M/(MgO)y(CeO2)1－y(M=Ni、Co、Cu)催化剂的催化甲烷燃烧性能

采用溶胶凝胶法制备了M/(MgO)_y(CeO2)_1－y(M=Ni、Co、Cu)催化剂. 研究了催化剂Ni/(MgO)y(CeO₂)_1－y催化活性与Ce含量的关系, 当y＝0.9时, 催化剂的活性和稳定性最好. 对比研究了(MgO)_0.9(CeO2)_0.1为载体, 负载Ni、Co、Cu活性组分的催化剂催化甲烷燃烧性能. 结果表明, 负载Cu的催化剂活性最好, 但二次评价后催化剂已烧结；负载Ni的催化剂活性与负载Cu的催化剂相差不大, 且稳定性最好, 经1000 ℃焙烧的Ni/(MgO)_0.9(CeO2)_0.1催化剂比表面仍有14.32 m₂•g^－1, 具有较高的催化活性和很好的热稳定性；负载Co的催化剂活性不如前两者, 稳定性居中, 但比表面降低得最少, 抗烧结能力强.     

Principal component analysis of polymer–solvent and filler–solvent interactions by inverse gas chromatography

Polymers (polyethylene, polyurethane), silica and modified silicas (modified with: N-2-aminoethyl-3-aminopropyltrimethoxysilane, 3-aminopropyltriethoxysilane, 3-merkaptopropyltrimethoxysilane, triethoxyoctylsilane) were examined by inverse gas chromatography at four different temperatures: 363, 383, 393 and 403 K. The modifiers of silica were applied at five different concentrations. Small amounts of the following test solutes were injected to achieve the infinite dilution conditions: pentane, hexane, heptane, octane, nonane, dichloromethane, chloroform, carbon tetrachloride, and 1,2-dichloroethane.

The retention times for these test solutes were determined and Flory–Huggins parameters were calculated. Values of these physico-chemical parameters characterizing the examined materials were arranged in a matrix form: in the rows the supports and modifiers were enumerated at different temperatures whereas the columns contained the test solutes. The input matrix was subject to principal component analysis after standardization. Three principal components explain more than 93% of the total variance in the data. Four test solutes (hexane, heptane, chloroform and carbon tetrachloride) carry very similar information. Therefore, it is justified to eliminate any three of them from the series of test solutes. Modifiers, supports and various temperatures were classified and different groups were observed according to the dominant interactions. Type of modifier, its content, and temperature can change and shift the properties from the dominant clusters to the neighboring clusters. Unambiguous separation was observed in cases of silica modified with 5 and 10 parts of triethoxyoctylsilane at all examined temperatures.     

Genetic Algorithm Based Potential Selection in Simultaneous Voltammetric Determination of Isoniazid and Hydrazine by Using Partial Least Squares (PLS) and Artificial Neural Networks (ANNs)

The voltammetric behavior of isoniazid and hydrazine at an overoxidized polypyrrole modified glassy carbon electrode has been investigated. The obtained cyclic voltammograms showed that their oxidation peaks were overlapped and it is difficult to determine them individually from a mixture without separation. To overcome this limitation, a procedure was proposed for resolution of overlapped voltammetric signals from mixtures of isoniazid and hydrazine. In this procedure, genetic algorithm was used for the selection of potentials for partial least squares. A feed forward artificial neural network with back propagation error algorithm was used to process the nonlinear relationship between currents and concentrations of hydrazine and isoniazid. The proposed method was suitable for determination of isoniazid in pharmaceutical tablets and detection of hydrazine impurities in the same samples.     

微量元素与中药有效化学成分的配合物的研究进展

综述了国内中药中微量元素与有机成分配合物的研究进展，并指出了微量元素与有机成分配合物的研制是开发特效新药的新途径。     

主成份分析同时单点pM滴定法研究

本文将主成份分析应用于单点ＰＭ滴定法中，同时测定了多组分金属离子混合物各组分浓度。讨论了方法原理，建立了主成份常数矩阵，对２１个三元、四元混合样进行了测定，得到满意结果。     

树兰花净油化学成份的研究

用气相色谱-质谱-数据系统联用技术以及红外和核磁共振光谱分析了树兰花净油的化学成份。其萜烯部分除已报道过的(王古)(王巴)烯、丁香烯、蛇麻烯、榄香烯之外,还发现有a-橙椒烯、β-橙椒烯、双环榄香烯、β-檀香烯、γ-木罗烯、金合欢烯、α-木罗烯、β-没药烯、β-荜澄茄烯、γ-荜澄茄烯、δ-荜澄茄烯、γ-榄香烯、白菖烯、甜旗烯等倍半萜烯;而含氧部分的主要成份是茉莉酮酸甲酯和蛇麻烯环氧物Ⅱ;此外还发现有蛇麻二烯酮、蛇麻烯环氧物Ⅰ、蛇麻烯-7醇、丁香烯环氧物、T-荜澄茄醇、δ-荜澄茄醇、表-橙椒醇、橙椒醇、芳萜醇等。     

一个基于诊断的稳健主成分分析方法

经典的主成分分析方法易受异常点影响。本文根据该方法的特点，提出一新的诊断方法，将多变量数据中异常剔除后再进行主成分分析，构成有效的稳健主成分分析法。用此法处理二组实际数据，结果令人满意。     

Chemical profiling and classification of illicit heroin by principal component analysis, calculation of inter sample correlation and artificial neural networks

Artificial neural networks (ANNs) were utilised to validate illicit drug classification in the profiling method used at “Institut de Police Scientifique” of the University of Lausanne (IPS). This method established links between samples using a combination of principal component analysis (PCA) and calculation of a correlation value between samples.Heroin seizures sent to the IPS laboratory were analysed using gas chromatography (GC) to separate the major alkaloids present in illicit heroin. Statistical analysis was then performed on 3371 samples. Initially, PCA was performed as a preliminary screen to identify samples of a similar chemical profile. A correlation value was then calculated for each sample previously identified with PCA. This correlation value was used to determine links between drug samples. These links were then recorded in an Ibase^® database. From this database the notion of “chemical class” arises, where samples with similar chemical profiles are grouped together. Currently, about 20 “chemical classes” have been identified.The normalised peak areas of six target compounds were then used to train an ANN to classify each sample into its appropriate class. Four hundred and sixty-eight samples were used as a training data set. Sixty samples were treated as blinds and 370 as non-linked samples. The results show that in 96% of cases the neural network attributed the seizure to the right “chemical class”.The application of a neural network was found to be a useful tool to validate the classification of new drug seizures in existing chemical classes. This tool should be increasingly used in such situations involving profile comparisons and classifications.     

Three-way partial least-squares regression for the simultaneous kinetic-enzymatic determination of xanthine and hypoxanthine in human urine

The performance of three-way principal component analysis and three-way partial least-squares regression when applied to a complex kinetic-enzymatic system is studied, in order to investigate the analytical potential of the combined use of these chemometric technologies for non-selective enzymatic systems. A enzymatic-kinetic procedure for the simultaneous determination of hypoxanthine and xanthine in spiked samples of human urine is proposed. The chemical system involves two consecutive reactions catalyzed by xanthine oxidase (EC 1.17.3.2). This enzyme catalyzes the oxidation of hypoxanthine, first to xanthine and then to uric acid, a competitive inhibitor of the reactions. The influence of uric acid during quantitative determination was considered in the design of the calibration set. The sample and enzyme solution were mixed in a stopped-flow module and the reaction was monitored using a diode array spectrophotometer. The recorded data have an intrinsical three-component structure (samples, time and wavelength). This data array was studied via three-way principal component analysis and was modeled for quantitative purposes using a three-way partial least-squares calibration procedure. Results are compared with those obtained by applying classical bilinear PLS to the previously unfolded data matrix.     

纳米CaMgSi2O6粉体的低温合成与微波介电性能

以硝酸锂、偏钒酸铵、硝酸钙、硝酸镁、正硅酸乙酯为原料，采用溶胶-凝胶法低温合成纳米CaMgSi₂O₆微波介质陶瓷粉体，研究了不同粒径粉体的烧结行为与微波介电性能。结果表明，通过在钙镁硅溶胶中引入锂钒烧结助剂可大大降低陶瓷粉体的晶相合成温度，干凝胶在750 ℃煅烧后可获得主晶相为CaMgSi₂O₆、分散性良好、粒径为78～98 nm的陶瓷粉体，可满足微型片式元器件用超薄陶瓷介质层的制备要求;该粉体在890 ℃烧结后获得致密结构的陶瓷，具有良好的微波介电性能:介电常数为7.68，品质因数为24 542 GHz，频率温度系数为-57.25×10^-6 ℃^-1。