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Predicting % of crystallinity in FCC catalysts by FT‐MIR and PLS
Author(s) -
Dago Angel,
Talavera Isneri,
Fernández Reinaldo,
Hernández Noslen,
Laza Mercedes
Publication year - 2008
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1155
Subject(s) - partial least squares regression , calibration , linear regression , mathematics , mean squared error , multivariate statistics , statistics , crystallinity , analytical chemistry (journal) , materials science , chemistry , chromatography , composite material
This paper describes an analytical procedure for prediction of percent of crystallinity of fluidized catalytic cracking catalysts (FCC) using Fourier transform mid infrared spectroscopy (FT‐MIR) and partial least‐squares (PLS) multivariate calibration technique. In order to make a robust regression model, multiplicative scatter correction (MSC) and smoothed second derivative pre‐processing methods were tested. Root mean squared error of prediction (RMSEP) of an independent test set was used to measure the performance of the models. The comparison shows that reasonable values of RMSEP and RMSECV were obtained for PLS‐MSC model (RMSEP = 0.8% and RMSECV = 1.3%). The accuracy of the results obtained by the PLS‐MSC regression model is in accordance with the uncertainty of the XRPD reference method. The developed method can be implemented in a refinery laboratory environment with ease. Copyright © 2008 John Wiley & Sons, Ltd.