information is needed on the state of civil infrastructure to ensure public safety and cost-efficient management. Lack of infrastructure investment and foreseeable funding challenges mandate a more intelligent approach to future maintenance of infrastructure systems. Much of the technology currently utilized to assess structural performance is based on discrete sensors. While such sensors can provide valuable data, they can lack sufficient resolution to accurately identify damage through inverse methods. Alternatively, technologies have shown promise for distributed, direct damage detection with flexible thin film and multifunctional polymer-nanocomposite materials. However, challenges remain as significant past work has focused on material optimization as opposed to sensing systems for damage detection. This dissertation offers novel methods for direct and distributed strain sensing by providing a fabrication methodology for broadly enabling thin film sensing technologies in structural health monitoring (SHM) applications. This fabrication methodology is presented initially as a set of materials and processes which are illustrated in analog circuit primitive forms including flexible, thin film capacitors, resistors, and inductors. Three sensing systems addressing specific SHM challenges are developed from this base of components and processes as specific illustrations of the broader fabrication approach. The first system developed is a fully integrated strain sensing system designed to enable the use of multifunctional materials in sensing applications. This is achieved through the development of an optimized fabrication approach applicable to many multifunctional materials. A layer-by-layer (LbL) deposited nanocomposite is incorporated with a lithography process to produce a sensing system. To illustrate the process, a strain sensing platform consisting of a nanocomposite film within an amplified Wheatstone bridge circuit is presented. The study reveals the material process is highly repeatable to produce fully integrated strain sensors with high linearity and sensitivity. The thin film strain sensors are robust and are capable of high strain measurements beyond 3,000 μϵ. The second system developed is an array of resistive distributed strain sensors and an associated algorithm to provide an alternative to electrical impedance tomography for spatial strain sensing. An LbL deposited polymer composite thin film is utilized as the piezoresistive sensing material. An inverse algorithm is presented and utilized for determining the resistance of array elements by electrically stimulating boundary nodes. Two polymer nanocomposite arrays are strain tested under cyclic loading. Both arrays functioned as networks of strain sensors confirming the viability of the approach and computational benefits for SHM. The third system developed is a thin film wireless threshold strain sensor for measuring strain in implanted and embedded applications. The wireless sensing system is comprised of two thin film, inductor-capacitor circuits, one of which included a fuse element. The sensor is fabricated on polyimide with metal layers used to pattern inductive antennas and a strain sensitive parallel plate capacitor. A titanium thin film fuse is designed to fail, or have a large resistance increase, when a strain threshold is exceeded. Three prototype systems are interrogated wirelessly while under increasing tensile strain. One of two sensor resonant peaks disappear at a strain threshold as designed, validating the sensing approach and thin film form for use in SHM systems. The fuse approach provides a platform for various systems and sensing elements. The reference peak remains intact and is used for continuous real-time strain sensing with a sensitivity of 0.5 and a noise floor below 50 microstrain.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144183/1/arburt_1.pd

Power Control Optimization of an Underwater Piezoelectric Energy Harvester

Over the past few years, it has been established that vibration energy harvesters with intentionally designed components can be used for frequency bandwidth enhancement under excitation for sufficiently high vibration amplitudes. Pipelines are often necessary means of transporting important resources such as water, gas, and oil. A self-powered wireless sensor network could be a sustainable alternative for in-pipe monitoring applications. A new control algorithm has been developed and implemented into an underwater energy harvester. Firstly, a computational study of a piezoelectric energy harvester for underwater applications has been studied for using the kinetic energy of water flow at four different Reynolds numbers Re = 3000, 6000, 9000, and 12,000. The device consists of a piezoelectric beam assembled to an oscillating cylinder inside the water of pipes from 2 to 5 inches in diameter. Therefore, unsteady simulations have been performed to study the dynamic forces under different water speeds. Secondly, a new control law strategy based on the computational results has been developed to extract as much energy as possible from the energy harvester. The results show that the harvester can efficiently extract the power from the kinetic energy of the fluid. The maximum power output is 996.25 mu W and corresponds to the case with Re = 12,000.The funding from the Government of the Basque Country and the University of the Basque Country UPV/EHU through the SAIOTEK (S-PE11UN112) and EHU12/26 research programs, respectively, is gratefully acknowledged. The authors are very grateful to SGIker of UPV/EHU and European funding (ERDF and ESF) for providing technical and human

Modelling, simulation and optimisation of a piezoelectric energy harvester

The power generation efficiency of piezoelectric energy harvesters is dependent on the coupling of their resonant frequency with that of the source vibration. The mechanical design of the energy harvester plays an important role in defining the resonant frequency characteristics of the system and therefore in order to maximize power density it is important for a designer to be able to model, simulate and optimise designs to match new target applications. This paper investigates a strategy for the application of soft computing techniques from the field of evolutionary computation towards the design optimisation of piezoelectric energy harvesters that exhibit the targeted resonant frequency response chosen by the designer. The advantages of such evolutionary techniques are their ability to overcome challenges such as multi-modal and discontinuous search spaces which afflict more traditional gradient-based methods. A single case study is demonstrated in this paper, with the coupling of a multi-objective evolutionary algorithm NSGA-II to a multiphysics simulator COMSOL. Experimental results show successful implementation of the schema with all 5 experimental tests producing optimal piezoelectric energy harvester designs that matched the desired frequency response of 250 Hz

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Continuation-Based Pull-In and Lift-Off Simulation Algorithms for Microelectromechanical Devices

The voltages at which microelectromechanical actuators and sensors become unstable, known as pull-in and lift-off voltages, are critical parameters in microelectromechanical systems (MEMS) design. The state-of-the-art MEMS simulators compute these parameters by simply sweeping the voltage, leading to either excessively large computational cost or to convergence failure near the pull-in or lift-off points. This paper proposes to simulate the behavior at pull-in and lift-off employing two continuation-based algorithms. The first algorithm appropriately adapts standard continuation methods, providing a complete set of static solutions. The second algorithm uses continuation to trace two kinds of curves and generates the sweep-up or sweep-down curves, which can provide more intuition for MEMS designers. The algorithms presented in this paper are robust and suitable for general-purpose industrial MEMS designs. Our algorithms have been implemented in a commercial MEMS/integrated circuits codesign tool, and their effectiveness is validated by comparisons against measurement data and the commercial finite-element/boundary-element (FEM/BEM) solver CoventorWare

Design for reliability applied to RF-MEMS devices and circuits issued from different TRL environments

Ces travaux de thèse visent à aborder la fiabilité des composants RF-MEMS (commutateurs en particulier) pendant la phase de conception en utilisant différents approches de procédés de fabrication. Ça veut dire que l'intérêt est focalisé en comment éliminer ou diminuer pendant la conception les effets des mécanismes de défaillance plus importants au lieu d'étudier la physique des mécanismes. La détection des différents mécanismes de défaillance est analysée en utilisant les performances RF du dispositif et le développement d'un circuit équivalent. Cette nouvelle approche permet à l'utilisateur final savoir comment les performances vont évoluer pendant le cycle de vie. La classification des procédés de fabrication a été faite en utilisant le Technology Readiness Level du procédé qui évalue le niveau de maturité de la technologie. L'analyse de différentes approches de R&D est décrite en mettant l'accent sur les différences entre les niveaux dans la classification TRL. Cette thèse montre quelle est la stratégie optimale pour aborder la fiabilité en démarrant avec un procédé très flexible (LAAS-CNRS comme exemple de baisse TRL), en continuant avec une approche composant (CEA-Leti comme moyenne TRL) et en finissant avec un procédé standard co-intégré CMOS-MEMS (IHP comme haute TRL) dont les modifications sont impossibles.This thesis is intended to deal with reliability of RF-MEMS devices (switches, in particular) from a designer point of view using different fabrication process approaches. This means that the focus will be on how to eliminate or alleviate at the design stage the effects of the most relevant failure mechanisms in each case rather than studying the underlying physics of failure. The detection of the different failure mechanisms are investigated using the RF performance of the device and the developed equivalent circuits. This novel approach allows the end-user to infer the evolution of the device performance versus time going one step further in the Design for Reliability in RF-MEMS. The division of the fabrication process has been done using the Technology Readiness Level of the process. It assesses the maturity of the technology prior to incorporating it into a system or subsystem. An analysis of the different R&D approaches will be presented by highlighting the differences between the different levels in the TRL classification. This thesis pretend to show how reliability can be improved regarding the approach of the fabrication process starting from a very flexible one (LAAS-CNRS as example of low-TRL) passing through a component approach (CEA-Leti as example of medium-TRL) and finishing with a standard co-integrated CMOS-MEMS process (IHP example of high TRL)

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