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Updated: Feb 2, 2026

Absolute Quantum Yield Measurement of Powder Samples
Published on: May 12, 2012
Achieving performance improvement of PAT in continuous powder blending process: A collective consideration of
Yifei Liu1, Zhong Xue2, Liping Chen3
1Department of Chinese Medicine Informatics, Beijing University of Chinese Medicine, Beijing 100029, China; Beijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing 102488, China; Beijing Key Laboratory of Chinese Medicine Manufacturing Process Control and Quality Evaluation, Beijing University of Chinese Medicine, Beijing 100029, China.
Abstract:
Real-time monitoring of continuous powder blending, particularly in the case of botanical drugs containing cohesive natural product powders, remains a considerable challenge due to limitations in spectral data quality and model robustness. In this paper, an integrated strategy that combines a sampling interface design with chemometrics optimization was employed to develop a robust online near-infrared (NIR) spectroscopy for monitoring the continuous blending of a quaternary botanical drug formulation with low concentration of active pharmaceutical ingredient (API) (i.e. the paeonol at 0.33-3.0% w/w). The inclined chute interface was designed to reduce its cross-sectional area, thereby stabilizing powder flow, increasing the sample mass at the NIR probe, and improving spectral data quality by minimizing baseline drift and noise. The Gaussian smoothing in conjunction with standard normal variate (SNV) transformation was identified as the optimal spectral preprocessing procedure. Seven variable selection algorithms were compared, and the successive projections algorithm (SPA) yielded the most effective and interpretable wavelengths that were consistent with the characteristic absorption bands of the paeonol. The optimal PLS model based on the data collected from the improved interface exhibited superior predictive performance compared with the model built from the initial sampling interface, achieving the validation R2 of 0.9858 (vs. 0.9529) and ratio of performance to deviation (RPD) of 7.26 (vs. 5.51). The uncertainty profile showed the uncertainty limits were all within acceptable limits of ±20% at each studied concentration, verifying the accuracy and reliability of the established NIR method. In conclusion, this work established a comprehensive framework that addressed both the physical aspects of process sampling and the chemometric modeling strategies to enable accurate, real-time monitoring of challenging cohesive powder blends in continuous pharmaceutical manufacturing.
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