化学计量学方法在动力学过程分析中的应用

提出了一种公因子分析的新方法。通过这一方法，对一个动力学体系，我们能够从两个不同的波长范围或反应时间范围的数据阵中获得共同组分的数目和它们的光谱或浓度曲线。将这一方法结合正交投影（OPR）技术，成功地应用于聚苯胺掺杂质子酸反应体系数据阵的解析，获得了这一过程中聚苯胺本征态及掺杂后两个新生结构的光谱和浓度变化曲线。基于解析结果可以推断：聚苯胺质子酸掺杂可能生成PANHn^n （α）、PANHn^a (β）两个不同结构的产物，他们间可相互转化。     

聚苯胺在有机溶剂中掺杂质子酸的In-site UV-Vis光谱及其因子分析法解谱

对聚苯胺在有机溶剂中掺杂质子酸的反应进行了in-situ UV-Vis光谱跟踪,用因子分析法对掺杂反应机理进行了研究.结果表明,聚苯胺在有机溶剂中掺杂质子酸的过程可能存在着两个并行反应:一个是掺杂与脱掺杂的动态平衡过程,在实验条件下反应的平衡常数约为k=5.16(24℃);另一个反应为副反应,生成的产物结构介于本征态与平衡掺杂态之间,很可能是反应过程中形成的包含不同掺杂形态的混合体.     

掺杂质子酸的类型对聚苯胺结构和电导率的影响

采用化学氧化聚合法以苯胺为单体，过硫酸铵为氧化剂，在不同质子酸的水溶液中合成聚苯胺，考察质子酸对聚苯胺电性能影响，并通过傅立叶红外吸收光谱（FTIR）和紫外可见光吸收光谱（UV－vis)研究聚苯胺掺杂前后结构的变化。结果表明，龙质子酸掺杂后聚 胺具有导电性是因为其分子链上电荷离城形成了共轭结构，具有不同质子酸中生成的聚苯胺氧化程度不同；分子链共轭程度与掺杂酸对阴离子大小有关，掺杂质子酸对阴离子越大，聚苯胺分子链共轭程度越大，电导率也就越高。     

导电聚苯胺的合成、结构、性能和应用

概述了中国科学院长春应用化学研究所对导电聚苯胺合成、结构、性能和应用的研究.从合成可溶性的聚苯胺入手,阐明了聚苯胺的若干基本化学和结构问题,提出并证明了掺杂态聚苯胺的结构模型和掺杂机理;除了质子酸掺杂外,发现了聚苯胺的碘氧化掺杂、光助氧化掺杂和K+注入还原掺杂;开发了分别以环氧树脂和聚氨酯为载体的聚苯胺防腐涂料;运用掺杂剂诱导的溶解性,通过合成带聚乙二醇链的膦酸掺杂剂,实现了导电态聚苯胺的水体系加工.其中的聚苯胺树脂及防腐涂料的生产技术,已经完成中试,正在走向产业化.     

聚间甲基苯胺的电子能带结构及其掺杂导电机理的量子化学研究

聚苯胺(Polyaniline,简称PAn)体系作为通用高分子材料已有100多年的历史,但近年来人们发现该体系具有异乎寻常的性质。仅仅经过简单的酸、碱反应,PAn就能从绝缘态变为导电态,且两种状态是可逆的,掺杂剂也只是简单的质子酸、碱,整个过程中体系的电子总数不变,仅发生质子数的增减。     

利用减秩因子分析法同时优化确定化学反应级数和速率常数

通过对反应过程中在线测得的动力学谱-光谱二维数据矩阵进行主成分分析，可确定化学反应过程存在的组分数。提出用优化动力学参数-减秩因子分析法解析二维数据矩阵，对未知动力学模型的复杂反应可同时优化求解第一步反应的级数和速率常数。模拟二维数据验证了该方法的可行性。该方法用于高锰酸钾氧化溴化钠的反应过程中测得的二维数据的解析，结果表明：高锰酸钾的还原过程符合0级反应模型。     

掺杂态聚苯胺链结构的研究

本文利用FTIR、固体高分辨~(13)C-NMR、共振拉曼光谱及紫外-可见光谱等手段,研究了聚苯胺掺杂前后的结构变化,指出质子酸的掺杂使聚苯胺中的醌亚胺单元和苯二胺单元发生部分的氧化还原反应,生成了具有一定电荷分布的共轭体系。     

F-T合成校正综合动力学模型

考虑了烯烃、醇与酸的再吸附及其非本征效应(烯烃、醇与酸在催化剂孔道中的扩散作用、物理吸附及溶解度效应)对产物分布的影响,推导了基于详细反应机理的亚甲基插入的烷基机理F-T合成校正综合动力学模型.利用文献数据对动力学模型进行了回归,获得了与文献报道结果相一致的动力学参数.由校正动力学模型计算的烷烃、烯烃、醇与酸产物分布及烯烃比、醇烃比及酸烃比与实验数据较好地吻合.动力学计算结果表明,在铁锰催化剂上,烷烃、烯烃、醇与酸生成的反应是平行竞争反应,烯烃、醇与酸在催化剂表面的再吸附及二次反应导致产物分布偏离了ASF分布.动力学研究还表明,相同碳数的醇与酸产物在催化剂表面上再吸附及二次反应的机会比相同碳数的烯烃大.通过比较相同碳数的烯烃、醇与酸的分子体积及沸点,指出了在铁锰催化剂上,低碳数的烯烃、醇与酸的再吸附及二次反应对产物分布影响的非本征效应中,烯烃、醇与酸的扩散阻力不是主导效应.     

不同质子酸掺杂对银/聚苯胺纳米复合材料结构和导电性的影响

利用紫外光作为辅助条件,在反胶束体系中采用一步双原位法合成了硝酸(HNO3)、对甲基苯磺酸(TSA)和5-磺基水杨酸(SSA)掺杂的银/聚苯胺(Ag/PANI)纳米复合材料.通过对复合材料进行红外光谱(FTIR)、紫外光谱(UV-Vis)、扫描电镜(SEM)、X射线衍射(XRD)和导电性能的测试,研究了不同质子酸对Ag/PANI纳米复合材料结构、形貌和导电性能的影响.测试结果表明,3种酸掺杂制备的Ag/PANI纳米复合材料均为聚苯胺包覆银粒子的核-壳结构.不同的质子酸掺杂会对Ag/PANI纳米复合材料的电性能有重要影响.在3种酸掺杂的复合材料中,TSA掺杂的复合材料的电导率最佳,为215.14 S·cm-1.     

聚苯胺的质子酸掺杂机制的研究

木文用FT-IR、ESR、XPS等研究了聚苯胺的质子酸掺杂机制。结果表明聚苯胺掺杂时的质子化反应优先发生在分子链中的醌亚胺结构单元的氮原子上,并产生了分子内氧化还原反应而形成阳离子自由基。质子所带的电荷由于共轭作用能较好地离域到邻近苯环及对位氮原子上。     

Determination of rank by augmentation (DRAUG)

Determining the rank of a chemical matrix is the first step in many multivariate, chemometric studies. Rank is defined as the minimum number of linearly independent factors after deletion of factors that contribute to random, nonlinear, uncorrelated errors. Adding a matrix of rank 1 to a data matrix not only increases the rank by one unit but also perturbs the primary factor axes, having little effect on the secondary axes associated with the random errors in the measurements. The primary rank of a data matrix can be determined by comparing the residual variances obtained from principal component analysis (PCA) of the original data matrix to those obtained from an augmented matrix. The ratio of the residual variances between adjacent factor levels represents a Fisher ratio that can be used to distinguish the primary factors (chemical as well as instrumental factors) from the secondary factors (experimental errors). The results gleaned from model studies as well as those from experimental studies are used to illustrate the efficacy of the proposed methodology. The method is independent of the nature of the error distribution. Limitations and precautions are discussed. An algorithm, written in MATLAB format, is included. Copyright © 2011 John Wiley & Sons, Ltd.     

一种判断电化学/化学反应体系热力学自洽性的新方法

介绍了一种判断电化学/化学反应体系热力学自洽性的新方法-“秩法”。结合 实际例子描述了该方法的原理、计算步骤。该方法充分利用矩阵“秩”的概念,由 反应系数矩阵的“秩”直接判断出其中的独立组分数,并且仅当寻找到依赖反应时 才需对有关方程进行求解。因此,“秩法”概念上清晰、直观,且由于可以直接调 用矩阵变换的子程序,程序实现也极为容易。该方法对于电化学、化学及化工反应 过程的模拟将非常有意义。     

Components and coupling in enzyme-catalyzed reactions

Many enzyme-catalyzed reactions involve coupling of two or more reactions that could otherwise be catalyzed separately. When biochemical reactions are coupled, the equilibrium composition is very different from that when the reactions are not coupled. The number of components in a chemical reaction is equal to the number of independent conservation equations for atoms of elements, but the number of components in an enzyme-catalyzed reaction that is coupled is larger than the number of independent conservation equations for atoms of elements. The investigation of these additional conservation equations by use of linear algebra is complicated by the fact that in dilute aqueous solutions, the activity of water is taken to be unity. This causes an incompatibility of conservation matrices and stoichiometric number matrices that can be avoided by use of the further transformed Gibbs energy G' ' that provides the criterion for spontaneous change and equilibrium when the standard transformed Gibbs energy of water is constant. In the most striking example discussed, the enzyme mechanism of a ligase reaction introduces three constraints in addition to conservation of atoms of elements. This is completely unheard of in chemical reaction thermodynamics.     

Rank annihilation factor analysis for multicomponent kinetic‐spectrophotometric determination using difference spectra

In this work rank annihilation factor analysis (RAFA) is used to analyze difference spectra of kinetic‐spectrophotometric data. Annihilation of the contribution of one chemical component from the original data matrix is a general method in RAFA. However, sometimes RAFA is not suitable for studying rank deficient data such as kinetic‐spectrophotometric measurements. On the other hand, in order to apply RAFA for the determination of an analyte in an unknown sample, a standard two‐way matrix of the analyte with rank one should generally be available. This is not usually attainable for kinetic‐spectrophotometric monitoring of complexation reactions. Processes monitored by difference spectroscopy always have the spectrum of the initial stage subtracted from each spectrum in the data matrix. In this work we show that, for kinetic‐spectrophotometric data of complexation reactions, the spectrum of ligand (reactant) itself can be used as initial spectrum for subtraction. The obtained difference matrix of sample and that of analyte of interest will be full‐rank and rank 1, respectively. Therefore the system can be analyzed by RAFA. The proposed method was investigated with simulated data at the first stage. The method was then applied in the analysis of experimental kinetic‐spectrophotometric data of a complexation reactions of Co(II) and Ni(II) with chromogenic reagent 1‐(2‐pyridylazo) 2‐naphthol in order to do multi‐component determination of these ions in various real samples. Copyright © 2009 John Wiley & Sons, Ltd.     

一个新的荧光猝灭动力学方程

从光化学反应动力学模型出发，推导出一个新的荧光猝灭动力学方程：实验结果表明：该方程能够准确地拟合荧光反应的实验数据，可用于定量描述猝灭剂对高分子半透膜内的荧光分子的影响，并能很好地说明荧光猝灭的机理．     

Automatic analysis of mixed spectra : Generalised spectral subtraction applied to electron spin resonance spectroscopy

A new technique is described for estimating the pure component spectra from a set of linearly independent spectra. The process is one of generalised spectral subtraction in which an iterative combination of multivariate linear least-squares analysis and matrix transformation is applied to the input data to give estimates of the number of independent components in the original mixed spectra. This technique is applicable to bipolar data (e.g. from e.p.r. spectra) as well as absorption spectra determined by any spectroscopic technique, provided that the spectra may be reasonably assumed to be an additive mixture of unknown pure components. Numerical model examples are given together with an experimental application to electron spin resonance.     

燃烧反应机理构建的极小反应网络方法 氢氧燃烧

基于化学同时平衡原理, 提出复杂反应体系的极小反应网络方法(MRN), 在指定中间物种数目条件下, 构建反应步数最小的详细燃烧反应机理. 确定了8个物种的氢氧燃烧的6个独立反应, 对缺乏动力学参数的独立反应进行组合替代, 反应速率常数采用Arrhenius双参数形式. 采用构建的9步反应氢氧燃烧机理(MRN-C0)进行了点火延迟时间和层流火焰速度的模拟.     

典型燃料点火延迟时间的一阶和二阶局部和全局敏感度分析

Sensitivity analysis is an important tool in model validation and evaluation that has been employed extensively in the analysis of chemical kinetic models of combustion processes. The input parameters of a chemical kinetic model are always associated with some uncertainties, and the effects of these uncertainties on the predicted combustion properties can be determined through sensitivity analysis. In this work, first- and second-order global and local sensitivity coefficients of ignition delay time with respect to the scaling factor for reaction rate constants in chemical kinetic mechanisms for combustion of H₂, methane, n-butane, and n-heptane are examined. In the sensitivity analysis performed here, the output of the model is taken to be natural logarithm of ignition delay time and the input parameters are the natural logarithms of the factors that scale the reaction rate constants. The output of the model is expressed as a polynomial function of the input parameters, with up to coupling between two input parameters in the present sensitivity analysis. This polynomial function is determined by varying one or two input parameters, and allows the determination of both local and global sensitivity coefficients. The order of the polynomial function in the present work is four, and the factor that scales the reaction rate constant is in the range from 1/e to e, where e is the base of the natural logarithm. A relatively small number of sample runs are required in this approach compared to the global sensitivity analysis based on the highly dimensional model representation method, which utilizes random sampling of input (RS-HDMR). In RS-HDMR, sensitivity coefficients are determined only for the rate constants of a limited number of reactions; the present approach, by contrast, affords sensitivity coefficients for a larger number of reactions. Reactions and reaction pairs with the largest sensitivity coefficients are listed for ignition delay times of four typical fuels. Global sensitivity coefficients are always positive, while local sensitivity coefficients can be either positive or negative. A negative local sensitivity coefficient indicates that the reaction promotes ignition, while a positive local sensitivity coefficient suggests that the reaction actually suppresses ignition. Our results show that important reactions or reaction pairs identified by global sensitivity analysis are usually rather similar to those based on local sensitivity analysis. This finding can probably be attributed to the fact that the values of input parameters are within a rather small range in the sensitivity analysis, and nonlinear effects for such a small range of parameters are negligible. It is possible to determine global sensitivity coefficients by varying the input parameters over a larger range using the present approach. Such analysis shows that correlation effects between an important reaction and a minor reaction can have relatively sizable second-order sensitivity coefficient in some cases. On the other hand, first-order global sensitivity coefficients in the present approach will be affected by coupling between two reactions, and some results of the first-order global sensitivity analysis will be different from those determined by local sensitivity analysis or global sensitivity analysis under conditions where the correlation effects of two reactions are neglected. The present sensitivity analysis approach provides valuable information on important reactions as well as correlated effects of two reactions on the combustion characteristics of a chemical kinetic mechanism. In addition, the analysis can also be employed to aid global sensitivity analysis using RS-HDMR, where global sensitivity coefficients are determined more reliably.     

Mechanism reduction of chemical reaction based on sensitivity analysis: development and testing of some new procedure

This paper proposes a procedure for simplifying the mathematical model of a chemical reaction by reducing the number of steps and species in the reaction scheme. This procedure is based on the sensitivity analysis of the model functional to the change in the model parameters. The application of this procedure makes it possible to accelerate and improve the construction of mathematical models for chemical reactions, as this does not require the calculation of sensitivity coefficients at various time points or sensitivity matrix analysis. This scheme was predicted the same behavior of the main reaction components as the detailed reaction scheme but includes much fewer steps. The efficiency of using this procedure was demonstrated by comparative results of modeling of formaldehyde oxidation and hydrogen oxidation in terms of detailed and reduced schemes. The sensitivity analysis was performed by Sobol’s method.