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Analysis of Synthetic Polymers and Copolymers by Pyrolysis- Gas Chromatography/Mass Spectrometry
(2005)
Structural analysis and the study of degradation properties are important in order to understand and improve performance characteristics of synthetic polymers and copolymers in many industrial applications. Polymers/copolymers are inherently difficult to analyze because of their high molecular weight and lack of volatility. Traditionally, various analytical techniques are used to characterize polymers/copolymers including physical testing (rheological testing), thermogravimetric analysis (TGA), electron microscopy, Fourier transform infrared (FTIR) spectroscopy, size-exclusion chromatography (SEC)/gel permeation chromatography (GPC), and mass spectrometry (MS). Often, time consuming sample preparation, including hydrolysis, dissolution, or derivatization is needed before analysis.
Gas chromatography with flame-ionization detection (FID) and gas chromatography-mass spectrometry (GC/MS) has been used for structure elucidation of long-chain primary n-alkyl amines after derivatization with trifluoroacetic anhydride (TFAA). Electron impact ionization- (EI) and positive chemical ionization- (PCI) mass spectra of trifluoroacetylated derivatives of the identified nalkyl amines are presented. The corrosion inhibiting n-alkyl amines were applied in the investigation of a new anticorrosive and antifouling formulation for water-steam circuit of energy systems in the power industry. The presented results are part of an EU-funded international collaboration with partners from research institutes and industry from Poland, Lithuania, Romania, France and Germany (EUREKA project BOILTREAT E!2426).
Timely recognition of threats can be significantly supported by security assistance systems that work continuously in time and call the security personnel in case of anomalous events in the surveillance area. We describe the concept and the realization of an indoor security assistance system for real-time decision support. The system consists of a computer vision module and a person classification module. The computer vision module provides a video event analysis of the entrance region in front of the demonstrator. After entering the control corridor, the persons are tracked, classified, and potential threats are localized inside the demonstrator. Data for the person classification are provided by chemical sensors detecting hazardous materials. Due to their limited spatio-temporal resolution, a single chemical sensor cannot localize this material and associate it with a person. We compensate this deficiency by fusing the output of multiple, distributed chemical sensors with kinematical data from laser-range scanners. Considering both the computer vision formation and the results of the person classification affords the localization of threats and a timely reaction of the security personnel.