Calibration-free estimates of batch process yields and detection of process upsets using in situ spectroscopic measurements and nonisothermal kinetic models: 4-(dimethylamino)pyridine- catalyzed esterification of butanol.

Abstract

In this paper, we report the use of an NIR fiber-optic spectrometer with a high-speed diode array for calibration-free monitoring and modeling of the reaction of acetic anhydride with butanol using the catalyst 4-(dimethylamino)pyridine in a microscale batch reactor. Acquisition of spectra at 5 ms/scan gave information relevant for modeling these fast batch processes with a single multibatch kinetic model. Nonlinear fitting of a first-principles model directly to the reaction spectra gave calibration-free estimates of time-dependent concentration profiles and pure component spectra. The amount of catalyst was varied between different batches to permit accurate estimation of its effect in the multiway model. A wide range of different models with increasing complexity could be fit to each batch individually with low residuals and apparent low lack of fit. However, only one model properly estimated the concentration profiles when all five batches were fitted simultaneously in a multiway kinetic model. Inclusion of on-line temperature measurements and use of an Arrhenius model for the estimated rate constant gave significantly improved model fits compared to an isothermal kinetic model. Augmentation of prerun batches with data from an additional batch permitted model-based forecasts of reaction trajectories, reaction yield, reaction end points, and process upsets. One batch with added water to simulate a process upset was easily detected by the calibration free process model.