Poly(ethy1ene vinyl acetate) (EVA) is a very common polymer used in hot melt adhesives. The rheological and thermal-mechanical properties of these adhesives are strongly related to the content of vinyl acetate (VA) incorporated into this random copolymer during polymerization. Results of in-line monitoring of VA content in flowing molten EVA polymers, using fiberoptic near infrared spectroscopy, shall be discussed in detail. In-line monitoring is not only desired for its numerous advantages (such as high quality products, lower waste, lower developmental cycle time, and lower costs) but also because it eliminates the sample handling concerns associated with molten polymers.

The concept of improved product quality and reduced costs has revolutionized analytical techniques in the polymer industry. It has brought in‐line analysis to the forefront, with near infrared (NIR) spectroscopy proving to be a very viable technique for such operations. A system for continuous in‐line near infrared monitoring of molten polymer blends, copolymers, and polymer reactions is being developed. The ultimate objective is to use this monitoring system to develop feedback control for polymeric processes. Experiments on blends of polystyrene and poly(phenylene oxide) have been performed by using a flow cell, located at the exit port of a single‐screw extruder. Qualitative analysis of spectral data has been substantiated by a variety of quantitative (multivariate) techniques. Robust calibration models, suitable for on‐line predictions, have been developed. The success of in‐line process analysis depends on the performance of fiber‐optic probes that are inserted into the process stream. These probes normally succumb to the demands of the rigorous process environment, typical of polymeric processes, i.e., high temperatures, high pressures, and adverse chemical conditions. Design and development of fiber‐optic probes that are capable of withstanding such harsh conditions have also been undertaken. Results will be reported on the polymeric systems and optical probes.

Peak absorbance changes correlated to changes in species concentration have been the norm in applied spectroscopy, while baseline shifts have been more of an inconvenience. Taking the first or second derivative of the spectra eliminates these baseline shifts. However, with multivariate techniques becoming more readily available, repeatable baseline changes may now be monitored and correlated to specific physical changes. This concept has been studied by monitoring the concentration of titanium dioxide (TiO2), a white inorganic filler, in molten poly(ethylene terepthalate) (PET). Various mixtures of filled and unfilled PET resins were run through a single‐screw extruder, and near infrared spectra were collected in‐line by using a flow cell, housing two fiber‐optic probes, and mounted downstream of the extruder. The presence of titanium dioxide caused the scattering of light that resulted in a systematic baseline shift. The baseline shifts were correlated to the TiO2 concentration data. Multivariate techniques involving the use of singular value decomposition (SVD) to perform partial least squares regression (PLS) were applied to quantitatively determine TiO2 content in the PET melt stream. Standard error of prediction (SEP) values of about 1% were obtained for a model based on two factors.