In Situ Monitoring of Polymorphic Transformations Using a Composite Sensor Array of Raman, NIR, and ATR-UV/vis Spectroscopy, FBRM, and PVM for an Intelligent Decision Support System
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Abstract
Raman spectroscopy, particle vision and measurement (PVM), and infrared spectroscopy have already been used singularly to detect nucleation and polymorphic transformations during crystallization processes as well as to analyze powder mixtures of multiple polymorphic forms. However, a comprehensive study and comparison of these techniques used simultaneously with integration of the signals during polymorphic transformation has not been performed to date. The aim of the present work is to compare the effectiveness of Raman spectroscopy, near-infrared spectroscopy, and PVM to detect nucleation and polymorphic transformations during crystallization processes. The information from focused beam reflectance measurement (FBRM) and attenuated total reflection ultraviolet/visible (ATR-UV/vis) probes were also used simultaneously in the same system to validate and integrate the results obtained by the other probes. This paper illustrates for the first time of the use of a composite sensor array (CSA) that truly integrates the signals from a variety of process analytical tools for better information extraction and more robust detection of various crystallization mechanisms. The proposed principal component analysis-based signal integration and the CSA can be used as the bases for an intelligent decision support system for crystallization processes, which can automatically detect various mechanisms occurring during the process, as well as a framework for the automated selection of the optimal minimal sensor configurations for the robust detection of these events.
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