Signal Power-Insensitive Analog MEMS Tunable Capacitor by Immobilizing the Movable Plates PROJECT TITLE :Signal Power-Insensitive Analog MEMS Tunable Capacitor by Immobilizing the Movable PlatesABSTRACT:This paper presents an very power-insensitive microelectromechanical systems (MEMS) tunable capacitor equipped with immobilization capability in the moving plates when an radio frequency signal is flowing. The proposed tunable capacitor is the same as the traditional metal-insulator-metal capacitor, however the high metal plate is capable of moving laterally also vertically; it moves to the left and right to set the capacitance value by modulating the overlap area between the high and bottom plates (analog tuning and high capacitance tuning ratio are the deserves), and then the top plate is pulled right down to be immobilized ensuing in remarkable robustness to the signal power, also high capacitance value. The proposed tunable capacitor, that was fabricated by metal surface micromachining, showed the tuning ratio of 181% at 2 MHz (470-852 fF) and 194% at one GHz with lateral and vertical actuation voltages beneath fifty V. It conjointly exhibited tiny capacitance change against the radio frequency (RF) signal power; the maximum capacitance variation by the signal power of up to nine W was <;5.five% over the total tuning range, that is the record-high power insensitivity among the analog MEMS tunable capacitors. This glorious power insensitivity is because of the immobilizing capability of the proposed tunable capacitor. The proposed tunable capacitor maintained the set capacitance value with a variation of <;eightpercent over ten million cycles beneath one-W signal (cold switching condition). The planning, modeling, fabrication, and measurements, together with RF characteristics, are all described during this paper. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest 3-D Model-Based Multi-Camera Deployment: A Recursive Convex Optimization Approach Personalized Public Transportation: A Mobility Model and its Application to Melbourne