Flexible Design Techniques for Polysilicon MEMS Process

Inertial Measurement Units (IMUs) using MEMS (Micro Electro Mechanical Systems) sensors, to detect rotation and acceleration, are extremely sensitive to vibration and shock. Because these IMUs are used in aircraft, missiles, and even in gun launched projectiles, the vibration and shock levels can be extremely high. We have been successful in designing isolation systems that protect the MEMS sensors from these harsh environments. These isolation systems attenuate the shock and vibration in frequency ranges that would otherwise degrade IMU performance and even damage the sensors. In designing an isolation system, for an IMU with MEMS devices, the designer must first acquire a good definition of the shock and vibration environment to which the IMU will be exposed. Then the designer must determine the frequencies and levels to which the MEMS devices are sensitive. Finally the designer must have knowledge of IMU properties such as resonant frequencies, mass properties, clock frequencies, etc. By knowing all of this information, and how it affects IMU performance, the designer can determine the proper parameters for the isolation system. A well designed isolation system using these parameters will be capable of protecting the MEMS devices while maintaining IMU performance through out all specified environments.

In this paper, we discuss how finite element analysis (FEA) can be used to simulate certain micro electro mechanical systems (MEMS). The mechanical behavior of many MEMS devices is a direct result of non-mechanical physical phenomena, such as electrostatics, electromagnetics or heat transfer. This coupling of mechanical behavior with other physical effects, combined with considerations associated with their small dimensions, poses significant challenges to the analysis of MEMS. These challenges can be met by FEA software capable of performing multiphysics analysis with no limitations on the dimensions of the objects in a model. With such software at their disposal, engineers can use the results of their simulations to design MEMS devices.

Stress distribution is one of the main factors influencing the reliability of MEMS (Micro Electro Mechanical System) structure. In most cases, MEMS devices work in motion state, the dynamic stress often affects the performances of the MEMS devices. For the first time, dynamic streses were measured by means of Raman spectroscopy and high-frequency modulation technology, the measurement result shows that dynamic stress at a certain point in silicon micro-resonator is in agreement with the analysis of theory.

This research project focuses on production scheduling in MEMS (Microelectromechanical Systems) manufacturing. The MEMS manufacturing process studied in this chapter is based on a commercial SCREAM (single crystal reactive etching and metallization) micro-machining technology. The whole process can be organized into 3 sub-processes, that is, the wafer front-end process, the wafer cap process and the back-end process. Raw wafers are initially released to the two parallel sub-processes, the front-end and wafer cap process, in batches of eighteen wafers. They are processed in these two sub-processes with this batch size concurrently. Each wafer upon completion of all the operations in the front-end process has to be bonded at the bonding machine with a correspondingwafer emerging from thewafer cap process. The bondedwafers are then processed in the back-end process individually instead of in batches. The total processing time for the wafer front-end process is 63.2 hours which is much longer than the total processing time of 14.6 hours for the wafer cap process. Therefore the coordination of the releases of wafers to the front-end process as well as the wafer cap process is an important issue. An ineffective coordination will create longer cycle time and larger WIP (work-in-process). The objective of this study is to develop reasonable scheduling and control policies to reduce cycle time and WIP inventory.

If you've not been involved in MEMS (MicroElectroMechanical Systems) technology or had the cause to use MEMS devices, then you may wonder what all the fuss is about. What are MEMS anyway? What's the difference between MEMS and MST (MicroSystems Technology)? What are the advantages over existing technologies? If you have ever found yourself pondering over such questions, then this book may be for you. As the title suggests, the main aim is to provide an introduction to MEMS by describing the processes and materials available and by using examples of commercially available devices. The intended readership are those technical managers, engineers, scientists and graduate students who are keen to learn about MEMS but have little or no experience of the technology. I was particularly pleased to note that Maluf has dedicated a whole chapter to the important (and often difficult) area of packaging. The first three chapters provide a general overview of the technology. Within the first three pages we are introduced to the MEMS versus MST question, only to discover that the difference depends on where you live! The United States prefer MEMS, while the Europeans use the handle MST. (Note to self: tell colleagues in MEMS group at Southampton). A good account is given of the basic materials used in the technology, including silicon, silicon oxide/nitride/carbide, metals, polymers, quartz and gallium arsenide. The various processes involved in the creation of MEMS devices are also described. A good treatment is given to etching and bonding in addition to the various deposition techniques. It was interesting to note that the author doesn't make a big issue of the differences between bulk and surface micromachined devices; the approach seems to be `here's your toolbag - get on with it'. One of the great strengths of this book is the coverage of commercial MEMS structures. Arising as they have, from essentially a planar technology, MEMS devices are often elaborate three-dimensional creations, and 2D drawings don't do them much justice. I have to say that I was extremely impressed with the many aesthetic isometric views of some of these wonderful structures. Pressure sensors, inkjet print nozzles, mass flow sensors, accelerometers, valves and micromirrors are all given sufficient treatment to describe the fundamental behaviour and design philosophy, but without the mathematical rigour expected for a traditional journal paper. Chapter 5 addresses the promise of the technology as a means of enabling a new range of applications. The concept of using MEMS devices as key elements within complex systems (or even microsystems!) is explored. The so-called `lab-on-a-chip' approach is described, whereby complex analytical systems are integrated onto a single chip together with the associated micropumps and microvalves. The design and fabrication of MEMS devices are important issues by themselves. A key area, often overlooked, is that of packaging. Painstaking modelling and intricate fabrication methodologies can produce resonator structures oscillating at precisely, say, 125 kHz. The device is then mounted in a dual-in-line carrier and the frequency shifts by 10 kHz because of the additional internal stresses produced. Packaging issues can't be decoupled from those of the micromachined components. Many of these issues, such as protective coatings, thermal management, calibration etc, are covered briefly in the final chapter. Overall, I found this book informative and interesting. It has a broad appeal and gives a good insight into this fascinating and exciting subject area. Neil White

Integrated TiC coatings for moving MEMS

We present a comparative computational study of temperature-dependent elastic constants of silicon (Si), silicon carbide (SiC) and diamond as substrates that are commonly used in the manufacture of Micro-Electromechanical Systems (MEMS) devices. Also mentioned is Cd2SnO4, whose ground-state elastic constants were determined just recently for the first time. Si is the dominant substrate used in the manufacture of MEMS devices, owing to its desirable electrical, electronic, thermal and mechanical properties. However, its low hardness, brittleness and inability to work under harsh environment such as high-temperature environment, has limited its use in the manufacture of MEMS like mechanical sensors and bioMEMS. Mechanical sensors are fabricated on SiC and diamond due to their high Young’s moduli as well as high fracture strength, while the bioMEMS are fabricated on polymers. The effect of temperature on the elastic constants of these substrates will help in giving insight into how their performance vary with temperature.

This paper investigates the possibilities of measuring vehicle deceleration using modern devices based on GPS (Global Positioning System) and MEMS (Micro Electro Mechanical System) technologies, with the aim of replacing traditional inertial devices. The experiments were carried out on a passenger vehicle and a construction machine, using three different measuring devices: an inertial decelerometer, a GPS device (Racelogic DriftBox) and a MEMS accelerometer. The measurement results show good mutual agreement between recorded results from devices used for this paper, with an emphasis on the precision and ease of use of modern devices. The conclusion emphasizes the justification of using GPS and MEMS devices in testing the dynamic characteristics of vehicles due to their high frequency of data acquisition, simple processing, absence of the need for calibration, and greater practicality. This research suggests that such devices will be increasingly used in the future to analyse vehicle dynamics.

In this study we describe a novel system for measuring the distribution of inhomogeneous mechanical properties of microelectromechanical system (MEMS) devices. Such inhomogeneous properties are important because they can decrease the reliability of MEMS devices. Our technique involves measuring the variation in the relative position and angle between single molecule markers sprayed on a MEMS device, which indicates the amount of local deformation. The distribution of the deformation on the surface of a MEMS device is calculated from local displacements measured using the system. To simultaneously measure the three-dimensional (3D) position and orientation of the markers, we developed a 3D orientation measurement system that consists of an epifluorescence microscope and a polarization mode converter (PMC). We also detected the 3D displacement and orientation of the torsion bar in a MEMS mirror device.

A variation of local point interpolation method ( vLPIM) for analysis of microelectromechanical systems (MEMS) device

This dissertation explores the feasibility of using integrated optical waveguides to measure the motion of microelectromechanical structures (MEMS). MEMS are a class of silicon devices which are being developed as sensors and actuators. Because these free moving structures are fabricated using processes similar to microfabrication, MEMS devices and traditional electronics can be integrated on the same substrate. This merging of the technologies will allow the miniaturization of large scale mechanical systems. A difficulty with MEMS devices is determining the submicron motion. One method of noninvasive measurement is optical measurement. Research focused on the characterization of one particular MEMS device, a linear comb resonator. Linear comb resonators displace linearly along a single axis when drive with a sinusoidal voltage signal. This research presents how single mode and multimode guided waves have potential to yield significant positional information. Using optical fibers to create a bulk optical metrology probe, the displacement and operating frequency of this device was characterized. Integration of this an optical probe structure with the MEMS devices can create integrated optical metrology (IOM), which is an in-situ method of device characterization and can represent an enabling technology for MEMS. Co-integration of the two technologies can be achieved through either processing or post processing of integrated waveguides with the MEMS devices. The fabrication process for co-integration of polymer optical waveguides has been experimentally defined in this dissertation, however final results indicate guides wave IOM would best be explored through process interruption or hybrid techniques given existing polymer materials. Analysis yields that the co-integration of inorganic waveguide structures first requires optimization of the design of the microprobe layout.

This review article through light on a highly promising & demanding technology, which is set to revolutionize nearly every product category in present era, while discussing the Concept, Design & Development, Fabrication techniques and applications of micro electro-mechanical systems (MEMS) based Devices or systems. Microelectromechanical system discloses outstanding flexibility and adaptability in miniaturization devices followed by their compact dimension, low power consumption, and fine performance. The MEMS devices have numerous and very high potentials of creating a new field of applications for mobile equipment’s with increased flexibility & more reliability. This work deals with research carried out for the development of MEMS based sensors & Actuators and appropriate uses of MEMS. This work carries information’s regarding subsequent commercial and real life applications of MEMS and discusses various recent technological innovations carried out with their advantages & disadvantages. This work also describes the historical development of micro-electromechanical system (MEMS) sensor technology.

There is strong experimental evidence for the existence of strange modes of failure of microelectromechanical systems (MEMS) devices under mechanical shock and impact. Such failures have not been explained with conventional models of MEMS. These failures are characterized by overlaps between moving microstructures and stationary electrodes, which cause electrical shorts. This work presents modeling and simulation of MEMS devices under the combination of shock loads and electrostatic actuation, which sheds light on the influence of these forces on the pull-in instability. Our results indicate that the reported strange failures can be attributed to early dynamic pull-in instability. The results show that the combination of a shock load and an electrostatic actuation makes the instability threshold much lower than the threshold predicted, considering the effect of shock alone or electrostatic actuation alone. In this work, a single-degree-of-freedom model is utilized to investigate the effect of the shock–electrostatic interaction on the response of MEMS devices. Then, a reduced-order model is used to demonstrate the effect of this interaction on MEMS devices employing cantilever and clamped–clamped microbeams. The results of the reduced-order model are verified by comparing with finite-element predictions. It is shown that the shock–electrostatic interaction can be used to design smart MEMS switches triggered at a predetermined level of shock and acceleration.

In-situ vapor-phase lubrication of sidewall MicroElectroMechanical System (MEMS) devices is investigated with 1-pentanol vapor. The 1-pentanol vapor successfully maintains lubricating properties between silicon contacts of MEMS devices. This is attributed to the ability of alcohol to adsorb on the silicon surface and sustain a lubricating layer, which prevents wear of the MEMS surfaces and minimizes friction. In the presence of these vapors, MEMS devices with sliding contacts operated without failure for up to a factor of 1.7 × 104 longer than in dry N2 gas alone, representing a dramatic improvement in operating life. Adhesion and friction were also investigated as a function of alcohol vapor pressure. The adhesive force between microfabricated MEMS sidewall surfaces increases from ∼30 to ∼60 nN as the alcohol vapor pressure is increased from 0 to 20% of saturation, and then only slightly increases to ∼75 nN at 95% of saturation vapor pressure. This increase in force is well within the capabilities of even the lowest force on-chip actuators, such as electrostatic comb drives which can typically generate a few μN of force. The static friction force was found to be independent of alcohol vapor pressure within the uncertainties in the measurement.

Microelectromechanical Systems (MEMS) devices typically need to be designed against a very low failure probability, which is on the order of or lower. Experimental determination of the target strength for such a low failure probability requires testing of tens of thousands of specimens, which can be cost prohibitive for the design process. Therefore, understanding the probabilistic failure of MEMS devices is of paramount importance for design. Currently available probabilistic models for predicting the strength statistics of MEMS structures are based on classical Weibull statistics. Significant advances in experimental techniques for measuring the strength of MEMS devices have produced data that have unambiguously demonstrated that the strength distributions consistently deviate from the Weibull distribution. Such deviations can be explained by the fact that the Weibull distributions are derived based on extreme value statistics, which is inapplicable to MEMS devices where the dimensions of the material microstructure are not negligible compared to the characteristic structural dimensions. This paper presents a robust probabilistic model for strength distribution of polycrystalline silicon (poly‐Si) MEMS structures that could be extended to other brittle materials at the microscale. The overall failure probability of the structure is related to the failure probability of each material element along its sidewalls through a weakest‐link statistical model. The failure statistics of the material element is determined by both the intrinsic random material strength as well as the random stress field induced by the sidewall geometry. Different from the classical Weibull statistics, the present model is designed to account for structures consisting of a finite number of material elements, and it predicts a scale effect on their failure statistics. It is shown that the model agrees well with the measured strength distributions of poly‐Si MEMS specimens of different sizes, and the calibrated mean strength of the material element is consistent with the theoretical strength of silicon. Meanwhile, it is shown that the two‐parameter and three‐parameter Weibull distributions cannot provide optimum and consistent fits of the observed size‐dependent strength distributions, and thus have very limited prediction capability. The present model explicitly relates the strength statistics to the size effect on the mean structural strength, and therefore provides an efficient means of determining the failure statistics of MEMS structures.