Spring-Like Ammonium Salt Assisting Stress Release for Low-Temperature Deposited FAPbI3 Films Toward Flexible Photovoltaic Application

The substrates of conventional flexible perovskite solar cells (FPSCs) are thermoplastic polymer material polyethylene naphthalate (PEN), which will deform during high temperature annealing process. In addition, lead iodide (PbI₂) permanently formed and the substrate undergoes reversible deformation from 20 °C to 200 °C and back to 20 °C. Therefore, to balance the substrate supporting capacity and the crystalline quality of narrow band gap α-phase formamidinium lead iodide (α-FAPbI₃), an annealing process of 120 °C for 30 minutes is determined. Additionally, there will also be a large number of gaps and lattice strain at the perovskite grain boundaries during the annealing process as the FAPbI₃ phase transition is accompanied by much lattice shrinkage. As a result, 1,6-hexanediammonium diiodide (HADI) is chosen to passivate the defects and release the stress of perovskite film. Therefore, a recorded 1.4% extended stretch rate of the flexible film is attained. Finally, the champion PCE of 21.14% under AM 1.5G and 31.52% under 1062 lux is achieved after HADI treatment, accompanied by a better long-term and mechanical stability. This study provides annealing process optimization and stress relief strategies for the further development of narrow band gap FPSCs.     

An improved approach to find membership functions and multiple minimum supports in fuzzy data mining

Fuzzy mining approaches have recently been discussed for deriving fuzzy knowledge. Since items may have their own characteristics, different minimum supports and membership functions may be specified for different items. In the past, we proposed a genetic-fuzzy data-mining algorithm for extracting minimum supports and membership functions for items from quantitative transactions. In that paper, minimum supports and membership functions of all items are encoded in a chromosome such that it may be not easy to converge. In this paper, an enhanced approach is proposed, which processes the items in a divide-and-conquer strategy. The approach is called divide-and-conquer genetic-fuzzy mining algorithm for items with Multiple Minimum Supports (DGFMMS), and is designed for finding minimum supports, membership functions, and fuzzy association rules. Possible solutions are evaluated by their requirement satisfaction divided by their suitability of derived membership functions. The proposed GA framework maintains multiple populations, each for one item’s minimum support and membership functions. The final best minimum supports and membership functions in all the populations are then gathered together to be used for mining fuzzy association rules. Experimental results also show the effectiveness of the proposed approach.     

Synthesis,crystal structure,and anti-thermal quenching performance of Lu2Sr(1−x)Al4SiO12:xEu2+ phosphors

With high-temperature solid-state reaction method, a series of Lu₂Sr_(1−x)Al₄SiO₁₂:xEu²⁺ phosphors have been synthesized. With Rietveld refinement method, the crystal structure of Lu₂SrAl₄SiO₁₂ has been refined. Under the excitation of the ultraviolet and violet band light, Lu₂Sr_(1−x)Al₄SiO₁₂:xEu²⁺ emits the Eu²⁺ characteristic blue broadband light. The photoluminescence properties of concentration quenching, emission peak shift, reflectance spectra, and luminescence decay have been investigated. With the structure analyses, the corresponding physical mechanisms have been discussed. With the increased temperature, this phosphor shows well thermal stabilities. For the x_Eu = 0.06, 0.08, and 0.1 phosphors, the strong anti-thermal quenching performance has been observed. The reason for the anti-thermal quenching of this phosphor has been discussed. The trap capture mechanism may be the suitable physical mechanism to explain the anti-thermal quenching of this phosphor. This phosphor shows the potential applications in the white LED lighting fields.     

3D laser trimming technology for regulating embedded thick-film carbon resistors on a random access memory module

This study presents a novel solution for regulating embedded thick-film carbon resistors on random access memory (RAM) modules using 3D laser trimming technology. The embedded passive components, which are printed on a substrate using liquid-polymer ink, are employed due to their rapid response time. The original resistance of such resistors, however, is less than the target value. Hence, a 3D laser trimming technology is proposed for etching thick-film resistors and reaching a target resistance value with online assistance of a four-wire resistance measurement device. A laser beam deflection path with a spiral cycle is manufactured on the printed thick-film to superficially thin the resistor using a wobble-grinding function in a layer-by-layer manner. Resistance material was removed by each laser pulse until the target resistance was obtained. Twelve RAM modules were tested. Experimental results demonstrate that the resistance value of the trimmed resistors was an averaged accredited percentage of 88.54% with a tolerance of 5%. All trimmed resistors with a tolerance of 10% were obtained. Furthermore, 144,000 embedded thick-film carbon resistors on 1800 RAM modules were trimmed in a factory using the proposed scheme. Measurement results indicate that an average accredited rate of 95.67% with tolerances of 5–20% was obtained for industrial applications. Therefore, the proposed technology is a practical and efficient solution for regulating thick-film carbon resistors on RAM modules and other related products.     

Safety Evaluation for Campus Parking Garage Performance Using Fuzzy Logic

Crime has been plaguing parking garages in the United States. At The Ohio State University, (OSU) crime on campus, in general, has decreased in recent years; however, crime in OSU parking garages has remained stable in spite of campus-wide efforts to reduce crime. When assessing and evaluating parking garages, occupants employ experience-based judgment that is subjective and imprecise, yet extremely useful. When designers employ the principles of crime prevention through environmental design, they also use subjective variables. An approach that captures the imprecise information in noncrisp expressions reflecting subjective and experience-based variables is the fuzzy logic concept. This concept allows the use of mathematical operations to manipulate and operate on imprecise information or knowledge. Variables such as garage illumination and wall height were collected, fuzzified, and treated as the knowledge base of a model presented in this paper. In addition, numerous experience-based implication rules were developed and employed to evaluate subjective variables. A computer program was developed to illustrate implementation of the model.     

Full-Vectorial Optical Waveguide Mode Solvers Using Multidomain Pseudospectral Frequency-Domain (PSFD) Formulations

New full-vectorial optical waveguide eigenmode solvers using pseudospectral frequency-domain (PSFD) formulations for optical waveguides with arbitrary step-index profile are presented. Both Legendre and Chebyshev collocation methods are considered in the formulation. By applying Legendre-Lagrange or Chebyshev-Lagrange interpolating polynomials to the approximation of spatial derivatives at collocation points, the Helmholtz equations for the transverse-electric or transverse-magnetic components are converted into a matrix eigenvalue equation which is then solved for the eigenmodes by the shift inverse power method. Suitable multidomain division of the computational domain is arranged to deal with general curved interfaces of the refractive-index profile together with a curvilinear mapping technique for each subdomain so that field continuity conditions can be carefully imposed across the dielectric interfaces, which is essential in achieving high numerical accuracy. The solver is applied to the optical fiber for the assessment of its numerical performance, to the classical benchmark rib waveguide for comparing with existing high-accuracy results, and to the fused fiber structure for demonstrating its robustness in calculating the form birefingence.     

基于预训练模型和多层次信息的代码坏味检测方法

目前已有的代码坏味检测方法仅依赖于代码结构信息和启发式规则, 对嵌入在不同层次代码中的语义信息关注不够, 而且现有的代码坏味检测方法准确率还有进一步提升的空间. 针对该问题, 提出一种基于预训练模型和多层次信息的代码坏味检测方法DeepSmell, 首先采用静态分析工具提取程序中的代码坏味实例和多层次代码度量信息, 并...     

二级可调增压柴油机变海拔热平衡试验

进行二级可调增压柴油机热平衡性能研究,有助于评价发动机在不同工况下的热量分配情况,合理控制发动机热负荷,解决高海拔发动机开锅问题,提高热效率。利用自主设计的柴油机高海拔热平衡试验系统,进行不同模拟海拔(0、3 500、5 500 m)二级可调增压柴油机全负荷热平衡试验,研究了海拔高度对二级可调增压柴油机热平衡性能的影响。结果表明:随海拔升高,发动机热负荷升高,具体表现为高速区域涡前排温增大、1 500 r/min全负荷工况下缸内最高燃烧温度峰值升高且对应曲轴转角减小;随海拔升高,有效功和排气带走热量占总热量百分比均呈下降趋势,发动机冷却液带走热量和余项损失占总热量百分比增加,相较于平原工况,海拔5 500 m时,有效功率和排气散热量占比减小1.8%、16.8%,冷却液带走热量和余项损失占比增加2.9%、15.7%;二级增压技术对柴油机高原性能恢复具有明显效果,5 500 m海拔环境条件下,柴油机中、高转速下的热效率恢复情况明显优于低速工况。     

Actionable high-coherent-utility fuzzy itemset mining

Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from quantitative transaction databases. Since each item has its own utility, utility itemset mining has become increasingly important. However, common problems with existing approaches are that an appropriate minimum support is difficult to determine and that the derived rules usually expose common-sense knowledge, which may not be interesting from a business point of view. This study thus proposes an algorithm for mining high-coherent-utility fuzzy itemsets to overcome problems with the properties of propositional logic. Quantitative transactions are first transformed into fuzzy sets. Then, the utility of each fuzzy itemset is calculated according to the given external utility table. If the value is larger than or equal to the minimum utility ratio, the itemset is considered as a high-utility fuzzy itemset. Finally, contingency tables are calculated and used for checking whether a high-utility fuzzy itemset satisfies four criteria. If so, it is a high-coherent-utility fuzzy itemset. Experiments on the foodmart and simulated datasets are made to show that the derived itemsets by the proposed algorithm not only can reach better profit than selling them separately, but also can provide fewer but more useful utility itemsets for decision-makers.