Boron Nanosheet?Supported Rh Catalysts for Hydrogen Evolution: A New Territory for the Strong Metal?Support Interaction Effect

High-efficiency electrochemical hydrogen evolution reaction (HER) offers a promising strategy to address energy and environmental crisis. Platinum is the most e...     

The Main Progress of Perovskite Solar Cells in 2020–2021

Perovskite solar cells (PSCs) emerging as a promising photovoltaic technology with high efficiency and low manufacturing cost have attracted the attention from ...     

A Predictive Instrument for Sensitive and Expedited Measurement of Ultra-Barrier Permeation

The reliable operation of flexible display devices poses a significant engineering challenge regarding the metrology of high barriers against water vapor. No reliable results have been reported in the range of 10^–6 g∙(m²∙d)⁻¹, and there is no standard ultra-barrier for calibration. To detect trace amount of water vapor permeation through an ultra-barrier with extremely high sensitivity and a greatly reduced test period, a predictive instrument was developed by integrating permeation models into high-sensitivity mass spectrometry measurement based on dynamic accumulation, detection, and evacuation of the permeant. Detection reliability was ensured by means of calibration using a standard polymer sample. After calibration, the lower detection limit for water vapor permeation is in the range of 10^–7 g∙(m²∙d)⁻¹, which satisfies the ultra-barrier requirement. Predictive permeation models were developed and evaluated using experimental data so that the steady-state permeation rate can be forecasted from non-steady-state results, thus enabling effective measurement of ultra-barrier permeation within a significantly shorter test period.     

四川盆西平原区裸土扬尘中Pb、Cd化学形态的生物有效性

为探究四川盆西平原区裸土扬尘中Pb、Cd总质量分数与其生物有效性的规律,在构建的"阳离子型污染物土壤表层运移行为研究系统"内进行模拟起尘试验,对土壤样品进行Pb、Cd模拟污染试验,结果表明:试验条件下,四川盆西平原区裸土扬尘颗粒物中Pb、Cd的总质量分数随着粒径的减小而增大,其中Pb的化学形态以碳酸盐结合态为主(44....     

Urban building roof segmentation from airborne lidar point clouds

This article presents a new approach to segmenting building rooftops from airborne lidar point clouds. A progressive morphological filter technique is first applied for separation between ground and non-ground points. For the non-ground points, a region-growing algorithm based on a plane-fitting technique is used to separate building points from vegetation points. Then, an adaptive Random Sample Consensus (RANSAC) algorithm based on a grid structure is developed to improve the probability of selecting an uncontained sample from the localized sampling. The distance, standard deviation and normal vector are integrated to keep topological consistency among building rooftop patches during building rooftop segmentation. Finally, the remaining points are mapped on to the extracted planes by a post-processing technique to improve the segmentation accuracy. The results for buildings with different roof complexities are presented and evaluated.     

Depth from Refraction Using a Transparent Medium with Unknown Pose and Refractive Index

In this paper, we introduce a novel method for depth acquisition based on refraction of light. A scene is captured directly by a camera and by placing a transparent medium between the scene and the camera. A depth map of the scene is then recovered from the displacements of scene points in the images. Unlike other existing depth from refraction methods, our method does not require prior knowledge of the pose and refractive index of the transparent medium, but instead can recover them directly from the input images. By analyzing the displacements of corresponding scene points in the images, we derive closed form solutions for recovering the pose of the transparent medium and develop an iterative method for estimating the refractive index of the medium. Experimental results on both synthetic and real-world data are presented, which demonstrate the effectiveness of the proposed method.     

Optimization of optical design for developing an LED lens module

In this study, a procedure for optimization of an LED lens module design based on 3 LED light sources was divided into two phases. For preliminary optimization of the dimensions of the LED lens module in Stage I, an optical analysis with orthogonal arrays and TracePro (an optical design package) combined with analysis of variance was conducted to investigate relationships between the multiple optical quality characteristics (viewing angle and average illuminance) and dimension parameters and find the initial optimal parameter combination of the LED lens module. In Stage II, the initial optimal parameter combination determined in Stage I was employed to develop an orthogonal array L₂₅(5⁶) for optical simulation. The experimental data of the orthogonal array were used to train and test the back-propagation neural network to develop an optical quality predictor, which was integrated into the genetic algorithms and the particle swarm optimization in order to find the optimal parameter combination that conformed to optical quality. From the experimental results, the proposed optimization procedure contributes to a precise viewing angle to achieve the goal of optical quality and improved the average illuminance in development of the product. The procedure to optimize the optical design developed in this study can be applied to design all types of LED lens modules and improve the optical design and technology of the LED lens industry.     

Analysis of an in-plane micro-generator with various microcoil shapes

This study presents an analysis of an in-plane micro-generator with various microcoil shapes and multiple aspects of coupling, and reports the fabrication of a prototype micro-generator. It is important to establish analytical solutions for the micro-generator to predict the induced voltage. These analytical solutions can be used to estimate the micro-generator power to reduce the experimental time and the cost. Understanding the physical meanings of the variables can optimize the structure of the micro-electromagnetic generator. This model considers electromagnetism, kinematics, and geometry. The proposed in-plane rotary electromagnetic micro-generator was fabricated using low-temperature co-fired ceramic technology to co-fire the silver microcoils on the ceramic substrate with different shaped coils (e.g., square-shaped, circle-shaped and sector-shaped) both with the printing linewidth and 100 μm spacing of these microcoils. A planar permanent magnet with an outer diameter of 9 mm and a thickness of 700 μm was sintered by Nd/Fe/B. Its residual induction is 1.4 T. The experimental data in this study can be compared with analytical solutions. Analytical results show that the micro-generator with a sector-shaped microcoil generates a maximum effective value of 218.127 mV induced voltage at 1395.34 rad/s. Experimental measurements show a close agreement with these analytical solutions.     

Supply chain management with lean production and RFID application: A case study

This study applies lean production and radio frequency identification (RFID) technologies to improve the efficiency and effectiveness of supply chain management. In this study, a three-tier spare parts supply chain with inefficient transportation, storage and retrieval operations is investigated. Value Stream Mapping (VSM) is used to draw current state mapping and future state mapping (with lean production and RFID) with material, information, and time flows. Preliminary experiments showed that the total operation time can be saved by 81% from current stage to future stage with the integration of RFID and lean. Moreover, the saving in total operation time can be enhanced to 89% with cross docking. In addition, utilizing RFID technology, the cost of labors can be significantly reduced while maintaining current service capacity at the members in the studied supply chain. Return-on-investment (ROI) analysis shows that the proposed method is both effective and feasible.