engleski

Development of the calibration model for real-time measurement of glycine concentration in glycine-water system using ANN

The subject of this research is the development of a calibration model based on in-situ ATR-FTIR measurements using artificial neural network (ANN) for monitoring the concentration of glycine in glycine-water system in a batch crystallizer. Supersaturation, as a driving force of batch cooling crystallization processes, has a strong effect on product properties, i.e. crystal morphology, purity and crystal size distribution.[1] Therefore, the application of process analytical techniques plays a vital role for real-time monitoring and controlling of crystallization processes in order to obtain high-quality products. Attenuated total reflectance - Fourier transform infrared spectroscopy (ATR-FTIR) is used for inline measurement of solute concentration. IR spectrum is characteristic of the vibrational structure of the substance in immediate contact with the ATR immersion probe.[2] To obtain useful information from the spectral data, a calibration model is needed. A calibration model for glycine concentration was developed based on experimental data. Experiments were conducted with different process conditions, including changes of solute concentration and the operating temperature. The developed ANN model has a multilayer perceptron structure. ANN was trained using FTIR spectral data with the corresponding temperature values collected in the laboratory crystallizer. Validation of the model was performed on an independent dataset not used during the neural network training. The application of the developed model for monitoring the concentration in real-time combined with solubility curve and metastable zone width provides information about supersaturation in real-time. That allows the application of a process control method for maintaining the desired degree of supersaturation and thus, obtaining uniform product properties.

crystallization, process analytical technology, artificial neural network, ATR-FTIR spectroscopy, calibration

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