Propylene epoxidation over Ti/MCM-41 catalysts prepared by chemical vapor deposition

Ti-containing mesoporous catalysts were prepared by chemical vapor deposition (CVD) of TiCl₄ on silica MCM-41 in the 700–900 °C temperature range. These samples were characterized (with XRD, ICP, nitrogen adsorption, FT-IR, ESCA, and TEM) and evaluated for the epoxidation of propylene with two alkyl hydroperoxides. The increase of CVD temperature resulted in the decrease of titanium content, catalyst hydroxyl population, crystallinity, and surface area. Catalyst selectivity to the desired product – propylene oxide – was highly sensitive to the deposition temperature. The best Ti/MCM-41 catalyst was prepared at the temperature of 800 °C, which had the maximum propylene oxide yield of 94.3%.     

正丁醇水溶液通氨气法制备TiO2粉体

以TiCl4为原料,正丁醇和水的混合液为溶剂,通入氨气促使TiCl4水解,制备出不同粒径的TiO2粉体.由X射线衍射、场发射扫描电镜和激光粒度仪对样品进行了表征.研究了温度、pH值对粉体的晶型、形貌和粒径的影响.结果表明:在80 ℃通氨气,3≤pH≤8时,所得TiO2粉体均为锐钛矿和金红石的混相,且pH=3时制得的粉体为60 nm左右的球形颗粒,分散性很好;而pH=6,8时所得的粉体团聚严重;室温(20～30 ℃)下通氨至pH=6也可得到分散性较好的无定型态TiO2粉体,但粉体粒径增大,约170nm左右.     

间溴苯甲醚的合成研究

硝基苯经过溴化、还原、重氮化、甲基化得到间溴苯甲醚,总收率为40%。     

Al2O3─SiC Composites from Aluminosilicate Precursors

Al₂O₃ and SiC composite materials have been produced from mixtures of aluminosilicates (both natural minerals and synthetic) and carbon as precursor materials. These composites are produced by heating a mixture of kaolinite (or synthetic aluminosilicates) and carbon in stoichiometric proportion above 1550°C, so that only Al₂O₃ and SiC remain as the major phases. A similar process has also been used for synthesizing other composite powders having mixtures of Al₂O₃, SiC, TiC, and ZrO₂ in different proportions (all compounds together or selective mixtures of some of them), as desired. The microstructure of hot-pressed dense compacts, produced from these powders, revealed that the SiC phase is distributed very homogeneously, even occasionally within Al₂O₃ grains on a nanosize scale. The homogeneous distribution of SiC particles within the system produced high fracture toughness of the hot-pressed material (K_IC∼ 7.0 MPa · m^1/2) and having Vicker's hardness values greater than 2000 kgf/mm².     

Poly(Vinyl Pyrrolidone), a Dispersant for Non-Aqueous Processing of Silicon Carbide

In this paper, poly(vinyl pyrrolidone) (PVP) was selected as a dispersant for preparation of high concentrated silicon carbide (SiC) slurries in an ethanol (EtOH)/methyl ethylene ketone (MEK) solvent system. The interactions between (1) solvent and powders, (2) the solvent and dispersant, and (3) dispersant and powder were characterized in terms of adsorption and viscosity measurement. It was evidenced that the dispersion of SiC slurries was highly dependent on the solvent composition. Well-stabilized SiC slurries could be obtained using PVP as a dispersant in EtOH/MEK media with the content of EtOH in the 40–50 wt% range. The optimal dosage of PVP as a dispersant was at a PVP/SiC mass ratio of 17 mg/g. Results showed that PVP was an effective dispersant for SiC in EtOH/MEK media.     

羧甲基纤维素阳离子化衍生物的研究现状

羧甲基纤维素阳离子化改性是制备性能优良的天然两性高分子的重要方法之一。文章综述了迄今为止羧甲基纤维素阳离子化改性所用的阳离子单体的主要类型及其接枝的若干主要途径,其中包括自由基型接枝共聚、高分子侧基反应、聚合后功能化等三大类。     

β-甘露聚糖酶理化性质与其最适pH的相关性

为了探究影响GH5家族β-甘露聚糖酶最适pH的各种因素,利用该酶的序列信息,构建了基于氨基酸组成的β-甘露聚糖酶理化性质与其最适pH的相关性模型。结果表明:该酶N端氨基酸序列是影响其最适pH的重要因素,在243个理化性质中有17个呈极显著相关,其中7个呈正相关。优化的转移能量参数相关性最高,为0.78:7个正相关的理化性质中,与螺旋相关的理化性质占3个。优化的转移能量参数和螺旋是影响pH稳定性的最重要的因素。所建立的模型为研究该酶酸碱适应性机理提供了一种简单有效的方法。     

化学吸附式制冷-化学反应热对吸附床的影响

化学吸附制冷中,不同温度下CaCl_2-NH_3会发生2种不同的反应,吸附床的温度不是均匀分布的,所以吸附床内存在2种化学反应。同时化学反应会产生相应的化学反应热,又会反过来影响吸附床的温度。在数值模拟中,化学反应热对吸附床的温度会产生很大的影响,通过在Fluent中的UDF导入有关化学反应的编程,从而模拟出吸附床温度的变化,比较了考虑化学反应热与不考虑化学反应热对吸附床温度分布的影响。     

基于CaO引导的甲烷蒸汽重整化学链燃烧制氢系统

为在重整气中得到高纯H_2和降低尾气CO_2分离成本,建立了基于CaO引导的甲烷蒸汽重整化学链燃烧制氢系统,该系统在重整反应器中加入CaO吸收剂,用以吸收重整器内的CO_2,提高重整气中H_2浓度,形成的CaCO_3固体在煅烧器中受热分解重新生成CaO。利用Aspen Plus进行了过程模拟及热力学分析,并研究主要参数对系统性能的影响,得到优化的操作条件为:CaO循环量/CH_4比为0.5,CH_4(燃料)/CH_4比为0.35,NiO循环量/CH_4比为1.4。CaO循环量/CH_4比从0变化到0.5时,重整气中H_2浓度从0.60增长到0.99;CH_4(燃料)/CH_4比在0.25~0.45区间变化时,重整气中H_2浓度从0.86提高到0.99,产气量增加;NiO循环量/CH_4比在1~1.6区间变化时,重整气中H_2浓度从0.88增长到0.99,系统有效能效率变化较小。     

结合双粒子群和K-means的混合文本聚类算法

传统K-means算法对初始聚类中心选择较敏感, 结果有可能收敛于一般次优解, 为些提出一种结合双粒子群和K-means的混合文本聚类算法。设计了自调整惯性权值策略, 根据最优适应度值的变化率动态调整惯性权值。两子群分别采用基于不同惯性权值策略的粒子群算法进化, 子代间及子代与父代信息交流, 共享最优粒子, 替换最劣粒子, 完成进化, 该算法命名为双粒子群算法。将能平衡全局与局部搜索能力的双粒子群算法与高效的K-means算法结合, 每个粒子是一组聚类中心, 类内离散度之和的倒数是适应度函数, 用K-means算法优化新生粒子, 即为结合双粒子群和K-means的混合文本聚类算法。实验结果表明, 该算法相对于K-means、PSO等文本聚类算法具有更强鲁棒性, 聚类效果也有明显的改善。