Generalized Standard Addition Method Research Articles

Application of Generalized Standard Addition Method and Ultraviolet Spectroscopy to Quantify Electrolytic Depolymerization of Lignin

Industrial lignin waste is an important byproduct of bio-refineries and the paper industry. Depolymerization of industrial lignin could generate useful aromatic compounds. This group has focused on electrolytic decomposition of biorefinery lignin. To quantify electrolytic decomposition of the lignin in a highly caustic solution, ultraviolet (UV) spectroscopy provides a useful probe. The conversion of the neat lignin to the oxidized products achieved by the electrolytic reactor may be measured by quantifying the amount of unreacted neat lignin that remains in the effluent. Because the properties of electrolytic decomposition products are largely unknown, a useful approach to quantify decomposition of the neat lignin is to use a multivariate calibration method referred to as the generalized standard addition method (GSAM). In this approach, the electrolytic decomposition products represent a background interference and the neat lignin that remains can be quantified. This approach allows the conversion of the neat lignin to be calculated in a solution that is a complex mixture. • Conversion of lignin by an electrolytic reactor is quantified. • The generalized standard addition method (GSAM) determines the concentration of the neat lignin remaining in the solution after electro-oxidation. • An improved GSAM using the best linear unbiased estimator (BLUE) is compared with the conventional approach. • A novel GSAM using inverse least squares avoids the limitations knowledge of all the components in the conventional GSAM.

Solving matrix effect, spectral overlapping and nonlinearity by generalized standard addition method coupled with radial basis functions–partial least squares: simultaneous determination of atorvastatin and amlodipine in urine

For simultaneous determination in conditions with spectral overlap and variation of matrix effects, coupling of the generalized standard addition method (GSAM) with the multivariate nonlinear method of radial basis function–partial least squares (RBF–PLS) was proposed. The nonlinearity caused by the GSAM used to correct matrix effects was studied, and principal component analysis was proposed for identifying it. In the method introduced, the whole sensor range can be used without the collinearity problem encountered in the application of GSAM with classical least squares (CLS), and calibration can be made for each analyte, separately. The introduced method was applied to determine amlodipine and atorvastatin in urine samples. The mean of the percent recoveries was between 95 and 101.12. The percent relative standard deviation values of the method were in most cases below 5%. The results of GSAM–RBF–PLS were compared with those obtained by GSAM–CLS and GSAM–PLS. Copyright © 2013 John Wiley & Sons, Ltd.

Solving matrix effect, spectral interferences and nonlinearity by generalized standard addition method coupled with radial basis functions-partial least squares: Application to simultaneous determination of drugs in urine

We introduce here the coupling generalized standard addition method (GSAM) with radial basis functions-partial least squares (RBF-PLS) in inverse mode for analyte determination in the presence of matrix effect, spectral overlapping caused by interferences and nonlinearity. Therefore, in the procedure introduced, the whole sensor range can be used without afraid of collinearity problem encountered in application of GSAM with classical least squares and calibration can be made for each analyte, separately. The presence of nonlinearity was identified by a special case of principal components plots. Direct orthogonal signal correction (DOSC) was used as a preprocessing method. Resolution of binary and ternary mixtures of paracetamol (PAR), desxtromethorphan (DEX) and phenylephrine (PHE) in urine were successfully achieved without any sample pre-treatment and analyte separation. The mean recoveries for the real samples were between 98.2% and 107.4% in binary and between 95.9% and 100.3% in ternary mixtures. Relative standard deviations of the results were between 1.87% and 3.92% in binary and between 3.67 and 5.32 in ternary mixtures. Moreover, superiority of the proposed method over those which use classical least squares and partial least squares was shown.

Simultaneous spectrophotometric and chemometric determination of lipids in synthetic mixtures and human serum

AbstractThis article describes the development of a new paradigm in lipid testing wherein seven major human plasma lipids are determined simultaneously without the need for analytical separations. Included are cholesterol and the esters of linoleic, conjugated linoleic (CLA), arachidonic, linolenic, eicosapentaenoic, (EPA), and docosohexaenoic acids, (DHA). The simple quantitative colorimetric assay is rapid, rugged, inexpensive and specific to the ‐CH=CH‐CH2‐ functional group in both cyclic and acyclic structures. The critical moiety in the functional group is the α‐methylene (allylic) group that triggers the reaction. Without it, a double or triple bond is not reactive. The visible spectrum for a typical plasma sample turned out to be the linear sum of the weighted contributions from all seven analytes that – given the heterogeneity of blood samples – leads to a broad diversity in the spectral patterns. To resolve the spectral data, a number of chemometric techniques were investigated. Initially, calculations were made on spectral data that originated from prepared synthetic mixtures whose molar concentrations were known. The most encouraging algorithms employed are: coupling ridge regression (RR) with K‐matrix, partial least squares regression (PLS), and generalized standard addition method (GSAM). An attempt to apply GSAM to serum samples is validated using GC‐MS. The same serum samples are analyzed using GC‐MS and spectrophotometry and the ratios of omega‐6 to omega‐3 obtained from the analyses are compared. Results using both methods correspond very well. (The reaction between acetyl chloride and olefinic systems is described as a Friedel‐Crafts reaction but the mechanism of this process, the structure of the products, and the nature of the resulting chromophore remains to be fully identified.)

Genetic algorithm-based method for selecting conditions in multivariate determination of povidone-iodine using hand scanner

Application of hand scanner in multivariate quantification of povidone-iodine (PVI), as a popular antiseptic agent, in some of pharmaceutical products is presented. Brightness, contrast, and mixed gamma were the adjustable scanner parameters. For selection of optimum values of the scanner parameters, partial least squares (PLS) and multiple linear regression (MLR), coupled with genetic algorithm, were performed. For the selected variables, both MLR and PLS performances were similar and appropriate. From the results obtained, it was concluded that the simpler method of MLR could be successfully applied instead of PLS, which requires more statistical experience. The considered concentration range for PVI in the calibration and prediction samples was 0.0–10.0% (w/v). For the analysis of pharmaceutical samples, generalized standard addition method (GSAM) was applied (on the variables selected by GA) and desirable results were obtained. Relative standard error (RSE) of less than 8% was obtained for the majority of samples analyzed.

Implementation of a Generalized Standard Addition Method in a Flow Injection System Using Merging-Zones and Gradient Exploitation

A novel strategy for implementing a generalized standard addition method (GSAM) in a simple two-channel flow injection (FI) system and for correcting matrix effects and spectral interferences in multicomponent analysis is described. The FI-GSAM system exploits the concentration gradients of the sample and the standard solution, requires only one standard solution per analyte and provides several addition levels using a single simultaneous injection of the sample and of each standard solution. Because the matrix effects change at every addition level, a novel mathematical model for this FI-GSAM has been derived. The method was critically evaluated for simultaneous K, Ca and Na determinations by flame photometry in synthetic samples with different ethanol or glycerol contents, added to the samples to promote matrix effects. The results show good agreement with the expected values, with the relative error and the overall relative standard deviation usually being <5% (n=5) for 2.5–5.0 Na, 20.0 K and 1000 mg l–1 Ca. The elapsed time for the simultaneous determination of three analytes was about 2 min, consuming 400 m l of the sample and 100 m l of each standard solution.

Test of the generalized standard addition method and linearization algorithms for the direct, simultaneous, multi-element analysis of solid samples by electrothermal atomic absorption spectrometry

The application of a multi-element electrothermal atomic absorption spectrometry (ETAAS) instrument with line sources and Zeeman-effect background correction to the direct, simultaneous determination of Ag, Cd, Cr and Pb in solid reference materials is described. Due to the occurrence of interference effects, the generalized standard addition method (GSAM) was required for calibration purposes. In order to extend the dynamic range for analytes present at high concentrations, linearization algorithms were tested. The combination of the GSAM and extension of the linear range, when necessary, generally yielded acceptable analytical results for the suite of elements studied, and may provide a useful approach to calibration in the direct analysis of solid samples by multi-element ETAAS. However, while linearization yielded good results for Ag and Cd in solid reference materials, it remains to be demonstrated that acceptable performance can be obtained for other elements in real samples.

Background bilinearization by the use of generalized standard addition method on two-dimensional data

The capability of the standard addition method to correct the matrix effects and the advantage of two-dimensional bilinear analytical data were utilized in a hybrid method combining the generalized standard addition method (GSAM) and constrained background bilinearization. The proposed method can effectively compensate for both matrix effects and the influence of unexpected interferents in multivariate calibration. First, GSAM was extended to two-dimensional bilinear data. In the process of standard additions, the background is fixed and the standard responses of the sought-for components in actual samples could be thus acquired even with the existence of unexpected interferents in the sample. The quantification of the sought-for analytes was then completed by use of background bilinearization. In the optimization process of background bilinearization, a global optimization technique, generalized simulated annealing (GSA), was adopted to guarantee the global minimum. The characteristic performance of the proposed method was tested by a series of simulations and experimental fluorescence excitation-emission data with organic dye mixtures.

Evaluation and Elimination of the Interference Effects of Three Cephalosporins on the Kinetic-Spectrophotometric Determination of Creatinine in Serum Using the Jaffe Reaction

Abstract The cephalosporins studied, cefotaxime, cefazolin and cefoxitin react with alkaline picrate showing a complex kinetic behaviour which include a decomposition step in the case of cefotaxime and cefazolin. Cefoxitin does not conform strictly to pseudo-first order kinetics which seems to indicate that one or more intermediate reaction products might be formed before the final complex, or this might be unstable. The presence of the cephalosporins leads to results affected by systematic errors in the determination of creatinine in serum. This effect can be minimized for cefotaxime and cefazolin by choosing a specific time interval to process the analytical signal, δA. These intervals are 180–45 and 60–10s, respectively. The presence of cefoxitin requires the application of the generalized standard-addition method, which involves the simultaneus determination of creatinine and cefoxitin by measuring the δA for two different time intervals.

Elimination of interferences and effects from drift in working parameters in inductively coupled plasma atomic emission spectrometry by using a combination of the generalized standard addition method and the generalized internal reference method

The generalized standard addition method (GSAM) and the generalized internal reference method (GIRM) were combined in a single experimental setup. This combination was used to eliminate spectral interferences and effects due to fluctuations in the system parameters when applied to systems that are flicker noise limited and that perform simultaneous multichannel measurements. p]The developed method was simplified so as to keep it within routine perspective by assuming that the applied power and nebulizer pressure are the only system parameters of which the variation could affect the precision of the method. This assumption reduced considerably the number of measurements and the mathematical calculations required by the GIRM method. The developed method was tested by measuring the alloying constituents of standard steel samples using multichannel measurements. The experimental results indicate an effective elimination of interferences and effects of drift in various experimental parameters. The precision range achieved for measured elements was 0.1–0.4% relative standard deviation. The experimental results obtained by the developed method were compared with the results obtained by the GSAM method. This comparison indicated clearly the superior performance of the developed method. The mathematical calculations required by the developed method were executed using a computer programme written in Fortran IV language and run by an NEC-750 computer. This programme is able to perform the necessary calculation in just 8 s for samples containing 20 analytes.

Interplay between chemistry and statistics, with special reference to calibration and the generalized standard addition method

Abstract Ever since the beginning of this century problems in the field of chemistry and chemical engineering have played an important role in the development of statistics, and statistical models and methods have proved to be an efficient tool for planning of chemical experiments and in the analysis of chemical data. After mentioning a number of mutually important statistical methods and chemical problem areas, I will discuss in more detail the interplay and lack thereof in the field of calibration. In particular I will describe and discuss the generalized standard addition method (GSAM) with a two-fold intention: to propose statistically motivated improvements and future developments in the theory of estimation and design for this method of multicomponent analysis, as well as to illustrate how a statistician looks at the topic, for the possible benefit of chemists in their future contacts with statistics and statisticians.

Evaluation of volume and matrix effects for the generalized standard addition method

A volume-dependent problem in use of the generalized standard addition method (GSAM) is evaluated. It is shown both mathematically and experimentally how to correct the deficiency. The revised GSAM was applied with direct current plasma spectroscopy in the presence of a salt and an acetone matrix effect.

A simplified approach to the generalized standard-addition method and its application in electrothermal atomic absorption spectrometry

A simple and general standard-addition method for a single-component determination is presented. The method uses two independent variables for the calculation of the analyte concentration (the amount of sample taken and the amount of analyte added) and one dependent variable, the response. The sensitivity and the response of the blank can also be estimated from the model by changing the amount of the sample and the amount of the analyte addition. In the simples case, a linear equation is assumed to exist between the variables. Geometrically, the model can be expressed by the response plane in the variable-space. The method has all the advantages of the ordinary standard-addition method but also includes automatic blank elimination and versatile matrix-interference control. Two examples of the use of the method are based on graphite-furnace atomic absorption spectrometry of chromium and lead. Standard statistical packages are applied.

Non-linear transformations of factors in the generalized standard addition method

Experimental designs and non-linearly transformed factors (concentrations of analytes) have been applied in the Generalized Standard Addition Method (GSAM). The relationship betweenN measured analytical signals,R(1),...,Rsu(n), and concentrations of standard additions, Δc1,..., Δcn, ofn analytes has been approximated by the following polynomial models: The regression coefficientsB in models (1) are calculated from thesimple formulae1, 3, 4.Functionsfi(l) (e.g. linear, parabolic, exponential, hyperbolic or logarithmic) are selected on the basis of the experimentally determined relationshipsR(l) (l=1, ...,N) vs.ci (i=1, ...,n). An example concerns the flame emission photometric determination of Na and Ca. 22 factorial and uncomplete second-degree modelsR(l) have been applied expressed by linear and hyperbolic functionsfi(l). The results of determination of Na by GSAM reveal significant improvement of accuracy as compared with the conventional single-component standard addition method.

Interactive calibration by a recursive generalized standard addition method

The generalized standard addition method (GSAM) has recently been introduced for calibration to avoid matrix effects and many interferences. In GSAM, all additions and measurements precede the calculations of the K matrix (sensitivities of all analytes at all sensors_ and the analyte concentration. A recursive version of GSAM is presented here. Some new powerful properties are added to the method: (1) on-line checking of the validity of the linear model during the data acquisition stage, (2) simultaneous evaluation of the value and precision of the elements of the K matrix during the additions, and (3) access to an on-line interactive calibration, terminating the addition when the precision is within the desired limits or a deficiency in the model has been detected. The method is demonstrated for spectrophotometric measurements of copper and nickel in the presence of EDTA.

Compensation for drift and interferences in multicomponent analysis

Abstract : The detection and subsequent correction of drift in an analytical signal occurring during the course of an analysis is a common problem in analytical chemistry. In this paper, a solution to this problem is presented in the form of an extension to the theory of the Generalized Standard Addition Method (GSAM), a method currently used to simultaneously correct for matrix effects and interferences in multicomponent analysis. (Author)

Generalized standard addition method for multicomponent instrument characterization and elimination of interferences in inductively coupled plasma spectroscopy

Various types of interferences are known to exist when using inductively coupled plasma (ICP) emission spectrometry. They have been classified as stray light, direct spectral overlap, overlap of severely broadened lines of high intensity, and continuum emission from ion-electron recombination. The presence of these interferences often requires alternate (less sensitive) wavelength selection. The generalized standard addition method (GSAM) is a method of multicomponent analysis which provides a means of detecting the interference effects, quantifying the magnitude of the interferences, allowing the use of the most sensitive wavelengths for all analytes, and simultaneously determining analyte concentrations. In addition, the GSAM can be used to completely characterize all analytical wavelengths of a particular ICP instrument. This procedure is quite general and can be applied to most multicomponent methods of analysis.