Improved micro-contact resistance model that considers material deformation, electron transport and thin film characteristics

This paper reports on an improved analytic model forpredicting micro-contact resistance needed for designing microelectro-mechanical systems (MEMS) switches. The originalmodel had two primary considerations: 1) contact materialdeformation (i.e. elastic, plastic, or elastic-plastic) and 2) effectivecontact area radius. The model also assumed that individual aspotswere close together and that their interactions weredependent on each other which led to using the single effective aspotcontact area model. This single effective area model wasused to determine specific electron transport regions (i.e. ballistic,quasi-ballistic, or diffusive) by comparing the effective radius andthe mean free path of an electron. Using this model required thatmicro-switch contact materials be deposited, during devicefabrication, with processes ensuring low surface roughness values(i.e. sputtered films). Sputtered thin film electric contacts,however, do not behave like bulk materials and the effects of thinfilm contacts and spreading resistance must be considered. Theimproved micro-contact resistance model accounts for the twoprimary considerations above, as well as, using thin film,sputtered, electric contact

Bi-stable buckled energy harvesters actuated via torque arms.

Vibrational energy harvesters (VEH) are one way to generate electricity. Though the energy quantities are not enough to run desktop computers, they can power remote devices such as temperature, pressure, and accelerometer sensors or power biological implants. New versions of the Bluetooth protocol can even be used with VEH technology to send wireless data. An important aspect of VEH devices is the power output, operating frequency, and bandwidth. This dissertation investigates a novel method of actuating the primary buckled energy harvesting structure using torque arms as a force amplification mechanism. Buckled structures can exhibit snap-through and has the potential to broaden the operating frequency for the VEH. Macro and MEMS size prototypes are fabricated and evaluated via a custom made shaker table. The effect of compliance arms, which pin the center beam with piezoelectric strips, are also evaluated along with damping ratios. ANSYS models evaluating generated power are created for use in future optimization studies. Lastly, high energy orbitals (HEO) are observed in the devices. Results show that buckling lowers and broadens the output power of the new devices. Reverse sweeps drastically increase the operating frequency during snap-through. Rectangular compliance arms made of poly-lactic acid (PLA) generated the most power of all compliance arms tested. HEO performance can be induced by perturbing the system while maintaining the same input force which increases power output

Microelectromechanical Systems and Devices

The advances of microelectromechanical systems (MEMS) and devices have been instrumental in the demonstration of new devices and applications, and even in the creation of new fields of research and development: bioMEMS, actuators, microfluidic devices, RF and optical MEMS. Experience indicates a need for MEMS book covering these materials as well as the most important process steps in bulk micro-machining and modeling. We are very pleased to present this book that contains 18 chapters, written by the experts in the field of MEMS. These chapters are groups into four broad sections of BioMEMS Devices, MEMS characterization and micromachining, RF and Optical MEMS, and MEMS based Actuators. The book starts with the emerging field of bioMEMS, including MEMS coil for retinal prostheses, DNA extraction by micro/bio-fluidics devices and acoustic biosensors. MEMS characterization, micromachining, macromodels, RF and Optical MEMS switches are discussed in next sections. The book concludes with the emphasis on MEMS based actuators

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

\A Ro- bust Node Selection Strategy for Lifetime Extension in Wireless Sensor Networks

Distributed Wireless Sensor Networks (WSNs) consist of energy-constrained sensor nodes that may be deployed in large numbers in order to monitor a given area, track military targets, detect civilian targets or for other purposes. In such densely deployed environments, multiple transmissions can lead to collisions resulting in packet losses and network congestion. This can increase latency and reduce energy efficiency. These networks also feature significant redundancy since nodes close to each other often sense similar data. Therefore, it may be adequate to employ only a subset of the deployed nodes at any given time in the network. In this thesis, node subsets are selected in a manner that coverage and connectivity are consistently achieved. The working subsets are changed after predetermined durations. A framework using concepts from spatial statistics is developed as an approach to selecting the subset of sensor nodes. Proximal nodes negotiate with each other using energy information, to decide which nodes stay working while others go to sleep mode. The algorithm is executed autonomously by the network. The approach presented ensures that the selected subsets while not necessarily exclusive of previous selections covers the region of interest. Simulation results show that the algorithm is robust and retains some level of redundancy. The algorithm shows significant improvement in energy consumption compared with a network with no selection. The selected subset is shown to be able to withstand significant levels of fault in the network. Conclusions regarding the flexibility and application scenarios of the algorithm are drawn and opportunities for future work indicated