Dopant‐free hole transport materials (HTMs) are essential for commercialization of perovskite solar cells (PSCs). However, power conversion efficiencies (PCEs) of the state‐of‐the‐art PSCs with small molecule dopant‐free HTMs are below 20%. Herein, a simple dithieno[3,2‐b:2′,3′‐d]pyrrol‐cored small molecule, DTP‐C6Th, is reported as a promising dopant‐free HTM. Compared with commonly used spiro‐OMeTAD, DTP‐C6Th exhibits a similar energy level, a better hole mobility of 4.18 × 10?4 cm2 V?1 s?1, and more efficient hole extraction, enabling efficient and stable PSCs with a dopant‐free HTM. With the addition of an ultrathin poly(methyl methacrylate) passivation layer and properly tuning the composition of the perovskite absorber layer, a champion PCE of 21.04% is achieved, which is the highest value for small molecule dopant‐free HTM based PSCs to date. Additionally, PSCs using the DTP‐C6Th HTM exhibit significantly improved long‐term stability compared with the conventional cells with the metal additive doped spiro‐OMeTAD HTM. Therefore, this work provides a new candidate and effective device engineering strategy for achieving high PCEs with dopant‐free HTMs. 相似文献
The network attack profit graph (NAPG) model and the attack profit path predication algorithm are presentedherein to cover the shortage of considerations in attacker-s subjective factors based on existing network attack pathprediction methods. Firstly, the attack profit is introduced, with the attack profit matrix designed and the attackprofit matrix generation algorithm given accordingly. Secondly, a path profit feasibility analysis algorithm isproposed to analyze the network feasibility of realizing profit of attack path. Finally, an opportunity profit path andan optimal profit path are introduced with the selection algorithm and the prediction algorithm designed for accurateprediction of the path. According to the experimental test, the network attack profit path predication algorithm isapplicable for accurate prediction of the opportunity profit path and the optimal profit path. 相似文献
A wide wavelength range tunable guided-mode resonance filter (GMRF) with high peak efficiencies, narrow linewidths, and low sidebands is experimentally demonstrated. The resonance wavelength can be tuned under TM polarized light illumination by rotating the angle of incidence. The GMRF composed of a one-dimensional grating layer and two waveguide layers on a glass substrate is designed with rigorous coupled-wave analysis. The grating structure of the GMRF is patterned by interference lithography with two ultraviolet laser beams. The reflection colours of fabricated GMRF can be shifted from blue to red by rotating the angle of incidence. The measured full width at half-maximums of the reflection peaks located at 450.6, 500.9, 551.0, 601.1, and 651.3?nm are 3.1, 3.9, 4.3, 3.8, and 4.1?nm, respectively. The corresponding sidebands of measured spectra are below 0.2. Compared with previous experimental studies on tunable structures, the narrow linewidths and low sidebands of the proposed GMRF are remarkably improved. 相似文献
In the process of manufacturing, a large amount of manufacturing data is produced by different departments and different domain. In order to realise data sharing and linkage among supply chains, master data management method has been used. Through master data management, the key data can be shared and distributed uniformly. However, since these cross-domain data form a data network through the association of master data, how to evaluate the effectiveness and rationality of this network becomes the major issue in the proposed method. In this paper, a model of the master data network is built based on the theory of set pair analysis. In order to verify the master data, an evaluation method for the network is proposed. Finally, a case was presented to validate this network model and evaluation method.
本文提出了一种对分布式光纤声传感器的入侵事件分类方法.该方式采用小波包去噪方式对原始信号进行去噪;将去噪后的原始信号进行小波变换,得到原始信号的小波时频图;构建双输入型的卷积神经网络,将滤波后的原始一维信号直接输入到一个三层的1-D CNN中、滤波后得到的二维小波时频图直接输入到一个两层的2-D CNN中;将两种CNN输出的特征输入到支持向量机(SVM),使用SVM对事件进行分类.本文中主要识别3种振动事件:汽车通过、挖掘机挖掘和破路机工作.实验结果表明,所提方式对实际环境中3种振动事件的识别准确率平均可以达到96%,并且识别时间仅为0.61 s. 相似文献