The material research of reverse paintings on glass combines infrared spectroscopy and liquid chromatography–mass spectroscopy to investigate the binders. Observation methods (macro- and microphotography) and the scanning electron microscopy with...
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Making Cross Polarization Magic Angle Spinning Quantitative: A Solid‐State NMR/Multivariate Curve Resolution‐Alternating Least Squares Approach for Quantifying Crystalline and Amorphous Phases
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A broadly applicable and robust solid-state NMR approach, combined with multivariate curve resolution-alternating least squares, is presented to overcome the limitations of traditional methods. By leveraging advanced spectral deconvolution, it ensures accurate quantification of crystalline and amorphous active pharmaceutical ingredients phases, even without reference spectra of the pure forms.
Accurate quantification of both crystalline and amorphous phases of active pharmaceutical ingredients is crucial for ensuring drug efficacy and stability. However, amorphous content quantification poses significant challenges using traditional analytical techniques. To overcome these limitations, this work introduces a novel method combining solid-state nuclear magnetic resonance (SSNMR) with multivariate curve resolution-alternating least squares(MCR-ALS). Tested on mebendazole and indomethacin as model compounds, this approach enables accurate and robust quantification of crystalline and amorphous phases by leveraging the full spectral deconvolution through advanced multivariate analysis, overcoming the intrinsic challenges of cross polarization magic angle spinning (CPMAS) quantification. The approach allows for accurate quantification by either using reference spectra of the pure forms as constraints or extracting the spectral contributions directly from mixture data, making it applicable even when pure components are not available. While demonstrated in pharmaceuticals, this fast, robust, and user-independent approach is broadly applicable for solid-state quantification across various fields.
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