Characterization of pharmaceutical powder blends using in situ near-infrared chemical imaging

2014 ◽  
Vol 108 ◽  
pp. 244-257 ◽  
Author(s):  
Juan G. Osorio ◽  
Gina Stuessy ◽  
Gabor J. Kemeny ◽  
Fernando J. Muzzio
2007 ◽  
Vol 15 (3) ◽  
pp. 137-151 ◽  
Author(s):  
Hua Ma ◽  
Carl A. Anderson

A critical parameter in the evaluation of pharmaceutical dosage forms by hyperspectral imaging is the level of magnification. If the magnification (as set by the optical objective) is inadequate to resolve the relevant features, then the value of the imaging is diminished; if the magnification level is greater than is required, then the field of view is unnecessarily reduced. The purpose of this study was to determine an optimum magnification level for the study of powder mixing. Relevant features in this system include distribution of individual components within samples and the overall content of a given sample. In the present study, three magnification levels of near infrared (NIR) chemical imaging objectives were evaluated for their effects on imaging a blend of pharmaceutical materials (powders). High, medium and low objective magnification levels were investigated by comparing the resulting blend surface images of a two-component (salicylic acid and lactose) pharmaceutical powder mixture. Multiple images from high and medium magnification were concatenated so that an equivalent field of view was obtained for all magnification levels. Univariate images, principal component analysis score images, partial least squares predicted images and spectra extracted from different intensity regions in the area images were analysed qualitatively and quantitatively for comparison. A series of images spanning a strip across the centre of the circular field were collected at each magnification level and compared with respect to surface features elucidated and area of blend surface imaged. Analyses of images indicate that the three magnification levels delineate the component distribution for this particular powder system similarly. Images obtained at the low magnification level demonstrated adequate resolution and provided the broadest view of the blend surface. It is concluded that the low optical magnification level was adequate for the system being studied and is the preferred mode for pharmaceutical powder blend image data collection for this system.


2017 ◽  
Vol 10 (6) ◽  
pp. 2077-2091 ◽  
Author(s):  
Sabina Assan ◽  
Alexia Baudic ◽  
Ali Guemri ◽  
Philippe Ciais ◽  
Valerie Gros ◽  
...  

Abstract. Due to increased demand for an understanding of CH4 emissions from industrial sites, the subject of cross sensitivities caused by absorption from multiple gases on δ13CH4 and C2H6 measured in the near-infrared spectral domain using CRDS has become increasingly important. Extensive laboratory tests are presented here, which characterize these cross sensitivities and propose corrections for the biases they induce. We found methane isotopic measurements to be subject to interference from elevated C2H6 concentrations resulting in heavier δ13CH4 by +23.5 ‰ per ppm C2H6 ∕ ppm CH4. Measured C2H6 is subject to absorption interference from a number of other trace gases, predominantly H2O (with an average linear sensitivity of 0.9 ppm C2H6 per  % H2O in ambient conditions). Yet, this sensitivity was found to be discontinuous with a strong hysteresis effect and we suggest removing H2O from gas samples prior to analysis. The C2H6 calibration factor was calculated using a GC and measured as 0.5 (confirmed up to 5 ppm C2H6). Field tests at a natural gas compressor station demonstrated that the presence of C2H6 in gas emissions at an average level of 0.3 ppm shifted the isotopic signature by 2.5 ‰, whilst after calibration we find that the average C2H6 : CH4 ratio shifts by +0.06. These results indicate that, when using such a CRDS instrument in conditions of elevated C2H6 for CH4 source determination, it is imperative to account for the biases discussed within this study.


2016 ◽  
Vol 297 ◽  
pp. 349-356 ◽  
Author(s):  
Juan G. Osorio ◽  
Eduardo Hernández ◽  
Rodolfo J. Romañach ◽  
Fernando J. Muzzio

Author(s):  
Shi-Wei Hou ◽  
Si-Yu He ◽  
Jun Xie ◽  
Ming-You Li ◽  
Miao-Si Hong ◽  
...  
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