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In this work, the ultraviolet light-emitting diodes (UV-LEDs) at 380 nm were grown on patterned sapphire substrate (PSS) by atmospheric pressure metal organic chemical vapor deposition (AP-MOCVD). A sputtered AlN nucleation layer was utilized on the PSS to enhance the quality of the epitaxial layer. By using high-resolution X-ray diffraction, the full-width at half-maximum of the rocking curve shows that the UV-LEDs with sputtered AlN nucleation layer had better crystalline quality when compared to conventional GaN nucleation samples. From the scanning electron microscope (SEM) and transmission electron microscopy (TEM) images, it can be observed that the tip and sidewall portion of the pattern was smooth using the sputtered AlN nucleation layer. The threading dislocation densities (TDDs) are reduced from 6×10 7 cm −2 to 2.5×10 7 cm −2 at the interface between the u-GaN layers for conventional and AlN PSS devices, respectively. As a result, a much higher light output power was achieved. The light output power at an injection current of 20 mA was enhanced by 30%. Further photoluminescence (PL) measurement and numerical simulation confirm that this increase of output power can be attributed to the improvement of material quality and light extraction.

Internal quantum efficiency (IQE) of InGaN/GaN UV LEDs with patterned sapphire substrates (PSS) was investigated using electroluminescence (EL) and photoluminescence (PL) methods. The physical mechanisms that affect temperature-dependent EL efficiency as a function of injected carrier density were deduced. In order to reduce the density of non-radiative recombination centers to improve quantum efficiency, improvement of crystal quality and reduction in the number of defects are necessary. PSS LEDs showed better EL characteristics than non-PSS LEDs because of the improved epitaxial quality. Contrary to PL IQE, EL IQE was significantly affected by carrier injection efficiency, especially at low temperature when high bias voltage was applied to the p–n junction.

This study presents design, analysis and experiment of a miniaturized rotary generator in size of 10 times 10 times 2 mm3 and its compact energy harvest circuit chip. The designed generator consists of patterned planar copper coils and a multipolar hard magnet ring made of NdFeB. To perform modeling, a harmonic-like magnetic field model along the circumferential path of each magnetic pole is assumed with the assistance from measured peak magnetic flux densities. This is followed by the application of Faraday's law to predict generated electromotive forces (EMFs) in terms of the relative rotational speed between the magnet ring and coils. The genetic algorithm (GA) is next applied to optimize the critical dimensions of the miniaturized generator. The theoretical model of this power microgenerator is evaluated and compared with experimental results, and it is found that the analytical simulation shows a good agreement with the experimental results. The optimized generator offers 4.5 V and 7.23 mW in root mean square (rms) at 10 000 r/min. With microgenerator successfully fabricated, a novel energy harvest circuit employing Dickson charge pump is designed and fabricated via the 0.35-mum process offered by National Chip Implementation Center (CIC) of Taiwan. This charge pump circuit owns the merit of almost-zero thresholds of employed metal-oxide-semiconductor (MOS) transistors, enabling the conversion of low-power alternating current (ac) signals by the microgenerator to direct current (dc) ones.

The objective of the study is to design and construct an in situ inspection machine that would be used to evaluate the dynamic performance of the small-scaled hydrodynamic journal bearings used often for data-storage devices. To this end, novel design ideas of using a high-stiffness air bearing and suspending the test bearing by the specially-designed fixture frame are first proposed, which are accompanied by the special requirements in the manufacturing precisions for various dimensions and geometry characteristics of the components of the experiment system. The capacitor-type sensors, including two custom-mades are next utilized to measure the motions of the spindle and bearing. Finally, a calculating algorithm for deriving performance parameters of the test bearing are proposed, which is intended primarily to estimate rotor stiffness coefficients, load capacity, and eccentricity ratio to determine if the test bearing meet the dynamic performance expected by the original design.

The objective of this study is to design an intelligent control servo scheme for the three-axis optical pickups employed in the next-generation optical disc drives. The three-axis pickup owns the capability to move the lens holder in three directions of focusing, tracking and tilting, which is required particularly for higher data-density optical disks and precision measuring instruments to annihilate non-zero lens tilting. The intelligent controller utilizes a commercially often-used double phase-lead compensator equipped with the capability of auto-tuning on control parameters. In this way, the model uncertainty of the pickups caused by manufacturing tolerance and the coupling between three different DOFs of the three-axis pickup can be overcome to render desired precision data-reading. In the initial stage of the study, Lagrange’s equations are employed to derive equations of motion for the lens holder. A double-lead controller equipped with a fuzzy logic parameter tuning algorithm is then designed to perform dynamic decoupling and forge control efforts toward the goals of precision tracking, focusing and zero tilting simultaneously. Along with the controller, a genetic algorithm is developed to search the optimal designed parameters of previously designed auto-tuning algorithm. Finally, the experiments are conducted to show the effectiveness of the controller. With validated performance, the designed intelligent controller is ready to be employed for the next-generation optical disc drives.

Spatially-resolved electroluminescence (EL) images in the triple-junction InGaP/InGaAs/Ge solar cell have been investigated to demonstrate the subcell coupling effect. Upon irradiating the infrared light with an energy below bandgap of the active layer in the top subcell, but above that in the middle subcell, the EL of the top subcell quenches. By analysis of EL intensity as a function of irradiation level, it is found that the coupled p-n junction structure and the photovoltaic effect are responsible for the observed EL quenching. With optical coupling and photoswitching effects in the multi-junction diode, a concept of infrared image sensors is proposed.

A novel cone-shaped lens cap for High Brightness Light Emitting Diodes (HB-LEDs) is proposed for improving brightness and high uniformity of the direct LED Backlight Units (BLUs) for large area LCD-TVs. Combining the designed lens cap with red, green and blue (RGB) chips on a Metal Core Printed Circuit Board (MCPCB), the LED module with the proposed cap is able to provide a compact white light source with unique features such as instant color variability and lower power usage, etc [1] [2]. The cone shape of the proposed lens cap is designed to emit only a small portion of light upward along the optical axis of the lens, while most of the light rays to the sides, providing a uniform luminance distribution and the high brightness on the backlight. In addition, a small, local square reflective box is designed and coupled to enclose the proposed LED module[3] [4] [5], the inner surfaces of which are attached with reflective films to increase the level of light mixing in the larger, global reflector box. With the structure of the LED module well designed, the placement of the LED modules in the BLU is next optimized via the method of optimization algorithm (OA). In the process of OA executions, the locations of the LED modules are the design factors to be optimized with chosen enclosure dimensions and number of LEDs to maximize brightness and uniformity of the entire BLU. Moreover, in the OA process, the software TRACEPRO is utilized to compute brightness and uniformity of the BLU with certain combination of the aforementioned design and control parameters considered. With the theoretically-optimized placement of the LED modules in hand, experiments based on a realistic BLU built in the laboratory are conducted to verify the performance of the proposed LED module and associated optimized locations. The results indeed identify the attributes of the BLU, which make it possible to achieve excellent backlight performance using a direct illumination approach from the light source of "Cone-Shaped Lens Cap of LEDs".

We have studied the characteristics of efficiency droop in GaN-based light emitting diodes (LEDs) with different kinds of insertion layers (ILs) between the multiple quantum wells (MQWs) layer and n-GaN layer. By using low-temperature (LT) (780 °C) n-GaN as IL, the efficiency droop behavior can be alleviated from 54% in reference LED to 36% from the maximum value at low injection current to 200 mA, which is much smaller than that of 49% in LED with InGaN/GaN short-period superlattices layer. The polarization field in MQWs is found to be smallest in LED with InGaN/GaN SPS layer. However, the V-shape defect density, about 5.3×108 cm−2, in its MQWs region is much higher than that value of 2.9×108 cm−2 in LED with LT n-GaN layer, which will lead to higher defect-related tunneling leakage of carriers. Therefore, we can mainly assign this alleviation of efficiency droop to the reduction of dislocation density in MQWs region rather than the decrease of polarization field.

This study proposes a new miniaturized autofocusing mechanism and an intelligent autofocusing algorithm with digital images as feedbacks. An actuation scheme for autofocusing is fostered via (1) capturing image by a complementary metal-oxide semiconductor sensor array, (2) evaluating the clearness of images by the well-known method of discrete cosine transformation (DCT), and (3) actuating the lens in the designed mechanism to the best-focusing position estimated by a neural network (NN), assisted by a genetic algorithm (GA).