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71.
Han Yan Gu Yi Chen Lei Li Bing Liu Xiang Ming Chen 《International Journal of Applied Ceramic Technology》2020,17(2):790-796
SrLa[Ga1−x(R0.5Ti0.5)x]O4 (R = Mg, Zn) ceramics were prepared by a standard solid state sintering method. The single-phase ceramics with K2NiF4-type layered perovskite structure and I4/mmm space group were obtained, indicating that SrLa(R0.5Ti0.5) and SrLaGaO4 can form the unlimited solid solutions. With increasing x for R = Mg and Zn, εr increases monotonously, the Qf value first increases and then decreases, while τf increases from a negative to a positive value. The optimized microwave dielectric properties were obtained as following: εr = 23.3, Qf = 89 400 GHz, τf = −0.8 ppm/°C for SrLa[Ga0.6(Mg0.5Ti0.5)0.4]O4 and εr = 23.3, Qf = 76 200 GHz, τf = 0.2 ppm/°C for SrLa[Ga0.7(Zn0.5Ti0.5)0.3]O4, indicating that the present solid solution ceramics are the promising candidates as microwave resonator materials for the telecommunication applications. 相似文献
72.
Yao Dajie Liu Xiaofei Wu Jian 《International Journal of Control, Automation and Systems》2020,18(9):2251-2258
International Journal of Control, Automation and Systems - In this paper, the tracking problem for a class of uncertain nonlinearly parameterized systems with input delay based the adaptive... 相似文献
73.
To minimize the mass and increase the bearing failure load of composite doublelap bolted joints, a three-step optimization strategy including feasible region reduction,
optimization model decoupling and optimization was presented. In feasible region
reduction, the dimensions of the feasible design region were reduced by selecting dominant
design variables from numerous multilevel parameters by sensitivity analyses, and the
feasible regions of variables were reduced by influence mechanism analyses. In model
decoupling, the optimization model with a large number of variables was divided into
various sub-models with fewer variables by variance analysis. In the third step, the
optimization sub-models were solved one by one using a genetic algorithm, and the
modified characteristic curve method was adopted as the failure prediction method. Based
on the proposed optimization method, optimization of a double-lap single-bolt joint was
performed using the ANSYS® code. The results show that the bearing failure load increased
by 13.5% and that the mass decreased by 8.7% compared with those of the initial design of
the joint, which validated the effectiveness of the three-step optimization strategy. 相似文献
75.
76.
Mani Balamurugan Hui‐Yun Jeong Venkata Surya Kumar Choutipalli Jung Sug Hong Hongmin Seo Natarajan Saravanan Jun Ho Jang Kang‐Gyu Lee Yoon Ho Lee Sang Won Im Venkatesan Subramanian Sun Hee Kim Ki Tae Nam 《Small (Weinheim an der Bergstrasse, Germany)》2020,16(25)
The electrochemical reduction of carbon dioxide (CO2) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO2 to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO2 to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO2 in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions. 相似文献
77.
Neural Machine Translation (NMT) is an end-to-end learning approach for
automated translation, overcoming the weaknesses of conventional phrase-based translation
systems. Although NMT based systems have gained their popularity in commercial
translation applications, there is still plenty of room for improvement. Being the most
popular search algorithm in NMT, beam search is vital to the translation result. However,
traditional beam search can produce duplicate or missing translation due to its target
sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural
machine translation improvements based on a novel beam search evaluation function. And
we use reinforcement learning to train a translation evaluation system to select better
candidate words for generating translations. In the experiments, we conducted extensive
experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual
corpora of NiuTrans are used in our experiments. The experiment results prove that the
proposed methods can effectively improve the English to Chinese translation quality. 相似文献
78.
Shuang Shao Yong Liu Chun-Shui Xu Ying-Xuan Xu Bin Wu Xiao-Shu Zeng Xian-Feng Lu Xiang-Jie Yang 《金属学报(英文版)》2015,(1):7-14
The microstructure and mechanical properties of Mg–6Zn–1Y and Mg–6Zn–3Y(wt%) alloys under different cooling rates were investigated. The results show that the second dendrite arm spacing(SDAS) of Mg–6Zn–1Y and Mg–6Zn–3Y is reduced by 32 and 30% with increasing cooling rates(Rc) from 10.2 to 23 K/s, which can be predicted using a empirical model of SDAS=68 R 0:45:45cand SDAS=73 R 0c, respectively. The compressive strength of both alloys increases with increasing the cooling rate, which is attributed to the increase of volume fraction(Vf) of secondary phases under high cooling rate. The interaction of the cooling rate and component with SDAS has been theoretically analyzed using interdependence theory. 相似文献
79.
80.