Pregled bibliografske jedinice broj: 1184218
Development of the calibration model for real-time measurement of glycine concentration in glycine-water system using ANN
Development of the calibration model for real-time measurement of glycine concentration in glycine-water system using ANN // 27HSKIKI - Book of abstracts
Veli Lošinj, Hrvatska, 2021. str. 318-318 (poster, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 1184218 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Development of the calibration model for real-time
measurement of glycine concentration in
glycine-water system using ANN
Autori
Gavran, Matea ; Dorić, Hrvoje ; Bolf, Nenad
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
27HSKIKI - Book of abstracts
/ - , 2021, 318-318
Skup
27. hrvatski skup kemičara i kemijskih inženjera (27HSKIKI)
Mjesto i datum
Veli Lošinj, Hrvatska, 05.10.2021. - 08.10.2021
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
crystallization, process analytical technology, artificial neural network, ATR-FTIR spectroscopy, calibration
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Kemijsko inženjerstvo
POVEZANOST RADA
Projekti:
EK-EFRR-KK.01.1.1.07.0017 - Napredno vođenje procesa kristalizacije (CrystAPC) (Bolf, Nenad, EK - KK.01.1.1.07) ( CroRIS)
Ustanove:
Fakultet kemijskog inženjerstva i tehnologije, Zagreb