Design of system-on-glass for poly-Si TFT OLEDs using mixed-signals simulation

AMOLEDs (active-matrix organic light emitting diodes) employing poly-Si TFT have been used to integrate peripheral circuits on a glass to reduce the cost through the use of dead space on the glass. The system-on-glass (SOG) development provides enormous challenges to the developers, usually verifying the SOG by transistor-level simulation. IR-drop modeling is needed to reduce the uniformity degradation in the OLED image quality. This paper presents a full panel simulation technique for OLED driver and pixels that is integrated on a glass using the mixed-signals circuit design and the proposed process shows excellent capabilities relating to the capacity and the speed.     

Adhesion and rheological properties of EVA-based hot-melt adhesives

Ethylene vinyl acetate (EVA) copolymers of various melt indexes were blended with aromatic hydrocarbon resin in the molten state, and the thermal and adhesion properties as hot-melt adhesives (HMAs) were investigated. The thermal properties for the EVA blends with aromatic hydrocarbon resin were studied using differential scanning calorimeter, Brookfield viscometer and dynamic mechanical thermal analyzer. Their adhesion strength was also obtained using single lap shear strength. The examination of thermal properties for the blend of EVA copolymers with aromatic hydrocarbon resin over a large temperature range showed that the glass transition temperature was independent of their melt index (MI), but that their heat of fusion decreased with increasing MI of EVA copolymers. Furthermore, the storage and loss moduli of the blends decreased with increasing temperature and MI of EVA copolymers, but the loss tangent (tan δ) of the blends increased. An increase in the MI of EVA copolymers decreased the adhesion strength of the blend at the same test condition.     

Controlled Ag-driven superior rate-capability of Li4Ti5O12 anodes for lithium rechargeable batteries

The morphology and electronic structure of a Li₄Ti₅O₁₂ anode are known to determine its electrical and electrochemical properties in lithium rechargeable batteries. Ag-Li₄Ti₅O₁₂ nanofibers have been rationally designed and synthesized by an electrospinning technique to meet the requirements of one-dimensional (1D) morphology and superior electrical conductivity. Herein, we have found that the 1D Ag-Li₄Ti₅O₁₂ nanofibers show enhanced specific capacity, rate capability, and cycling stability compared to bare Li₄Ti₅O₁₂ nanofibers, due to the Ag nanoparticles (<5 nm), which are mainly distributed at interfaces between Li₄Ti₅O₁₂ primary particles. This structural morphology gives rise to 20% higher rate capability than bare Li₄Ti₅O₁₂ nanofibers by facilitating the charge transfer kinetics. Our findings provide an effective way to improve the electrochemical performance of Li₄Ti₅O₁₂ anodes for lithium rechargeable batteries.      

Investigation of freeze/thaw durability in polymer electrolyte fuel cells

This study aims to investigate the effect of different gas diffusion layers (GDLs) on freeze/thaw condition durability in polymer electrolyte fuel cells (PEFCs). Three kinds of GDLs–cloth, felt and paper type—with similar basic properties except thickness and bending stiffness were used. The changes in the properties and cell performance were investigated from the −30 to 70 °C range of freeze/thaw cycles. The I–V performance degradation was observed to be negligible for the felt GDL whereas the cloth and paper GDLs showed a marked I–V performance loss. No distinctive correlation between the changes in electrochemical properties, such as active metal surface area, hydrogen crossover rates and decreased I–V performance, was observed except an increase in ohmic resistance revealed by ac-impedance spectroscopy. The physical destruction of electrodes was also shown by scanning electron microscope (SEM) analysis.     

Improvement of Interpixel Uniformity in Carbon Nanotube Field Emission Display by Luminance Correction Circuit

Interpixel uniformity is critical to image quality, and is hard to be improved by structural reformation of emissive elements because of nonuniformity in luminance characteristics of subpixels in self-emissive device like the carbon nanotube field emission display (CNT-FED). In this paper, we discuss the improvement of the interpixel uniformity by individually controlling the luminance of all subpixels in a display panel. We propose a prototype CNT-FED with improved interpixel uniformity using luminance correction circuitry. The analysis of interpixel uniformity with the proposed luminance correction circuit shows that the index of interpixel uniformity increases about 8% with only about 10% luminance reduction ratio that is a relatively small penalty compared to the enhancement of the interpixel uniformity. The proposed correction method can also be used to ensure improvement of the interpixel uniformity in large-size CNT-FED panels.     

Online Approach for Spatio-Temporal Trajectory Data Reduction for Portable Devices

As location data are widely available to portable devices, trajectory tracking of moving objects has become an essential technology for most location-based services. To maintain such streaming data of location updates from mobile clients, conventional approaches such as time-based regular location updating and distance-based location updating have been used. However, these methods suffer from the large amount of data, redundant location updates, and large trajectory estimation errors due to the varying speed of moving objects. In this paper, we propose a simple but effcient online trajectory data reduction method for portable devices. To solve the problems of redundancy and large estimation errors, the proposed algorithm computes trajectory errors and finds a recent location update that should be sent to the server to satisfy the user requirements. We evaluate the proposed algorithm with real GPS trajectory data consisting of 17201 trajectories. The intensive simulation results prove that the proposed algorithm always meets the given user requirements and exhibits a data reduction ratio of greater than 87% when the acceptable trajectory error is greater than or equal to 10 meters.     

Recent Advances in Rechargeable Magnesium Battery Technology: A Review of the Field’s Current Status and Prospects

The demand for new energy storage systems to be employed in large-scale electrical energy storage systems (EESs) has grown recently, particularly for green energy storage and grid-supporting applications. Rechargeable Mg batteries are promising candidates for such applications because of their good safety characteristics and raw materials’ abundance. Recent progress in the field is noticeable, but further efforts are required to support the successful implementation of rechargeable Mg batteries. We address progress in the development of rechargeable Mg batteries and problems to be resolved in future research, briefly summarize the most recent advances in the development of rechargeable Mg batteries, from a materials perspective, and cover progress on each of the major components of Mg batteries: the electrolyte, the cathode material, and the anode material. We provide a practical guideline for further development of self-sustainable rechargeable Mg batteries as a future power source.     

Robust Position Control of Assistive Robot for Paraplegics

Paraplegia refers to the paralysis of the lower limbs resulting from the damage to the spinal cord. Thus far, considerable efforts have been devoted to the rehabilitation of paraplegics and the improvement of their quality of life. This study focuses on the position control of the sit-stand mechanism of an assistive robot developed to aid paraplegics in shifting from a sitting to a standing position and vice versa. Two control techniques for the model were proposed: sliding mode control (SMC) and SMC integrated with a sliding perturbation observer (SMCSPO). The control algorithm was designed and implemented in MATLAB/Simulink. The simulation results indicate that the SMC is a nonlinear control; however, because the robot is a highly nonlinear model, which requires a high switching gain, the controller introduces chattering into the system. The SMC has been observed to exhibit inadequate performance when controlling a system with uncertainties. In contrast, the SMCSPO is a robust nonlinear control integrated with a nonlinear compensator, which performs better than the SMC even in the presence of external disturbances.

     

Hybrid agent-based simulation for policy evaluation of solar power generation systems

To encourage the adoption of solar power as well as new technological improvements in solar industry, state and federal governments have employed various kinds of incentives over the past decades, such as rebates, tax return opportunities, and Net Metering credits. At the same time, however, the governments concern regulations to avoid highly steep growth of solar energy without considering necessary supporting structure such as storage components, which will increase the electricity price and threaten the stability of existing transmission systems. The goal of this research is to develop a decision support tool to analyze the effectiveness of various policies (both incentives as well as regulations) on the proper growth rate of distributed photovoltaic (PV) systems avoiding the instability of the transition system or steep rising of the electricity price. To this end, we propose a hybrid two-level simulation modeling framework, which is significantly more detailed than the simplified structures commonly used in most policy evaluations. The lower-level model concerns the calculation of PV system payback period of individual household based on hourly electricity generation (PV) and consumptions, incentive levels, PV module price, and hourly electricity price (grid). The higher-level model, running on a weekly basis for 20 years, concerns the household adoption behaviors of the PV systems influenced by various factors, including payback period, household income, word-of-mouth effect and advertisement effect. Agent-based and system dynamics modeling techniques are leveraged in both levels. The proposed models have been developed for residential areas at two different regions in the US based on real data, which have been used to illustrate the impact of policies in different regions.