Micromachines2016, 7(9), 149; doi:10.3390/mi7090149 - published 24 August 2016 Show/Hide Abstract
Abstract: The K-band microelectromechanical systems (MEMS) tunable band-pass filter, with a wide-frequency tunable range and miniature size, is able to fulfill the requirements of the multiband satellite communication systems. A novel 21.69–24.36 GHz MEMS tunable band-pass filter is designed, analyzed, fabricated and measured. This paper also designs and analyzes an inductively tuned slow-wave resonator, which consists of the MEMS capacitive switch, the MEMS capacitor and the short metal line. The proposed filter has four different work states by changing the capacitance values of the MEMS switches. Measured results demonstrate that, for all four states, the insertion loss is 2.81, 3.27, 3.65 and 4.03 dB at 24.36, 23.2, 22.24 and 21.69 GHz, respectively. The actuation voltage is 0, 20, 16 and 26 V, respectively. The 3 dB bandwidth of the tunable filter is 5.4%, 6.2%, 5.7% and 5.9%, respectively. This study contributes to the design of miniature millimeter tunable filters with a wide-frequency tunable range.
Micromachines2016, 7(9), 148; doi:10.3390/mi7090148 - published 24 August 2016 Show/Hide Abstract
Abstract: This paper presents a micromachined resonant pressure sensor. The sensor is designed to optimize the sensitivity and reduce the cross-talk between the driving electrodes and sensing electrodes. The relationship between the sensitivity of the sensor and the main design parameters is analyzed both theoretically and numerically. The sensing and driving electrodes are optimized to get both high sensing capacitance and low cross-talk. This sensor is fabricated using a micromachining process based on a silicon-on-insulator (SOI) wafer. An open-loop measurement system and a closed-loop self-oscillation system is employed to measure the characteristics of the sensor. The experiment result shows that the sensor has a pressure sensitivity of about 29 Hz/kPa, a nonlinearity of 0.02%FS, a hysteresis error of 0.05%FS, and a repeatability error of 0.01%FS. The temperature coefficient is less than 2 Hz/°C in the range of −40 to 80 °C and the short-term stability of the sensor is better than 0.005%FS.
Micromachines2016, 7(9), 121; doi:10.3390/mi7090121 - published 23 August 2016 Show/Hide Abstract
Abstract: Gallium nitride (GaN) is an III-V semiconductor with a direct band-gap of . GaN has important potentials in white light-emitting diodes, blue lasers, and field effect transistors because of its super thermal stability and excellent optical properties, playing main roles in future lighting to reduce energy cost and sensors to resist radiations. GaN nanomaterials inherit bulk properties of the compound while possess novel photoelectric properties of nanomaterials. The review focuses on self-assemblies of GaN nanoparticles without templates, growth mechanisms of self-assemblies, and potential applications of the assembled nanostructures on renewable energy.
Micromachines2016, 7(9), 147; doi:10.3390/mi7090147 - published 23 August 2016 Show/Hide Abstract
Abstract: The most common treatment for end-stage renal disease (ESRD) patients is the hemodialysis (HD). For this kind of treatment, the functional vascular access that called arteriovenous fistula (AVF) is done by surgery to connect the vein and artery. Stenosis is considered the major cause of dysfunction of AVF. In this study, a noninvasive approach based on asynchronous analysis of bilateral photoplethysmography (PPG) with error correcting output coding support vector machine one versus rest (ESVM-OVR) for the degree of stenosis (DOS) evaluation is proposed. An artificial neural network (ANN) classifier is also applied to compare the performance with the proposed system. The testing data has been collected from 22 patients at the right and left thumb of the hand. The experimental results indicated that the proposed system could provide positive predictive value (PPV) reaching 91.67% and had higher noise tolerance. The system has the potential for providing diagnostic assistance in a wearable device for evaluation of AVF stenosis.
Micromachines2016, 7(8), 146; doi:10.3390/mi7080146 - published 22 August 2016 Show/Hide Abstract
Abstract: This article describes a new way to explore neuromorphic engineering, the biomimetic artificial neuron using microfluidic techniques. This new device could replace silicon neurons and solve the issues of biocompatibility and power consumption. The biological neuron transmits electrical signals based on ion flow through their plasma membrane. Action potentials are propagated along axons and represent the fundamental electrical signals by which information are transmitted from one place to another in the nervous system. Based on this physiological behavior, we propose a microfluidic structure composed of chambers representing the intra and extracellular environments, connected by channels actuated by Quake valves. These channels are equipped with selective ion permeable membranes to mimic the exchange of chemical species found in the biological neuron. A thick polydimethylsiloxane (PDMS) membrane is used to create the Quake valve membrane. Integrated electrodes are used to measure the potential difference between the intracellular and extracellular environments: the membrane potential.
Micromachines2016, 7(8), 145; doi:10.3390/mi7080145 - published 22 August 2016 Show/Hide Abstract
Abstract: A series of thermoelectric responsive shape memory hydro-epoxy (H-EP) composites filled with different contents of graphene were developed and characterized. Compared with traditional actuation materials, these novel shape memory composites exhibit attractive properties, such as light weight, large deformation, good processability and high response speed, making them good candidates for actuator materials. The effect of graphene content on the shape memory composites was studied in terms of mechanical, dynamic mechanical analysis (DMA), electrical properties, and thermoelectric responsive shape memory test. The results show that when graphene content was 2 wt %, the bend strength of the composite improved by about 47% with a storage modulus larger than other composites. The shape recovery ratio of the composites was about 100%, and the shape recovery speed increased with the increment of graphene content, applied voltage, and temperature. Due to the excellent actuation performance, the graphene/hydro-epoxy composite has potential applications in the actuator in the future.