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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Louhi-Kultanen, Marjatta
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Publications (4/4 displayed)
- 2020Freeze Concentration of Aqueous [DBNH][OAc] Ionic Liquid Solutioncitations
- 2016Pulsed electric field assisted sol–gel preparation of TiO2nanoparticlescitations
- 2014Growth and characterization of 6-chloro-2,4-dinitroaniline crystals in anti-solvent precipitation and reprecipitation methodscitations
- 2005IR spectroscopy together with multivariate data analysis as a process analytical tool for in-line monitoring of crystallization process and solid-state analysis of crystalline productcitations
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article
IR spectroscopy together with multivariate data analysis as a process analytical tool for in-line monitoring of crystallization process and solid-state analysis of crystalline product
Abstract
<p>Crystalline product should exist in optimal polymorphic form. Robust and reliable method for polymorph characterization is of great importance. In this work, infra red (IR) spectroscopy is applied for monitoring of crystallization process in situ. The results show that attenuated total reflection Fourier transform infra red (ATR-FTIR) spectroscopy provides valuable information on process, which can be utilized for more controlled crystallization processes. Diffuse reflectance Fourier transform infra red (DRIFT-IR) is applied for polymorphic characterization of crystalline product using X-ray powder diffraction (XRPD) as a reference technique. In order to fully utilize DRIFT, the application of multivariate techniques are needed, e.g., multivariate statistical process control (MSPC), principal component analysis (PCA) and partial least squares (PLS). The results demonstrate that multivariate techniques provide the powerful tool for rapid evaluation of spectral data and also enable more reliable quantification of polymorphic composition of samples being mixtures of two or more polymorphs. This opens new perspectives for understanding crystallization processes and increases the level of safety within the manufacture of pharmaceutics.</p>