This study presents a tiny pressure sensor which is used to measure the Intracranial Pressure (ICP). The sensor is based on the piezoresistive effect. The piezoresistive pressure sensor is simulated and designed by using nonlinear programming optimizing and Finite Element Analysis (FEA) tools. Two kinds of sensor sizes are designed in the case of childhood and adult. The sensors are fabricated by Microelectro Mechanical Systems (MEMS) process. The test results yield sensitivities of 1.033x 10-2 mV/kPa for the childhood type detection and 1.257x 10-2 mV/kPa for the adult detection with sensor chip sizes of 0.40x0.40 mm2 and 0.50x0.50 mm2, respectively. A novel method for measuring ICP is proposed because of the tiny sizes. Furthermore, relative errors for sensitivity of pressure sensors are limited within 4.76%. Minimum Detectable Pressure (MDP) reaches 128.4 Pa in average.
Flexible arrays based on the flexible connection of double layers are demonstrated.Flexible sensor arrays are highly desired for many applications.Conventional flexible electronics are implemented by directly fabricating them on organic flexible substrates such as polyimide or polyethylene terephthalate,or forming on rigid substrates and then transferring them onto elastomeric substrates.For the first time,a novel process method based on trench refilling with polydimethylsiloxane to make flexible arrays is proposed.In this method,the sensors are directly fabricated on islands of the final bulk silicon.The performance of the sensor will not to be effected by bending and stretching operations.A one-dimensional flexible array shows good flexibility.Since the flexibility process is the last fabrication step,this method is compatible with many micro-electro-mechanical system fabrication technologies and has good yield.
An inductorless wideband programmable-gain amplifier (PGA) for 60 GHz wireless transceivers is presented. To attain wideband characteristics, a modified Cherry-Hooper amplifier with a negative capacitive neu- tralization technique is employed as the gain cell while a novel circuit technique for gain adjustment is adopted; this technique can be universally applicable in wideband PGA design and greatly simplifying the design of wideband PGA. By cascading two gain cells and an output buffer stage, the PGA achieves the highest gain of 30 dB with the bandwidth much wider than 3 GHz. The PGA has been integrated into one whole 60 GHz wireless transceiver and implemented in the TSMC 65 nm CMOS process. The measurements on the receiver front-end show that the re- ceiver front-end achieves an 18 dB variable gain range with a 〉 3 GHz bandwidth, which proves the proposed PGA achieves an 18 dB variable gain range with a bandwidth much wider than 3 GHz. The PGA consumes 10.7 mW of power from a 1.2-V supply voltage with a core area of only 0.025 mm2.
A handwriting input system was developed using three collinear ultrasonic transducers. These collinear polyvinylidene fluoride (PVDF) transducers were specially designed for the handwriting input system to give a large writeable area with writing in any direction. Driver and detection circuits were developed for the handwriting system. This handwriting input system based on 2-dimensional position tracing has large writeable area (A4 paper), low drive voltage (5 V), and is independent of the handwriting pad or the pen.
Traditional planar inductors in Radio Frequency (RF) Integrated Circuits (ICs) are plagued by large areas, low quality, and low frequencies. This paper describes a magnetic-based CMOS-compatible RF in- ductor. Magnetic-core inductors with various ferrite-filled structures, spiral structures, and magnetic material permeabilities were simulated to show that this inductor greatly improves the inductance by up to 97% and quality factor by 18.6% over a multi-GHz frequency range. The results indicate that the inductor is a very promising and viable solution to realize miniature, high quality, and high frequency on-chip inductors for high-end RF ICs.
Jing ZhanTianling RenChen YangYi YangLitian LiuAlbert Wang