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对乙酰氨基酚的合成与生产 总被引:7,自引:0,他引:7
综述了国内外近年来对药物扑热息痛(对乙酰氨基酚)合成与生产方法的研究,主要介绍了二步法、一步法和生化法。提出了无论从经济上还是从环保上考虑,一步催化合成法是当今扑热息痛合成的出路 相似文献
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Liang Xu Lei Su Hongjie Wang Min Niu Lei Zhuang Kang Peng Xingyu Fan Hongfei Gao De Lu 《Journal of the American Ceramic Society》2022,105(8):5490-5500
Pursuing novel thermal barrier–coating materials with lower thermal conductivity and high-temperature stability can simultaneously improve the working efficiency and service temperature of a gas turbine. In this study, a series of high-entropy RE2(Y0.2Yb0.2Nb0.2Ta0.2Ce0.2)2O7 (RE = La, Nd, Sm, Gd, Dy, and Er) oxides were prepared though solid-state reaction. Through tuning the rare-earth cations, an order–disorder transition occurs from certain partially ordered weberite structure (C2221) to disordered defective fluorite structure (Fm m). All the high-entropy RE2(Y0.2Yb0.2Nb0.2Ta0.2Ce0.2)2O7 oxides possess low thermal conductivity in the range of 0.91–1.34 W m−1 K−1 at room temperature, which can be attributed to increased lattice anharmonicity and disorder, resulting in additional phonon scattering. Herein, we proved that the incorporation of heterovalent cations at B-sites in high-entropy A2B2O7 crystals is an effective strategy to reduce the thermal conductivity without compromising the decrease of oxygen vacancy. Moreover, the high-entropy RE2(Y0.2Yb0.2Nb0.2Ta0.2Ce0.2)2O7 oxides show the relatively higher thermal expansion coefficients of 10.3–10.7 × 10−6°C−1 and excellent phase stability at elevated temperatures. 相似文献
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With the rapid development of online learning technology, a huge amount of e-learning materials have been generated which are highly heterogeneous and in various media formats. Besides, e-learning environments are highly dynamic with the ever increasing number of learning resources that are naturally distributed over the network. On the other hand, in the online learning scenario, it is very difficult for users without sufficient background knowledge to choose suitable resources for their learning. In this paper, a hybrid recommender system is proposed to recommend learning items in users’ learning processes. The proposed method consists of two steps: (1) discovering content-related item sets using item-based collaborative filtering (CF), and (2) applying the item sets to sequential pattern mining (SPM) algorithm to filter items according to common learning sequences. The two approaches are combined to recommend potentially useful learning items to guide users in their current learning processes. We also apply the proposed approach to a peer-to-peer learning environment for resource pre-fetching where a central directory of learning items is not available. Experiments are conducted in a centralized and a P2P online learning systems for the evaluation of the proposed method and the results show good performance of it. 相似文献