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71.
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With the development of modern industry,global warming is becoming a challenging issue due to the emissions of large quantities of greenhouse gases,mainly carbon dioxide(CO2).The conversion of CO2to useful compounds is considered as an effective and economic way to solve such a climate problem.Metal-organic frameworks(MOFs)are an emerging class of porous crystalline materials that have shown great potential in the conversion of CO2.The advantages of MOFs in CO 2 conversion lie in their high surface areas,adjustable pore size,and high porosity.More importantly,desirable functional sites can be easily designed and precisely installed to the pore wall of target MOFs by pre-assembly and/or post-synthetic modification(PSM)ways.This review summarizes the recent advances in constructing MOF catalysts for the application in CO2conversion.We believe that the design and synthesis of MOF catalysts for CO2conversion can be a promising way to solve the“greenhouse effect”. 相似文献
73.
Tae Woo Kim Eun‐Jin Oh Ah‐Young Jee Seung Tae Lim Dae Hoon Park Minyung Lee Sang‐Hoon Hyun Prof. Jin‐Ho Choy Prof. Seong‐Ju Hwang Prof. 《Chemistry (Weinheim an der Bergstrasse, Germany)》2009,15(41):10752-10761
A colloidal suspension of exfoliated, layered cobalt oxide nanosheets has been synthesized through the intercalation of quaternary tetramethylammonium ions into protonated lithium cobalt oxide. According to atomic force microscopy, exfoliated nanosheets of layered cobalt oxide show a plateau‐like height profile with nanometer‐level height, underscoring the formation of unilamellar 2D nanosheets. The exfoliation of layered cobalt oxide was cross‐confirmed by X‐ray diffraction, UV/Vis spectroscopy, and transmission electron microscopy. The maintenance of the hexagonal in‐plane structure of the cobalt oxide lattice after the exfoliation process was evidenced by selected‐area electron diffraction and Co K‐edge X‐ray absorption near‐edge structure analysis. The zeta‐potential measurements clearly demonstrated the negative surface charge of cobalt oxide nanosheets. Adopting the nanosheets of layered cobalt oxide as a precursor, we were able to prepare the monodisperse CoO nanocrystals with a particle size of ≈10 nm as well as the heterolayered film composed of cobalt oxide monolayer and polycation. 相似文献
74.
75.
Park BK Jeong S Kim D Moon J Lim S Kim JS 《Journal of colloid and interface science》2007,311(2):417-424
We describe herein the synthesis of metallic copper nanoparticles in the presence of poly(vinylpyrrolidone), employed as a protecting agent, via a polyol method in ambient atmosphere. The obtained copper particles were confirmed by XRD to be crystalline copper with a face-centered cubic (fcc) structure. We observed monodisperse spherical copper nanoparticles with a diameter range 45+/-8 nm. The particle size and its distribution are controlled by varying the synthesis parameters such as the reducing agent concentration, reaction temperature, and precursor injection rate. The precursor injection rate plays an important role in controlling the size of the copper nanoparticles. On the basis of XPS and HRTEM results, we demonstrate that the surface of the copper is surrounded by amorphous CuO and that poly(vinylpyrrolidone) is chemisorbed on the copper surface. 相似文献
76.
A new feruloyl amide derivative, named tribulusamide C, was isolated from the fruits of Tribulus terrestris. Its structure was determined on the basis of spectroscopic analysis including IR, 1-D-, 2-D-NMR and HR-ESI-MS. The structure of tribulusamide C was characterised by a unit of pyrrolidine-2,5-dione, which distinguished it from other lignanamides previously isolated from the fruits of T. terrestris. 相似文献
77.
采用氧化沉淀-浸渍法制备了不同含量Fe掺杂的Fe-Mn/TiO2低温脱硝催化剂,考察了催化剂在80~180 ℃范围内的脱硝能力并通过XRD、BET、TG、H2-TPR、NH3-TPD等测试手段,对催化剂的物理化学性质进行了表征.实验结果表明,Fe的加入并没有改变Mn/TiO2的主要晶相,仍是锐钛矿型的TiO2,MnOx和FeOx均以非晶态结构高度分散于载体表面,而且Fe的加入可以有效地改善催化剂的微观形貌、比表面积及表面酸性位点,从而提高其低温脱硝性能.Fe掺量在Fe/Ti为0.10时催化剂具有最佳性能,在120 ℃时脱硝率可达90;以上. 相似文献
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79.
Mengzhou Bi Zhen Guan Tengjiao Fan Na Zhang Jianhua Wang Guohui Sun Lijiao Zhao Rugang Zhong 《Molecules (Basel, Switzerland)》2022,27(6)
Dual-specific tyrosine phosphorylation regulated kinase 1 (DYRK1A) has been regarded as a potential therapeutic target of neurodegenerative diseases, and considerable progress has been made in the discovery of DYRK1A inhibitors. Identification of pharmacophoric fragments provides valuable information for structure- and fragment-based design of potent and selective DYRK1A inhibitors. In this study, seven machine learning methods along with five molecular fingerprints were employed to develop qualitative classification models of DYRK1A inhibitors, which were evaluated by cross-validation, test set, and external validation set with four performance indicators of predictive classification accuracy (CA), the area under receiver operating characteristic (AUC), Matthews correlation coefficient (MCC), and balanced accuracy (BA). The PubChem fingerprint-support vector machine model (CA = 0.909, AUC = 0.933, MCC = 0.717, BA = 0.855) and PubChem fingerprint along with the artificial neural model (CA = 0.862, AUC = 0.911, MCC = 0.705, BA = 0.870) were considered as the optimal modes for training set and test set, respectively. A hybrid data balancing method SMOTETL, a combination of synthetic minority over-sampling technique (SMOTE) and Tomek link (TL) algorithms, was applied to explore the impact of balanced learning on the performance of models. Based on the frequency analysis and information gain, pharmacophoric fragments related to DYRK1A inhibition were also identified. All the results will provide theoretical supports and clues for the screening and design of novel DYRK1A inhibitors. 相似文献