EXCEL TUTORIAL FOR PARAMETRIZATION OF ANALYTICAL CURVES

Authors

  • Cristian Debortolli Universidade Federal do Rio Grande
  • Luiza Dalbosco Universidade Federal do Rio Grande
  • Daniela Oppelt Universidade Federal do Rio Grande
  • Walter Augusto Ruiz Universidade Federal do Rio Grande
  • Ródner Bianchin Pedroso Universidade Federal do Rio Grande
  • Leano Aldous Jensen Universidade Federal do Rio Grande

Keywords:

analytical curve, parameters of the calibration curve, statistical models

Abstract

Analytical chemistry uses empirical procedures to determine analytes concentration through instrumental techniques that relate the analytical signal, instrumental response (y) to the analyte concentration (x). The signal measured by the instrument is generally a function of the analyte concentration, which is plotted (y = fx), commonly referred to as analytical curve or standard curve. Linear functions are commonly used for this purpose, thus the linearization of this function is necessary to calculate the concentration of the analyte and, to properly express the result, statistical processing of the experimental data is required. Usually, students of instrumental analytical chemistry courses find it difficult to process and interpret results when using a calibration curve and understand its parameters. In that sense, it is proposed a linear regression tutorial of experimental data for the calculation of all the parameters that characterize an analytical curve, through a procedure using Excel spreadsheet MS Office 2016. A routine of calculations was created using experimental data from the spectrophotometric determination of protein, using the standard BSA and pH meter calibration, but it can be extended to other procedures where the calculation is necessary.

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References

ASSOCIATION OF OFFICIAL ANALYTICAL CHEMISTS – AOAC. Official Methods of Analysis. 1995. Arlington. USA.

BISQUERRA, J.; CASTELLÁ S., J.; MARTÍNEZ, F. Introdução à Estatística, enfoque informático com o pacote estatístico SPSS. Ed. Artmed. Porto Alegre, RS. 2004.

GONÇALVES, M. L. S. S. Métodos Instrumentais para Análise de Soluções: Análise Quantitativa. 4ª ed. Lisboa: Fundação Calouste Gulbenkian, 2001.

HARRIS, D. Explorando a Química Analítica 4ª. Ed. Trad. Por Julio C. Afonso, Mauro dos Santos de Carvalho, Milton R. Salles, Oswaldo Barcia. Ed. Gen LTC, R.J. 2011.

HOLLER, F. J.; SKOOG, D. A. e CROUCH, S. R. Princípios de Análise Instrumental.

ª ed. São Paulo: Bookman, 2009.

MILLER, N. J. e MILLER, J. C. Estadística y Quimiometría para Química Analítica. Trad. C. M. Jimínez e R. I. Hornillos. 4ª ed. Madri: Pearson Educación, 2002.

NETO B., B.; SCARMÍNIO S., L.; BRUNS, R.E. Como Fazer Experimentos. Ed. UNICAMP. 2007.

RAWLING, J. O.; PANTULA, S. G. e DICKEY, D. A. Applied Regression Analysis: A Research Tool. 2ª ed. Nova York: Springer, 1998.

RIBEIRO, F. A. L. e FERREIRA, M. M. C. Planilha de validação: uma nova ferramenta para estimar figuras de mérito na validação de métodos analíticos univariados. Química Nova, v. 31, n. 1, p. 164-171, 2008.

STROBEL, H. A. e HEINEMAN, W. R. Chemical Instrumentation: A Systematic Approach. 3ª ed. Nova York: John Wiley & Sons, 1989.

Published

2021-10-20

How to Cite

Debortolli, C., Dalbosco, L., Oppelt, D., Augusto Ruiz, W., Bianchin Pedroso, R., & Aldous Jensen, L. (2021). EXCEL TUTORIAL FOR PARAMETRIZATION OF ANALYTICAL CURVES. VETOR - Journal of Exact Sciences and Engineering, 29(1-2), 52–68. Retrieved from https://furg.emnuvens.com.br/vetor/article/view/7167

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