On-line determination of the conversion in a styrene bulk polymerization batch reactor using near-infrared spectroscopy

Infrared Spectroscopic Quantification of Methacrylation of Hyaluronic Acid: A Scaffold for Tissue Engineering Applications

Methacrylated hyaluronic acid (MeHA) has been used extensively in tissue engineering and drug delivery applications. The degree of methacrylation (DM) of HA impacts hydrogel crosslinking, which is of pivotal importance for cell interactions. The methacrylation reaction occurs over several hours, and DM is currently assessed post reaction and after dialysis of the solution, using nuclear magnetic resonance (1H NMR) data. Thus, there is little control over exact DM in a specific reaction. Here, infrared (IR) spectroscopy in attenuated total reflection (ATR) mode was investigated as an alternate modality for assessment of the DM of HA hydrogels, including during the reaction progression. Attenuated total reflection is a low-cost technique that is widely available in research and industry labs that can be used online during the reaction process. Strong correlations were achieved with IR-derived peak heights from dialyzed and lyophilized samples at 1708 cm-1 (from the methacrylic ester carbonyl vibration), and 1H NMR values ( R = 0.92, P = 6.56E-11). Additional IR peaks of importance were identified using principal component analysis and resulted in significant correlations with the 1H NMR DM parameter: 1454 cm-1 ( R = 0.85, P = 2.81E-8), 1300 cm-1 ( R = 0.95, P = 4.50E-14), 950 ( R = 0.85, P = 3.55E-8), 856 cm-1 ( R = 0.94, P = 1.20E-12), and 809 cm-1 ( R = 0.93, P = 3.54E-12). A multiple linear regression model to predict 1H NMR-derived DM using the 1708, 1300, and 1200 cm-1 peak heights as independent variables resulted in prediction with an error of 3.2% using dialyzed and lyophilized samples ( P < 0.001). Additionally, a multilinear regression model to predict the DM in undialyzed liquid MeHA samples obtained during the reaction process using similar peak height positions as independent variables resulted in a prediction error of 0.81% ( P < 0.05). Thus, IR spectroscopy can be utilized as an alternate modality to 1H NMR for quantification of the DM of MeHA while sampling either on-line during the methacrylation reaction as well as in post-lyophilized products. This could greatly simplify workflow for tissue engineering and other applications.

Monitoring of the thickness of ultraviolet-cured pigmented coatings and printed layers by near-infrared spectroscopy

Near-infrared (NIR) reflection spectroscopy was used for the determination of the thickness or the coating weight, respectively, of white-pigmented acrylic coatings and layers of printing inks. The thickness of coatings was studied in the range from 5 to 60 microm, whereas the coating weights of the printed layers covered a range between 1 to 5 g m(-2). Quantitative analysis of the spectral data relied on partial least squares (PLS) regression. A thickness gauge or gravimetry, respectively, were used to obtain reference data. Calibration models were typically based on six factors. The corresponding root mean square errors of prediction (RMSEP) were found to be on the order of 0.87 for coatings and 0.38 for printed layers. Monitoring of the coating thickness under process conditions was carried out on a pilot-scale roll coating machine. In order to simulate thickness changes during a coating process, either the nip between the applicator rolls or the web speed was varied. Data with high precision (standard deviation approximately 1 microm for coatings, approximately 0.4 g m(-2) for printed layers) and an excellent correlation with off-line reference data were obtained. The investigations have shown that NIR spectroscopy can be used for process control in coating and curing technology.

Application of multivariate curve resolution to chemical process control of an esterification reaction monitored by near-infrared spectroscopy

Multivariate curve resolution-alternating least squares (MCR-ALS) methodology was applied to near-infrared spectroscopy (NIR) data for the esterification reaction between glycerol and a mixture of caprylic and capric acids. Batch reaction processes were conducted either at the laboratory scale or at an industrial plant, while NIR data were obtained from samples withdrawn during the reaction processes. The process has been monitored via two typical parameters for this type of reaction, namely, the acid value (AV) and the hydroxyl value (OHV). Spectral and concentration profiles were estimated by applying soft-modeling MCR-ALS to a column-wise augmented data matrix with pure spectra of the components, and concentration values for the acid were used as a soft-equality constraint. The estimated concentration profiles have been compared with the AV and OHV values, and the estimated spectral profiles were used to predict the concentration profiles for new batches. Good results have been obtained in terms of RMSE for the prediction of AV and OHV.