基于随机扩散理论的气相色谱分离模拟

色谱分离过程中的粒子扩散问题是色谱动力学研究的基础,深入理解粒子的扩散行为对优化分离操作条件、提升色谱性能和开发新型色谱柱尤为关键.现有的模拟方法多集中于局部过程的热力学研究,而整体的扩散分离过程报道并不多见.为此,该文基于微尺度受限空间内随机扩散的方法,通过动态追踪粒子的运动轨迹,实现粒子在气相色谱开管柱内的扩散全过...     

光色谱分离方法研究

采用几何光学模型对光色谱分离中激光辐射压力与粒子半径之间函数关系进行了描述,对光色谱分离的动态范围进行了讨论。     

气相色谱柱内过程模拟和条件优化软件

各种已有的色谱模拟程序软件多用于描述谱峰的流出状况,对于实际样品在柱内的运动过程则缺乏关注。随着多维色谱技术的发展和色谱教学工作的深入,愈来愈多的人需要定量并形象地了解组分在柱内运动过程状况,特别是它们在气相色谱非等温(或液相色谱非等度)条件下的行为。计算机技术的发展为这一工作的研究提供了有力的工具。     

基于浮点编码的遗传算法优化模拟移动床色谱分离木糖醇母液

开发了一种基于浮点编码遗传算法的模拟移动床色谱优化方法。该优化方法中将归一化的生产强度取最大值作为目标函数,同时将纯度的n次方作为罚函数。运算过程中浮点编码遗传算法的适度值由模拟移动床色谱的稳态模型求得。为了保证遗传算法每一代的个体均满足模拟移动床色谱本身的约束条件,算术杂交和完全非均匀变异被用作演化算子。采用该算法很容易得到模拟移动床色谱分离过程中非线性条件下的最优条件。这种优化算法被应用于木糖醇母液的模拟移动床色谱,结果表明当罚函数指数n值由小到大变化时,可以得到产品纯度由低到高的最优分离条件。进一步     

电色谱塔板高度方程的考察

对电色谱塔板高度方程正确与否进行了验证。对于电色谱塔板高度方程的若干影响因素如色谱柱结构参数、毛细管内半径r0、保留因子k、扩散系数Dm以及脱附速率常数kd对柱效率的影响进行了实验考察,并将实验数据与借助计算机计算的结果加以对比。从而得出结论:我国色谱理论工作者提出的电色谱塔板高度方程成立。由于该方程合理地考虑到各种影响溶质谱带展宽的因素,因此可以为毛细管电色谱过程的柱型设计、条件优化提供理论上的指导。     

分子模型及其在手性识别机理研究上的应用

介绍了近十几年来在色谱手性识别机理研究中的分子模型。在这些模型中,采用量子力学、分子力学和分子动力学等方法计算了手性选择试剂与对映体之间的相互作用,并借助X射线晶体学、核磁共振技术和计算机模拟等技术建立了各种分子模型,研究在手性化合物分离过程中的手性识别机理。     

线性柱色谱分离过程的递推方程

依据非平衡热力学分离理论中的局域平衡假设和流体力学的Lagrangian描述方 法，首次提出了线性柱色谱分离过程中溶质带迁移和扩散的状态递推方程，克服了 以经典动力学为基础的塔板理论不能准确预测时变控制条件下溶质扩散的局限性。 反相色谱梯度洗脱的实验数据支持递推方程的理论预测，与基于塔板理论的预测方 法比较，状态递推方程法更具优越性。状态递推方程还为采用动态优化控制柱分离 过程奠定了基础。     

动态模拟法在酸碱滴定中的应用

本文建立了ＮａＯＨ滴定混合酸过程中〔Ｈ〕随滴定剂Ｖ变化的微分滴定方程，选用龙格－库塔算法求解上述微分方程，从而进行ｐＨ随△Ｖ变化的动态模拟计算。本文将离子的活度系数引入计算过程，因而获得了与实验值吻合的模拟计算结果。     

樟脑分子印迹整体柱的制备及性能评价

利用原位聚合法制备了樟脑分子印迹整体柱作为液相色谱固定相,通过优化制备条件和色谱条件,得到了对模板分子有较高保留性能的整体柱。采用前沿色谱分析法测定柱容量,得到有效结合位点Bt=1.815×102mmol/g和解离常数Kd=9.064 mmol/mL。Van’t Hoff方程得到的热力学参数焓值和熵值,说明了聚合物对樟脑的吸附为熵增过程。等温吸附模型证明在该聚合物表面只存在一种结合位点。     

离子对电色谱法分离机理的理论探讨

离子对电色谱是离子对高效液相色谱与电泳模式的复合体，兼具两种方法的特点；作者基于计量模型的基本假设，并考虑溶质在电色谱过程中的输运机制，通过对溶质在柱过程中涉及的多种平衡过程进行考察，得到了可以说明溶质迁移速率随离子对试剂浓度和各种相互作用之间关系的理论表达式；以中性溶质和简单带电溶质为例，对理论迁移方程进行简化，结果表明带电溶质在离子对电色谱中的迁移过程中同时受色谱机理、离子对作用和电泳分离机理的影响，因此离子对电色谱对样品溶质应有更好的选择性，且适宜于快速分离。     

正常拖尾色谱峰的塔板模型表达式

得到了描述正常拖尾色谱峰的塔板模型表达式,根据这一表达式,正常的色谱流出曲线应是非对称的拖尾峰,而对称的高斯型分布函数是对塔板模型进行近似处理的结果。和扩散模型的色谱流出曲线方程相比,二者在形式上完全相同,因此,尽管塔板模型和扩散模型的机理不同,但它们对于色谱流出曲线的数学描述是完全相同的。     

Modeling of size-exclusion chromatography of electrolytes on non-ionic nanoporous adsorbents

A dynamic model has been developed for chromatographic separation of mixed electrolyte solutions with non-ionic nanoporous adsorbents. The thermodynamic equilibrium condition at the pore entrance is written in terms of mixing, electrostatic and size-exclusion effects. The model is tested against experimental data measured with three binary mixtures on hypercrosslinked polystyrene and nanoporous carbon. The selectivity of the nanoporous adsorbents can be explained by the size-exclusion of the electrolytes and enrichment of both electrolytes in frontal chromatographic runs can be correlated satisfactorily with the proposed model. The model is also used to demonstrate continuous separation in a simulated moving-bed (SMB) system.     

Statistical assessment of solvent mixture models used for separation of biological active compounds

Two mathematical models with seven and six parameters have been created for use as methods for identification of the optimum mobile phase in chromatographic separations. A series of chromatographic response functions were proposed and implemented in order to assess and validate the models. The assessment was performed on a set of androstane isomers. Pearson, Spearman, Kendall tau-a,b,c and Goodman-Kruskal correlation coefficients were used in order to identify and to quantify the link and its nature (quantitative, categorical, semi-quantitative, both quantitative and categorical) between experimental values and the values estimated by the mathematical models. The study revealed that the six parameter model is valid and reliable for five chromatographic response factors (retardation factor, retardation factor ordered ascending by the chromatographic peak, resolution of pairs of compound, resolution matrix of successive chromatographic peaks, and quality factor). Furthermore, the model could be used as an instrument in analysis of the quality of experimental data. The results obtained by applying the model with six parameters for deviations of rank sums suggest that the data of the experiment no. 8 are questionable.     

Chemometric quality control of chromatographic purity

It is common practice in chromatographic purity analysis of pharmaceutical manufacturing processes to assess the quality of peak integration combined by visual investigation of the chromatogram. This traditional method of visual chromatographic comparison is simple, but is very subjective, laborious and seldom very quantitative. For high-purity drugs it would be particularly difficult to detect the occurrence of an unknown impurity co-eluting with the target compound, which is present in excess compared to any impurity. We hypothesize that this can be achieved through Multivariate Statistical Process Control (MSPC) based on principal component analysis (PCA) modeling. In order to obtain the lowest detection limit, different chromatographic data preprocessing methods such as time alignment, baseline correction and scaling are applied. Historical high performance liquid chromatography (HPLC) chromatograms from a biopharmaceutical in-process analysis are used to build a normal operation condition (NOC) PCA model. Chromatograms added simulated 0.1% impurities with varied resolutions are exposed to the NOC model and monitored with MSPC charts. This study demonstrates that MSPC based on PCA applied on chromatographic purity analysis is a powerful tool for monitoring subtle changes in the chromatographic pattern, providing clear diagnostics of subtly deviating chromatograms. The procedure described in this study can be implemented and operated as the HPLC analysis runs according to the process analytical technology (PAT) concept aiming for real-time release.     

Optical resolution of a series of potential cholecystokinin antagonist 4(3H)-quinazolone derivatives by chiral liquid chromatography on alpha1-acid glycoprotein stationary phase

Optical resolution of the enantiomers of new 4(3H)-quinazolone derivatives is investigated using the alpha1-acid glycoprotein chiral stationary phase (Chiral-AGP). Stereoselective separation of the model compounds can be controlled by varying the pH and adding uncharged organic modifiers (acetonitrile and 2-propanol) to the mobile phase. For the majority of quinazolone derivatives, Chiral-AGP is proved to be an excellent enantioselector, because optimized chromatographic conditions allow for the baseline separation of the enantiomers. Separation factors between 1.19 and 1.85 are obtained. The effects of acetonitrile and 2-propanol on the chromatographic behavior of the model compounds are quite different because of their different hydrophobic- and hydrogen-bonding properties. The eluent pH and organic modifier concentration also contributes to the chiral recognition by altering the protein environment. The analysis of the experimental results leads to new information about the chromatographic mechanism on a Chiral-AGP surface.     

用高效液相色谱法预测两油层合采过程中单层的产量分数

 在全油的气相色谱指纹没有显著差异的原油中 ,发现了萘、菲系列化合物在原油中的浓度具有显著差异。提出了预测两油层合采过程中的分层产量分数的新方法。选择萘、菲系列化合物为地化指标 ,用氧化铝 硅胶柱对其预分离 ,再用高效液相色谱法测定其视浓度。通过用人工配制的混合原油进行验证 ,结果表明该方法适用于全油气相色谱差别小的原油 ,预测值与实际值的相对偏差为 8% ,精确度优于全油气相色谱指纹法。     

Studies of Association Effects in Liquid Adsorption Chromatography with Ternary Mobile Phases

Abstract

In this paper a model of chromatographic process, which takes into account molecular association in the mobile phase is discussed. This model is applied to study the association effects in liquid adsorption chromatography with ternary mobile phases. Efects of nature of the eluent and structure of the chromatographed substance on the type of association is also investigated. Association effects in the chromatographic system containing ternary mobile phase can be evaluated by means of equations describing chromatographic process with the binary mobile phases.     

Extraction,separation and quantitative structure–retention relationship modeling of essential oils in three herbs

The essential oils extracted from three kinds of herbs were separated by a 5% phenylmethyl silicone (DB‐5MS) bonded phase fused‐silica capillary column and identified by MS. Seventy‐four of the compounds identified were selected as origin data, and their chemical structure and gas chromatographic retention times (RT) were performed to build a quantitative structure–retention relationship model by genetic algorithm and multiple linear regressions analysis. The predictive ability of the model was verified by internal validation (leave‐one‐out, fivefold, cross‐validation and Y‐scrambling). As for external validation, the model was also applied to predict the gas chromatographic RT of the 14 volatile compounds not used for model development from essential oil of Radix angelicae sinensis. The applicability domain was checked by the leverage approach to verify prediction reliability. The results obtained using several validations indicated that the best quantitative structure–retention relationship model was robust and satisfactory, could provide a feasible and effective tool for predicting the gas chromatographic RT of volatile compounds and could be also applied to help in identifying the compound with the same gas chromatographic RT.