Effect of laser power density on the electrochromic properties of WO3 films obtained by pulsed laser deposition

Pulsed laser deposition (PLD) was used to prepare tungsten trioxide (WO₃) films on ITO substrates with a varying laser power density of 4.0–5.5 W/cm². XPS indicated that when the laser power density decreased, the peak positions of the W 4f and O 1s orbits shifted slightly to low energy due to the difference in oxygen vacancies. As the laser power density decreased, W⁶⁺ gradually replaced the lattice position of O^2?, increasing oxygen vacancies in the lattice. The transmittance modulated values (ΔT) were over 44% at 830 nm, indicating strong absorption by the WO₃ thin films in the near-infrared ray. The switching time of the WO₃ thin films between bleached states and coloured states decreased as the laser power density increased due to the amorphous structure, morphology, and lower oxygen deficiency at a high power density. The high ΔT and very fast switching time of t_b (1.09 s) and t_c (6.01 s) demonstrated the excellent electrochromic (EC) properties of the WO₃ films prepared by PLD.     

建筑用气密膜相关强度性能试验研究

气密膜是被动房和超低能耗建筑气密性处理的常用材料,由于试验设备及方法等原因,国内对建筑用气密膜性能的试验研究较少,从施工应用角度出发,针对国内外无纺布基气密膜的相关强度性能开展试验研究,为气密膜的工程应用提供参考.     

基于光刀图像的机器人示教纠偏方法

为了解决机器人辅助在线检测系统示教过程中效率低、人为干预多的问题,针对孔类特征,提出一种通过处理光刀图像获取机器人位姿纠正参数的方法。在该方法中,纠偏过程按照将图像光刀线调整为水平方向、将被测特征调整至图像中央、根据不同特征调整最优扫描方向3个步骤进行。根据光刀图像可以求出测量坐标系与被测特征的位姿关系,并得到该位姿与理想测量位姿的偏差。经过坐标变换即可得到在机器人基坐标系下的调整参数。另外,可利用电脑控制机器人运动,从而实现了纠偏过程的自动化。实验结果表明,该方法可将初始的示教位姿修正为理想位姿,且比传统方式效率更高。     

供水管网DMA优化分区设计方案

实施独立计量分区(district metered area,DMA)是辅助供水管网管理和漏损识别的重要手段.图划分算法是进行DMA分区的方法之一,常规图划分算法应用中,存在解空间受限、分区后原水流状态易发生较大改变、形成较多串联分区(对流量计算不利)的缺点.在常规图划分算法基础上进行了改进:粗化阶段按照特定规则匹配、合并非输水干管两端的节点,形成简化的管网拓扑结构;分区阶段得到管网初步分区方案;细化阶段提出基于贪心算法、枚举算法、蒙特卡洛算法的分区调整方法,结合改进的仪表安置方法、水力模拟、优劣解距离法(technique for order preference by similarity to an ideal solution,TOPSIS),对分区方案进行调整.将该方法应用于YX市供水管网,成功进行了分区.     

Constructing magnetically recoverable CdS/CaFe2O4 P–N heterojunctions for enhanced photoelectrochemical properties towards H2 evolution reaction

A novel CdS/CaFe₂O₄ (CS/CFO) heterogeneous p-n junction was created by thermal deposition of CaFe₂O₄ nanoparticles on CdS rods. The CS/CFO hetero-structured photocatalysts exhibited increasingly efficient visible light harvesting compared to the bare CdS. The CS/CFO composites also presented higher photocurrent and slower decay of photoluminescence, suggesting a better separation of the photo-generated electrons and holes. The photocatalytic H₂ evolution quantity on the optimized CS/CFO composite from water in the presence of ethanol was up to 2200 μmol after 3-h visible light illumination, which is more than twice that of the pristine CdS. The chemical interaction between CdS and CaFe₂O₄ was confirmed by the shifts in the XPS peaks, which made it possible for the charge carriers to transfer across the p-n junction interface. This research highlights the importance of forming an interfacial p-n heterojunction between two semiconductors for efficient charge separation and improved photocatalytic performance.     

Effects of (Li0.5Sm0.5)/W co-substitution and sintering temperature on the structure and electrical properties of ultrahigh Curie temperature piezoceramics,Ca0.92(Li0.5Sm0.5)0.08Bi2Nb2-xWxO9

With co-substitution of (Li_0.5Sm_0.5) at A site and W at B site, the electrical properties of modified Ca_0.92(Li_0.5Sm_0.5)_0.08Bi₂Nb_2-xW_xO₉ [(CLS)BN-xW, x = 0, 0.015 and 0.03] piezoceramics with ultrahigh Curie temperature (T_C) of > 930 °C were enhanced dramatically. The increased resistivity induced by the co-substitution ensure them to be polarized under an enough high field. Combined with the increase of spontaneous ferroelectric polarization (P_S), the significant enhancements in the piezoelectric, dielectric and ferroelectric properties can be obtained in the composition x = 0.015. Furthermore, the piezoelectric activity (d₃₃) and bulk resistivity (ρ_b) of (CLS)BN-0.015 W can be further enhanced at an appropriate sintering temperature. This optimum composition sintered at 1170 °C shows ultrahigh T_C of ～948 °C, d₃₃ of ～17.3 pC/N and ρ_b of ～6.9 MΩ cm at 600 °C, which are comparable to those of the reported high-temperature Aurivillius piezoceramics with T_C > 850 °C.     

Effects of ultrafiltration combined with high-pressure processing,ultrasound and heat treatments on the quality of a blueberry–grape–pineapple–cantaloupe juice blend

This study investigated the effect of ultrafiltration (UF) combined with high-pressure processing (HPP) at 550 MPa, 25 °C for 5 min, ultrasound (US) at 520 W, 40 °C for 10 min and heat treatment (HT) at 90 °C for 3 min on the microbial, physicochemical and sensory properties of a blueberry–grape–pineapple–cantaloupe juice blend during 104 days of storage at 4 °C. After UF, the shelf life of the HPP- and US-treated clear juice blends were 104 and 72 days during the storage at 4 °C respectively. HPP, US and HT treatment minimally affected the anthocyanin and total phenol contents, while HPP better maintained the ascorbic acid levels and sensory properties in the clear juice blend during the storage. Therefore, HPP combined with UF was identified as a prospective processing technique in the fruit juice industry.     

Pattern design and optimization of yarn-dyed plaid fabric using isolation niche genetic algorithm and rough set theory

Under the circumstance of perceptual consumption, it is still challenging to grasp consumer's emotions and demands due to the large search space, diversified preferences, and easy fatigue of consumers. To reduce user fatigue and enlarge search space, a novel method was presented to design and optimize the pattern of yarn-dyed plaid fabric using the isolation niche genetic algorithm and rough set theory. Each pattern was encoded as a chromosome based on the real number code. The population was initialized and evolved using INGA to maintain the diversity. The rough set theory was adopted as the fitness function of isolation niche genetic algorithm to extract the consumer's demands. After multiple evolutions, a large set of practical patterns of the yarn-dyed plaid fabric are obtained. Experiments were carried out by 24 testers of different ages and genders. The results prove that the proposed method based on the isolation niche genetic algorithm and rough set theory is feasible and effective, supplying references to the designer.     

Improving accuracy of automatic optical inspection with machine learning

Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.