Page 461 - Handbook of Materials Failure Analysis
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                  3.2 APPLICATION OF Py-GC/MS AND SEM IN FAILURE ANALYSIS
                  IN THE RUBBER AND AUTOMOTIVE INDUSTRY
                  Commonly used rubbers in industry are natural rubber (NR, polyisoprene), synthetic
                  polyisoprene (IR), polybutadiene (BR), styrene-butadiene copolymers (SBR), and
                  nitrile rubber (NBR). Nitrile rubber [poly(acrylonitrile-co-butadiene)] is a copoly-
                  mer containing 15-50% acrylonitrile, manufactured by emulsion polymerization
                  of acrylonitrile and 1,3-butadiene. It was invented at roughly the same time as
                  SBR (near the end of the 1920s) as a substitute for NR [4].
                     Commercial rubbers always contain low molecular weight additives. These com-
                  pounds are essential in processing and in order to obtain the end-use properties of
                  rubber. Additives may accelerate the vulcanization of rubber, can improve or modify
                  the mechanical properties (fillers and reinforcements), modify the color and appear-
                  ance (pigments, dyestuffs), give resistance to heat degradation (antioxidants and sta-
                  bilizers), and provide resistance to light degradation (UV stabilizers). They can also
                  improve the flame resistance of rubber. The identification and quantification are dif-
                  ficult tasks because of wide variety of different additives. Usually, mixtures of addi-
                  tives are used, and the added amount is often low and can be further decreased due to
                  degradation [4].
                     Most analytical methods reporting the determination of rubber additives require
                  previous extraction of the additives from the investigated material. For this purpose,
                  widely used sample preparation techniques such as liquid extraction with various sol-
                  vents, Soxhlet extraction, ultrasonic-assisted extraction, and pressurized liquid
                  extraction (like microwave assisted extraction, accelerated solvent extraction, super-
                  critical fluid extraction, and extraction processes employing autoclaves) are used [4].
                  All these methods are laborious and time-consuming. Subsequent analysis of the
                  extracted additives has been performed using FTIR and UV-spectroscopy or by using
                  chromatographic methods, like thin-layer chromatography, supercritical fluid chro-
                  matography, GC, high-performance liquid chromatography (HPLC), and capillary
                  electrophoresis (CE) or their conjunction with mass spectrometry (GC/MS,
                  HPLC/MS CE/MS). Also headspace-solid phase microextraction and thermal
                  extraction in conjunction with GC/MS have been applied for the extraction and iden-
                  tification of several common rubber additives. In such volatile removal techniques,
                  the additives are usually detected at temperatures below the decomposition temper-
                  ature of the rubber [4].
                     Analysis of the components of vulcanized rubber is a difficult, yet very important
                  process in analytical polymer chemistry. Each rubber compound in automobile
                  tire contains rubber polymers, sometimes one but often a blend of two or more.
                  The more commonly used polymers are NR, IR, BR, and SBR. SBR is generally used
                  in the tire treads of passenger cars and NR in the relatively large-sized tires of buses
                  and trucks [4].
                     The analytical Py-GC/MS has extended the range of possible tools for character-
                  ization of natural and synthetic rubbers. In the following failure analysis case, a new
                  passenger car tire and an operationally stressed passenger car tire with cracks and
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