ABSTRACT
Tablet coating thicknesses were estimated using several techniques such as weight gain and scanning electron microscopy (SEM), in comparison with acoustic microscopy and diffuse reflectance spectroscopy. Acoustic microscopy, used for the first time in such an application, is based on the physical phenomenon of ultrasound propagation through the materials and the echoes generated by their interfaces. Based on the time of flights (TOFs) of the echoes from the coating surface and the tablet, it is possible to calculate the coating thickness. In order to evaluate the accuracy and robustness of these methods, drug tablets were coated with Kollicoat SR polymer for several times, so that to prepare tablets with different coating thicknesses. Tablets with 3, 6 and 9 wt% coating material have been prepared and based on SEM micrographs it was found that the tablet coating thickness is 71.99 ± 1.2 µm, 92.5 ± 1.7 µm and 132.3 ± 2.1 µm, respectively (SEM analysis). The tablet coating thicknesses measured with acoustic microscopy and infrared diffuse reflectance spectroscopy, were in agreement with those obtained using SEM. This verifies that both techniques can be successfully applied for real time and non-destructive thickness measurements of tablet coating. Furthermore, both techniques, compared with SEM and weight gained measurements, are fast and fully automated.
Subject(s)
Tablets/chemistry , Technology, Pharmaceutical/methods , Acoustics , Microscopy/methods , Microscopy, Electron, Scanning , Polyvinyls/chemistry , Propylene Glycol/chemistry , Spectrophotometry, Infrared/methodsABSTRACT
The microsampling destructions caused by the sampling of analytical spectroscopic methods are generally not permitted to art objects. Consequently, the development of nondestructive analysis techniques is a necessity. In this work we present a set of signal processing and artificial intelligence techniques which support the operation of a novel device developed for the nondestructive identification of art objects. The proposed device combines ultraviolet, visible, near infrared, and midinfrared spectroscopy in diffuse reflectance mode to identify the materials that exist in each paint layer of an artwork.
