Quantification of CaCO3-CaSO3 center dot 0.5H(2)O-CaSO4 center dot 2H(2)O mixtures by FTIR analysis and its ANN model

Date

2004-02-01

Author

Boke, H
Akkurt, S
Ozdemir, S
Gokturk, EH
Saltık, Emine Nevin

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A new quantitative analysis method for mixtures of calcium carbonate (CaCO3), calcium sulphite hemihydrate (CaSO3.1/2H(2)O) and gypsum (CaSO4.2H(2)O) by FTIR spectroscopy is developed. The method involves the FTIR analysis of powder mixtures of several compositions on KBr disc specimens. Intensities of the resulting absorbance peaks for CaCO3, CaSO3.1/2H(2)O and CaSO4.2H(2)O at 1453, 980, 1146 cm(-1) were used as input data for an artificial neural network (ANN) model, the output being the weight percent compositions of the mixtures. The training and testing data were randomly separated from the complete original data set. Testing of the model was done with successfully low-average error levels. The utility of the model is in the potential ability to use FTIR spectrum to predict the proportions of the three substances in unknown mixtures.

Subject Keywords

Characterization methods, Computer simulation, Modelling, Artificial neural networks, FTIR, Sulphur dioxide, Calcium carbonate, Gypsum

URI

https://hdl.handle.net/11511/31795

Collections

Graduate School of Natural and Applied Sciences, Article