响应曲面法用于高效液相色谱优化分离磺胺的研究

通过响应曲面法对高效液相色谱分离磺胺的优化过程进行了研究,分别考察了分离的3个主要因素(柱温、流动相配比、流速)对最小分离度与分离时间的影响,建立了3个因素与最小分离度和最大保留时间的目标函数,从响应曲面图可优化预测因素水平范围内的最佳分离条件.在选定优化条件下:柱温为20℃,乙腈的体积分数19%,流速1.5 mL/min,8种磺胺组分可在8 min内达到基线分离.     

纤维素酶水解动力学的人工神经网络模型研究

酶作用机制的模糊以及影响异相体系因素的大量存在, 使得纤维素水解的酶催化过程高度复杂, 很难为之建立理论模型. 采用非理论模型人工神经网络模拟和预测了纤维素酶水解反应, 并与常用的响应面模型进行了比较. 选取加酶量 X1, 底物浓度 X2 和反应时间 X3 作为自变量, 还原糖浓度 Y1 和原料转化率 Y2 作为响应值. 结果表明, 人工神经网络模型比响应面模型更适合作为研究纤维素酶水解的动力学工具. 在模拟过程中, 除中心试验点外, 只有 1 个试验点上人工神经网络模拟值 Y2 产生的误差大于响应面模型. 在预测过程中, 人工神经网络模型的预测值都比响应面模型更接近实验值.     

超声萃取-响应面法优化淡竹叶多糖提取方法研究

利用超声辅助萃取—响应面法提取淡竹叶多糖工艺进行研究。在单因素试验基础上,采用五因素三水平响应面分析法,使用中心组合(Box-Benhnken)试验设计原理得到二次线性回归方程,以多糖产率为响应面值作响应面图,确定超声提取淡竹叶多糖最佳工艺条件为:功率200W,温度50℃,液料比35,超声时间30min,提取次数2次,多糖产率为3.42%。验证实验表明,所得模型方程能较好地预测实验结果,拟合度较好。     

基于响应面法的螺旋藻多肽制备工艺的研究

应用响应面分析法优化木瓜蛋白酶酶解制备螺旋藻多肽的工艺条件。根据中心组合试验设计的原理,在单因素试验的基础上,以多肽得率为响应值,利用响应面法对影响螺旋藻蛋白酶解反应的各种影响因素如温度、pH、酶解时间和加酶量进行了系统研究,得到最佳工艺条件为:反应温度55℃、pH值7、酶底比1.6%、酶解2 h,制得多肽含量得率可达20.61%,与模型预测的肽含量21.25%较接近。     

响应面法优化硅藻土负载纳米零价铁去除水中Cr(Ⅵ)

近年来,纳米零价铁(Nanoscale zerovalent iron, NZVI)因高还原性、高比表面积等优点被广泛应用于去除水中Cr(Ⅵ)的研究。本文采用壳聚糖改性后的硅藻土(CDt)对NZVI进行负载制备了硅藻土负载型纳米零价铁(NZVI-CDt),并对其去除水中Cr(Ⅵ)的条件进行了响应面法优化。以负载比(CDt与NZVI的质量比)、温度、反应时间以及反应溶液pH值为4个响应因素,以水中Cr(Ⅵ)的去除率为响应值进行了四因素三水平的响应面实验设计(Box-Behnken Design, BBD),建立了响应面模型。分析结果表明：模型在整个回归区域内拟合度好,4个因素对Cr(Ⅵ)去除率的影响是显著的(F值为146.83),影响顺序为溶液p H值>负载比>反应时间>温度。通过模型优化得到最佳去除条件为：负载比3∶1,温度30℃,反应时间35 min,pH=4,且预测的Cr(Ⅵ)最高去除率为97.81%。通过3组平行实验对模型的预测结果进行验证,得到预测值高于实际值且绝对误差为1.93%,说明预测值与实际值的拟合度较好。通过该研究优化了NZVI-CDt去除水中Cr(...     

多工作模式液相色谱电化学检测系统Ⅱ．单工作电极检测

从理论上导出了薄层池的电极响应电流方程式。电极响应与流动相流速的关系为i_p∝u~(0.332),与理论预测基本吻合。电极响应与池通道厚度有关,池通道越薄,电极响应越大。单电极薄层池工作方式用于分离和检测止痛药类化合物,分离效果好,灵敏度高,m-APAP、SAm和Phen的检测限分别为1ng,4ng和4ng。     

主成分-BP算法在近红外光谱法纸浆卡伯值测量中的应用研究

提出采用主成分-BP算法建立纸浆卡伯值近红外光谱法在线测量模型。结果表明,这种算法由于既考虑到了近红外光谱响应的非线性因素,又可防止BP算法在建模时出现“过拟合”的现象,利用该算法建立的纸浆卡伯值测量模型与一元回归,多元回归和主成分回归等线性方法相比,具有更高的预测精度。     

多工作模式液相色谱电化学检测系统Ⅱ．单工作电极检测

 ]从理论上导出了薄层池的电极响应电流方程式。电极响应与流动相流速的关系为ip∝u0.332，与理论预测基本吻合。电极响应与池通道厚度有关，池通道越薄，电极响应越大。单电极薄层池工作方式用于分离和检测止痛药类化合物，分离效果好，灵敏度高，m-APAPSAm和Phen的检测限分别为1ng，4ng和4ng。     

正交设计与响应面优化玄参黄酮提取工艺研究

以玄参总黄酮提取率为考察指标,在单因素实验分析的基础上,采用正交设计和响应面法对比研究不同溶剂与溶剂体积分数、微波功率、提取时间及液固比等因素对玄参总黄酮提取的影响.2种实验优化方法所得玄参总黄酮的最佳提取工艺条件:固定微波功率值为500W;乙醇体积分数为60%或60.37%;提取时间为10或11.17min;液固比30∶1或31.39∶1m L/g,验证实验总黄酮提取率为1.107%~1.192%.2种优化方法所得结论基本一致,正交设计实验次数少,响应面法更精确,预测能力更强,适用范围更广.     

热解吸-气相色谱法检测空气中邻氯化苯亚甲基丙二腈

运用热解吸-气相色谱法对空气中邻氯化苯亚甲基丙二腈的检测方法进行了研究.采用中心复合设计法优化了邻氯化苯亚甲基丙二腈的热解吸参数,通过方差分析找出影响响应的显著因素,最小二乘法得到二次多项式回归方程预测模型,并利用响应曲面法推导出热解吸参数的最优条件,试验证明预测的准确性较好.同时模拟了空气中样品的测定,测得值为115,646 ng,回收率分别为77%和86%.     

Mitigating model deficiency in three-way data analysis by the combination of background constraining and iterative correcting techniques

PARAFAC is a popular model for trilinear data analysis in analytical chemistry. The prerequisite for the successful application of PARAFAC in analytical chemistry is that the three-way data array should follow a trilinear model, which is always violated by the presence of deviations such as Rayleigh scattering in fluorescence spectroscopy. In order to mitigate the influence of model deviations, background constraining and iterative correcting techniques are advocated in this contribution. The method established on these two techniques can nearly eliminate the effect of model deviation on the chemical loading parameters estimated. Compared with other methods for mitigating model deviations, the proposed method requires no prior knowledge about the chemical loading parameters. It is also unnecessary to assign weights to data entities as the weighted PARAFAC of Anderson does. Its implementation is comparable to PARAFAC-ALS and can be programmed to be completely automatic. Its performance has been demonstrated by fluorescent and chromatographic experiments.     

光谱多元分析的校正模型检验及干扰物的检出

提出了一种在校正模型不确定时分析体系的光谱多元分析方法,首先构造投影阵以检验校正模型的合理性,通过检验可以发现分析体系是否含有其它不纯物,继用不纯物在投影空间中的矢量与可能存在物质的投影光谱进行检索比较,检出不纯物并测出各组份含量.将此法应用于3个分析体系,获得满意的结果.     

A Matrix Based Indexing HDMR method for multivariate data modelling

Modelling multivariate data of real life problems from engineering, chemistry, physics, mathematics or other related sciences, in which function values are known only at arbitrarily distributed points of the problem domain, is an important and complicated issue since there exist mathematical and computational complexities in the analytical structure construction process coming from the multivariance. The Plain High Dimensional Model Representation (HDMR) method expresses a multivariate problem in terms of less-variate problems. In this work, a Matrix Based Indexing HDMR method is developed to make the Plain HDMR philosophy employable for the multivariate data partitioning process. This new method will have the ability of dealing with less-variate data sets by partitioning the given data set into univariate, bivariate and trivariate data sets. Interpolating these partitioned data sets will construct an approximate analytical structure as the model of the given multivariate data modelling problem.     

近红外光谱法分析格列齐特片

应用化学计量法处理光谱数据,用偏最小二乘法建立格列齐特片的近红外分析模型。通过光谱预处理和模型的逐步优化最终确定定量分析模型的相关系数为0.991,交叉验证均方差(RMSECV)为0.641,预测均方根误差(RMSEP)为0.980,主因子数为4。选取15个验证样品对模型进行检验,检测结果相对误差在-2.04%～3.52%之间。     

A software package for the evaluation of peak parameters in an analytical signal based on a non-linear regression method

Computer-based data handling of analytical signals to extract commonly used analytical parameters often produces poor results if the signals are affected by noise and a drifting baseline. Only a minor part of the information present in the signal is used for correction. A computer package is presented, in which the total information of the signal is used to give accurate evaluation of analytical parameters. The program uses a non-linear regression method to deconvolute analytical signals into a number of peaks and a baseline. To describe the peak shape any mathematical model can be used. In the computer package, a Gaussian curve-related model is used, with variable asymmetry. The baseline is described with a polynomial of variable order. The method is simultaneously a filter procedure Deconvolution of poorly separated peaks is possible. The software is developed on a minicomputer; however, test results of this study indicate the feasibility of implementation on a microcomputer without extremely time-consuming runs of the program.     

ICP-AES法测定油漆中总铅量不确定度的讨论

根据EURACHEM／CITAC2000中的规定计算了ICP—AES法测定油漆中总铅量的不确定度,建立了数学模型和根据在测试过程中产生不确定度的变量建立了因果图。通过转化数学模型和因果图,对油漆标准样品中含铅量的测定精密度和准确度进行试验,并计算了此方法的不确定度。结论中提出可根据在日常分析试验中所积累的数据,用B类不确定度的计算方法计算所得的测定过程的不确定度具有更高的真实可信性,并指出要不断积累测试数据,不断更新测定方法的不确定度,这样得到的不确定度更为可信合理。     

Correlation equations for solubility of NaHS in water and organic solvents at 297–323 K

The solubility of NaHS in different solvents had been determined from 297.85 to 342.55 K by an analytical method. A solubility model is proposed and the solubilities calculated by the model show good agreement with experimental data. It provided the basic data for the synthesis of isopropyl mercaptan in industry.     

Mixture models for two-dimensional baseline correction,applied to artifact elimination in time-resolved spectroscopy

Baseline correction and artifact removal are important pre-processing steps in analytical chemistry. We propose a correction algorithm using a mixture model in combination with penalized regression. The model is an extension of a method recently introduced for baseline estimation in the case of one-dimensional data. The data are modeled as a smooth surface using tensor product P-splines. The weights of the P-splines regression model are computed from a mixture model where a datapoint is either allocated to the noise around the baseline, or to the artifact component. The method is broadly applicable for anisotropic smoothing of two-way data such as two-dimensional gel electrophoresis and two-dimensional chromatography data. We focus here on the application of the approach in femtosecond time-resolved spectroscopy, to eliminate strong artifact signals from the solvent.     

Analytical Methodologies with Very Low Blank Levels: Implications for Practical and Empirical Evaluations of the Limit of Detection

Abstract

Limit of detection criteria in analytical chemistry are regularly specified in terms of the distribution of the measured blank response. The consequences of an analytical blank response with a negligible distribution of measured values on the calculation and significance of limit of detection criteria receive scarce attention. A consideration of a hypothetical analytical methodology where the blank response is zero and the distribution of blank values is negligible is described. The impact of this situation on the traditional limit of detection criteria and on calibration relationships is discussed in detail. A simple, empirical method of estimating indicative method detection limits based on whole‐method repeatability is proffered. This model has been validated with experimental data.     

An evaluation of voltammetric titration procedures for the determination of trace metal complexation in natural waters by use of computers simulation

The impact of random analytical errors on the determination of metal complexation parameters of natural waters by metal titration procedures based on cathodic stripping (CSV) or anodic stripping (ASV) voltammetry is investigated by means of computer simulation. The results indicate that random analytical errors are of overriding importance in establishing the range of ligand concentrations and conditional stability constants that can be accurately determined by these techniques. Simulations incorporating realistic estimates of random analytical error show that only stability constants lying within a relatively narrow range, typically three orders of magnitude, can be determined accurately by the ASV procedure. The CSV procedure suffers from the same limitations, but is potentially more flexible in that the available detection window can be moved (but not widened) by adjustments to the method. Both techniques are capable of accurately determining ligand concentrations provided that the corresponding stability constant, K′, is greater than a threshold value which corresponds to the lower end of the available detection window for the stability constant. Realistically attainable improvements in analytical precision did not greatly improve the performance of either technique. Two graphical treatments for the evaluation of metal complexation parameters from titration data are compared: the Scatchard and Van den Berg/Ruzic plots. Simulations indicate that at least for the single-ligand model of complexation, the Van den Berg/Ruzic method is superior. The importance of the simulation results with respect to determining metal complexation parameters in natural waters is discussed. This study illustrates the value of computer simulation when complex, time-consuming analytical techniques are applied and the need for rigorous analysis of errors in producing data of environmental relevance.