aThe paper studies the utilization of attenuated total reflectance-Fourier transformed infrared (ATR-FTIR) and Raman spectroscopy to investigate isothermal semi-batch precipitation of a model compound, L-glutamic acid. ATR-FTIR spectroscopy was mainly used for in-line monitoring of the solution phase and Raman spectroscopy for analysis of the solid phase. L-glutamic acid has two reported polymorphs: a metastable a form and a stable b form. The b form can be obtained at relatively high supersaturation levels at 25 o C. The synthesis consists of a sodium glutamate reaction with sulfuric acid yielding L-glutamic acid crystals and sodium sulfate as a side-product solute. The spectral data were utilized to interpret the crystallization process using multivariate methods. A thermodynamic model taking into account the non-ideal character of the studied compound system and dissociation of different compounds is introduced. The resolution of ATR-FTIR is not sufficient to determine directly the L-glutamic acid concentration in the solution. Therefore, special efforts were made to determine the instantaneous concentration of dissolved glutamic acid based on the mass balance and ATR-FTIR spectra. Calibration concentrations were based on thermodynamic data. Multivariate methods were applied in monitoring the precipitation process and to predict indirectly the concentration of the chemical compounds. In this study, the spectra from ATR-FTIR were utilized to estimate and predict the concentrations from thermodynamic modeling. It was also investigated if the Raman spectra could be used for this purpose.
The aim of the present study was to investigate feedback control of a reactive crystallization process. The present study built up a control structure needed to control the driving force of reactive crystallization using the feed rate of added acid. The concentration of the crystallizing compound and pH was used to compute feedback in the closed-loop control of semi-batch precipitation. The concentration of L-glutamic acid was determined from measured MID-IR ATR-FTIR spectra based on a multivariate model. Dynamic change of set value was based on the mass of added sulfuric acid and pH. The studied properties of the product crystals were polymorphism and crystal size. The polymorphic composition was analyzed with a Raman spectrometer and was expressed by mass fraction of the a-polymorph. The obtained results showed that the developed feedback process control system allows effective control of forming of polymorphs.
The crystallization mechanism of anhydrate/hydrate has to be understood in order to control the hydration state of an active pharmaceutical ingredient. In the present work, the formation of the anhydrous (CBZA) and dihydrate (CBZH) form of carbamazepine (CBZ) in ethanol−water solutions was studied by simultaneous monitoring of both the anhydrate/hydrate phase of the crystals and the CBZ concentration in the mother liquor with the Raman immersion probe. Two different cooling strategies and the effect of one surfactant were studied. The information obtained from the Raman spectroscopy indicated that the thermodynamic factor was dominated in determining the anhydrate/hydrate form of the crystals in the studied system. The thermodynamically stable form was obtained in all studied crystallization conditions. The presence of a surfactant additive showed a slight promotion effect only on the phase transformation of CBZA to CBZH. The results obtained in the present work lead to improved understanding of the formation mechanism of anhydrate/hydrate in aqueous solution.
In chemometric studies all predictor variables are usually collected in one data matrix X. This matrix is then analyzed by PLS regression or other methods. When data from several different sub-processes are collected in one matrix, there is a possibility that the effects of some sub-processes may vanish. If there is, for instance, mechanic data from one process and spectral data from another, the influence of the mechanic sub-process may not be detected. An application of multi-block (MB) methods, where the X-data are divided into several data blocks is presented in this study. By using MB methods the effect of a sub-process can be seen and an example with two blocks, near infra-red, NIR, and process data, is shown. The results show improvements in modelling task, when a MB-based approach is used. This way of working with data gives more information on the process than if all data are in one X-matrix. The procedure is demonstrated by an industrial continuous process, where knowledge about the sub-processes is available and X-matrix can be divided into blocks between process variables and NIR spectra.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.