[Quantitative analysis of surface composition of polypropylene blends using attenuated total reflectance FTIR spectroscopy].
The surface composition and structure of solid organic polymers influence many of their properties and applications. Oligomers such as poly(ethylene glycol) (PEG), poly(methyl methacrylate) (PMMA) poly(butyl methacrylate) (PBMA) and their graft copolymers of polybutadiene and polypropylene were used as the macromolecular surface modifiers of polypropylene. The compositions on surface and in bulk of the polypropylene (PP) blends were determined quantitatively using attenuated total reflectance FTIR spectroscopic (ATR-FTIR) technique with a variable-angle multiple-reflection ATR accessory and FTIR measurements, respectively. By validating by Lambert-Beer law, 1103 and 1733 cm(-1) can be used to represent modifiers characteristic absorbance band to determine quantitatively the surface composition of modifiers including poly(ethylene glycol) and carbonyl segment in PP blends, respectively. The determination error can be effectively eliminated by calibrating wavelength and using absorption peak area ratio as the calibrating basis for the quantitative analysis. To minimize the effect of contact between the polymer film and the internal reflection element on the results of absolute absorbance, the technique of "band ratioing" was developed, and it was testified that the error of the peak area ratios of interest can be reduced to 5% or below, which was suitable for ATR-FTIR used as a determining quantitative tool for surface composition. The working curves were then established and used to calculate the composition of the responding functional groups in the film surface of the PP blends. The depth distribution of modifiers on the surface of blend films also can be determined by changing the incident angle of interest on the basis of the equation of the depth of penetration of the excursion wave in ATR spectra. The results indicated that ATR-FTIR can be used to determine quantitatively the surface composition and distribution of modifiers with reproducible and reliable measurement results.
Chen
Han-jia
HJ
School of Science, Shantou University, Shantou 515063, China. hjchen@stu.edu.cn
Zhu
Ya-fei
YF
Zhang
Yi
Y
Xu
Jia-rui
JR