Rank annihilation factor analysis using mean centering of ratio spectra for kinetic–spectrophotometric analysis of unknown samples

Bahram, Morteza; Mabhooti, Mehdi

doi:10.1016/j.aca.2009.02.032

Cited by 12 publications

(8 citation statements)

References 33 publications

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“…Bahram et al . used RAFA for multicomponent kinetic‐spectrophotometric determinations using difference spectra . Afkhami et al .…”

Section: Review Of Some Published Materials By Iranian Chemists In DImentioning

confidence: 99%

“…Rank annihilation factor analysis is a chemometrics method used by Iranian chemometricians for different purpose. Bahram et al used RAFA for multicomponent kinetic-spectrophotometric determinations using difference spectra [49,50]. Afkhami et al used this method for the study of oxidation and tautomerization reactions and also inclusion phenomena [51][52][53].…”

Section: Multivariate Curve Resolution and Factor Analysismentioning

confidence: 99%

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A perspective on the growth of chemometrics in Iran: a glance into activities between 2005 and 2012

Naseri

Bahram

2013

Journal of Chemometrics

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Although the first publications in the field of chemometrics by Iranian researchers go back nearly 23 years, Iran's chemometrics has experienced significant growth after the year 2000. More than 1500 papers have been published by Iranian chemometricians between 2005 and 2012 which is about seven times more than those published before 2005. The aim of this review is to present a perspective about Iran's chemometrics developments. The role of enthusiastic students, motivated professors, annual workshops, and international collaborations is discussed in this work. After introducing the first papers in each field of chememotrics, the papers published during 2005–2012 were screened, and some of them were introduced. Copyright © 2013 John Wiley & Sons, Ltd.

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“…Bahram et al . used RAFA for multicomponent kinetic‐spectrophotometric determinations using difference spectra . Afkhami et al .…”

Section: Review Of Some Published Materials By Iranian Chemists In DImentioning

confidence: 99%

Section: Multivariate Curve Resolution and Factor Analysismentioning

confidence: 99%

A perspective on the growth of chemometrics in Iran: a glance into activities between 2005 and 2012

Naseri

Bahram

2013

Journal of Chemometrics

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“…The prediction error of a single component in the mixtures was calculated as the relative standard error (RSE) of the prediction concentration using equation 12: 32 (12) where N is the number of samples, C j is the concentration of the component in the j th mixture and C^j is the estimated concentration. The total prediction error of N samples is calculated as equation 13: (13) where C ij is the concentration of the i th component in the j th samples and C^i j its estimate.…”

Section: Experimental Data Setmentioning

confidence: 99%

“…Moreover, the second-order algorithms avoid the need of using a large number of calibration sample since a single calibration sample, that contains the analyte of interest, is sufficient. 8 Suitable algorithms for analyzing second-order data are parallel factor analysis (PARAFAC), 9 the generalized rank annihilation method (GRAM), 10 rank annihilation factor analysis (RAFA), 11,12 direct trilinear decomposition (DTLD), 13 bilinear least squares (BLLS), 14 alternating trilinear decomposition (ATLD) 15 and its variants (self-weighted alternating trilinear decomposition (SWATLD), 16 alternating penalty trilinear decomposition (APTLD) 17 and multivariate curve resolution-alternating least squares (MCR-ALS). 18 It was shown that MCR-ALS is a powerful tool for the species resolution and the quantitative determination of many types of unresolved chemical mixtures especially in kinetic systems.…”

Section: Introductionmentioning

confidence: 99%

A second-order standard addition method based on the data treatment by calculation of variation matrix of kinetic systems analyzed by MCR-ALS

Naseri¹,

Bahram²,

Mabhooti³

2011

J. Braz. Chem. Soc.

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Um método novo é proposto para resolver dados de cinética-espectrométrica de misturas do tipo multicomponentes e para a determinação de analito(s) na presença de matriz desconhecida. O método utiliza dados de matrizes de variação pelo deslocamento de alvo, denominado espaço de reação. A matriz de variação é obtida pela subtração do espectro do ponto-zero (isto é, primeiro espectro) de cada espectro a cada tempo. Este deslocamento espacial diminui os números de classificação para os números de reações. A resolução da curva de auto-modelagem é usada para resolver as matrizes dos dados de cinética-espectrométrica por matrizes de analitos. Além do mais, o método de adição padrão de segunda ordem é usado para remover o efeito(s) das matrizes para quando se analisa amostras desconhecidas. Isto significa que, a análise quantitativa pode ser realizada pela argumentação da matriz de variação das amostras desconhecidas e amostras adicionadas de padrão e, em seguida, traçar a curva de calibração de adição de padrão. A aplicabilidade do método proposto é avaliada usando dados modelo e real de misturas de analitos.A new method is proposed to resolve the kinetic-spectrophotometric data of multicomponent mixtures and determination of analyte(s) in the presence of unknown matrix. The method uses variation matrix data by shifting to another target, namely the reaction space. The variation matrix is obtained by subtracting the zero-point spectrum (e.g., first spectrum) from each spectrum at each time. This space shifting decreases the rank numbers to the numbers of reactions. Self-modeling curve resolution is used to resolve the variation matrices of kinetic-spectrophotometric data for mixtures of analytes. In addition, second-order standard addition method is used to remove the matrix effect(s) when analyze unknown samples. This means that, quantitative analysis can be performed by augmentation of the variation matrix of the unknown samples and standard added samples and, then, plotting standard addition calibration curve. The applicability of the proposed method is evaluated using model and real data for mixtures of analytes.

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“…Mean centering of ratio spectra was also applied to pre-treat kinetic-spectrophotometric data prior to rank annihilation factor analysis method for the analysis of unknown samples [33].…”

Section: Introductionmentioning

confidence: 99%

Estimation of the rate constants of second order reactions using mean centering of ratio spectra

Gorji

Bahram

Golshan

2010

JICS

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A new application of the mean centering of ratio spectra method is proposed for estimation of the rate constants of second order reactions, using kinetic-spectrophotometric data. The method is based on the mean centering of the ratio spectra to obtain a kinetic profile of the product. Using computational fitting, the rate constant can be obtained without any ambiguity. An interesting feature of second-order reactions is that the number of steps in the reaction is less than the number of absorbing species, resulting in a rank-deficient response matrix. Through using row mean centering of ratio spectra, the pure response of the product of the reaction could be obtained, and thus an accurate estimation of rate constant would be possible. The applicability of the method was evaluated by using several model data. The reaction of 1,2-naphthoquinone-4-sulfonate sodium (NQS) and 3-nitroaniline (TNA) in ethanol as a real system was also studied applying the proposed method.

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Rank annihilation factor analysis using mean centering of ratio spectra for kinetic–spectrophotometric analysis of unknown samples

Cited by 12 publications

References 33 publications

A perspective on the growth of chemometrics in Iran: a glance into activities between 2005 and 2012

A perspective on the growth of chemometrics in Iran: a glance into activities between 2005 and 2012

A second-order standard addition method based on the data treatment by calculation of variation matrix of kinetic systems analyzed by MCR-ALS

Estimation of the rate constants of second order reactions using mean centering of ratio spectra

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