Experimental implementation of a Quality-by-Control (QbC) framework using a mechanistic PBM-based nonlinear model predictive control involving chord length distribution measurement for the batch cooling crystallization of L-ascorbic acid

L-ascorbic acid is synthetized in large industrial scale from glucose and marketed as an immune system strengthening agent and anti-oxidant ingredient. The overall yield of conversion of the precursor glucose to L-ascorbic acid is limited, therefore the crystallization is a critically important step of the L-ascorbic acid production from economic point of view. It is widely accepted that the crystal size distribution (CSD) influences numerous relevant macroscopic properties of the final crystalline product and it also significantly affects the downstream operations. The present paper discusses the chord length distribution (CLD, which is directly related to the CSD) control, during the crystallization of L-ascorbic acid from aqueous solution. Batch crystallization process is employed, which is the classical, and still dominant, operation in fine chemical and pharmaceutical industries. A comparative experimental study of two state-of-the-art Quality-by-Control (QbC) based crystallization design approaches are presented: (1) a model-free QbC based on direct nucleation control (DNC) and (2) a model-based QbC using a novel nonlinear model predicative control (NMPC) framework. In the first investigation, the DNC, a process analytical technology based state-of-the-art model free control strategy, is applied. Although, DNC requires minimal preliminary system information and often provides robust process control, due to the unusual crystallization behavior of L-ascorbic acid, it leads to long batch times and oscillatory operation. In a second study the benefits of model-based QbC approach are demonstrated, based on using a NMPC approach. A population balance based crystallization process model is built and calibrated by estimating the nucleation and growth kinetics from concentration and CLD measurements. A projection based CSD to CLD forward transformation is used in the estimation of nucleation and growth kinetics. For robustness and adaptive behavior, the NMPC is coupled with a growing horizon state estimator, which is aimed to continuously improve the model by re-adjusting the kinetic constants. The study demonstrates that the model-based QbC framework can lead to rapid and robust crystallization process development with the NMPC system presenting good control behavior under significant plant model mismatch (PMM) conditions

Experimental investigation of the effect of scale-up on mixing efficiency in oscillatory flow baffled reactors (OFBR) using principal component based image analysis as a novel noninvasive residence time distribution measurement approach

Oscillatory flow strategies through baffled tubular reactors provide an efficient approach in improving process kinetics through enhanced micromixing and heat transfer. Known to have high surface area to volume ratios, oscillatory flow baffled reactors (OFBR) generate turbulence by superimposing piston driven oscillatory flow onto the net flow generated by a pump. By tuning the oscillating parameters (amplitude and frequency), one can tailor the residence time distribution of the system for a variety of multiphase applications. Using a microscope camera, principal component image analysis, and pulse tracer injections, a novel noncontact approach has been developed to experimentally estimate dispersion coefficients in two geometrically different systems (DN6 and DN15, Alconbury Weston Ltd.). The paper also introduces for the first time a novel scaled-down version of the commercially available DN15 OFBR, the DN6 (about 10 times smaller scale), and provides a comprehensive investigation of the effect of oscillation parameters on the residence time distributions (RTD) in both systems. The oscillation amplitude was found to have a significant positive correlation with the dispersion coefficient with 1 mm providing the least amount of dispersion in either system. Oscillation frequency had a less significant impact on the dispersion coefficient, but optimal operation was found to occur at 1.5 Hz for the DN6 and 1.0 Hz for the DN15. Until now, OFBR literature has not distinguished between piston and pump driven flow. Pump driven flow was found to be ideal for both systems as it minimizes the measured dispersion coefficient. However, piston driven turbulence is essential for avoiding particle settling in multi-phase (solid-liquid) systems and should be considered in applications like crystallization