New publication: “Kinetic modelling and steady-state optimization of cooling crystallization by continuous oscillatory baffled crystallizer”

Migyan Zhao, Tao Liu, Bo Song, Ji Fan, Xiongwei Ni, Zoltan K. Nagy and Rolf Findeisen

2025/06/30

Kinetic modelling and steady-state optimization of cooling crystallization by continuous oscillatory baffled crystallizer

Abstract

To address an open issue of sufficiently describing crystallization kinetics in a continuous oscillatory baffled crystallizer (COBC), a comprehensive kinetic modelling method is proposed in this paper, along with a steady-state optimization approach (SOA) for operating the COBC. Taking into account the axial dispersion of crystal quantity (ADCQ), velocity dispersion of crystal population (VDCP), and growth rate dispersion (GRD), a non-ideal plug flow micro-distribution model (NPF-MDM) is firstly established, which could be used to predict the crystal size distribution (CSD) and mean crystal size (MCS) in each zone of COBC. The model parameters are estimated by heterogeneous tracer experiments and continuous cooling crystallization (CCC) experiments in a real COBC named DN15. Based on the established NPF-MDM, an SOA is provided for operating the COBC. The tube length distribution across different temperature zones of COBC is optimized to determine the maximum attainable region of product MCS. By introducing an objective function related to the target crystal size and the CSD width of product crystals, a sensitivity analysis (SA) is presented to identify the critical operating conditions (COCs), including the seed recipe and net flow rate. Subsequently, the SA-based SOA is carried out. A growth optimizer algorithm is offered to solve the related nonconvex optimization problems. Experiments on the CCC of L-glutamic acid (LGA) via DN15 are performed to validate the proposed modelling and SOA.

DOI: https://doi.org/10.1016/j.cej.2025.164978