The complete Raman spectra of isotropically crystalline and amorphous polylactide (PLA) have been successfully obtained with the use of a Fourier transform instrument equipped with a near-IR laser source. The Raman spectra of PLA were recorded at a resolution of 4 cm−1 from a backscattering sampling geometry. The changes in band intensity and shape of Raman spectra in the crystalline PLA samples facilitated the quantification of the crystallinity, which was primarily determined by the change in enthalpy via differential scanning calorimetry (DSC). A comparison of quantitative analysis of crystallinity by a multivariate technique, partial least-squares (PLS), and a univariate method at the carbonyl stretching band is described. Quantitative analysis of PLA crystallinity was performed after the data preprocessing with the standard normal variate (SNV) method in the combined spectral regions 3100–2800 cm−1 and 2000–200 cm−1 that were determined by the analysis of the correlation spectrum. The use of the calibration model containing mostly 1% d-PLA samples to separately analyze the samples with 1% and 5% d-PLA is discussed. Superior results obtained from the multivariate over the univariate method make PLS the preferred method of choice in quantification of crystallinity. The standard error of prediction (SEP) for the analysis of 1% d-PLA samples with the use of the calibration model described is 0.85 (—J/g), and the SEP for 5% d-PLA samples is 1.35 (—J/g) with the outliers excluded. The discrepancy in analyzing these two types of PLA samples with the use of the same calibration model is also discussed.

Current efforts in the Process Analytical Chemistry and Control Technology group at Bell Laboratories, Lucent Technologies, have focused on the development of an online method for real-time characterization of organiccontaining effluents (principally trimethyamine (TMA) and methanol) produced during a high-temperature processing. On-line analysis of the gas streams was performed by combining FT-IR spectrometry with partial least squares (PLS) to obtain quantitative information for process control. The gas-phase infrared spectra were measured at a resolution of 16 cm -1 under atmospheric conditions. The correlation coefficients for all the components including water were larger than 0.999, and the standard errors of prediction were much less than 1% by weight. The effect of CO 2 on the predictability of other components is discussed. Results of our experiment showed that the predicted errors for TMA and methanol increased by as much as 10 and 15%, respectively, as the amount of CO 2 increased to 100% of the most intense absorption peak in the spectra.

The advantages of measuring open-path Fourier transform infrared (OP/FT-IR) spectra at low resolution are discussed both from a theoretical and experimental viewpoint. In general, the optimum combination of selectivity and sensitivity is found when the resolution is approximately equal to the average full-width at half height (FWHH) of the analytical bands. The FWHH of many bands in the vapor-phase spectra of molecules of medium size, such as chlorinated organic solvents, is approximately 20 cm', so that a resolution of 16 cm' is often found to yield the most accurate analytical results. The low baseline noise level found when spectra are measured at low resolution can allow room temperature deuterated triglycine sulfate pyroelectric bolometers to be used instead of liquid nitrogen cooled mercury cadmium telluride photodetectors for OP/FT-JR measurements.

The physical properties of ethylene-styrene (ES) copolymers, like many other copolymers, are determined primarily by copolymer composition. ES copolymers may also contain a small amount of polystyrene. It is important to quantify the copolymerized styrene and polystyrene in ES copolymers. The difficulty associated with this analysis, however, arises from the fact that copolymerized styrene and polystyrene have a similar infrared spectrum. The quantitative analysis of ethylene-styrene copolymers by the Fourier transform infrared (FT-IR) technique, combined with the partial least squares (PLS) method, is described. The use of the PLS method facilitates the analysis. The PLS factors, which are calculated iteratively to maximize the covariance between the independent variable and the dependent variable in PLS, remove the collinearity problem present in the original spectral data, and make this analysis possible. The standard error of calibration (SEC) for 60 samples included in the calibration is 0.19% for polystyrene and 0.48% for copolymerized styrene. The standard error of prediction (SEP) for polystyrene and copolymerized styrene, calculated from 120 samples that were excluded from the calibration, is 0.25 and 0.51%, respectively.