A Modular Framework for the Modelling and Optimization of Advanced Chromatographic Processes

A framework is introduced for the systematic development of preparative chromatographic processes. It is intended for the optimal design of conventional and advanced concepts that exploit strategies, such as recycling, side streams, bypasses, using single or multiple columns, and combinations thereof. The Python-based platform simplifies the implementation of new processes and design problems by decoupling design tasks into individual modules for modelling, simulation, assertion of cyclic stationarity, product fractionation, and optimization. Interfaces to external libraries provide flexibility regarding the choice of column model, solver, and optimizer. The current implementation, named CADET-Process, uses the software CADET for solving the model equations. The structure of the framework is discussed and its application for optimal design of existing and identification of new chromatographic operating concepts is demonstrated by case studies

Deducing kinetic constants for the hydrodechlorination of 4-chlorophenol using high adsorption capacity catalysts

Employing high surface area supports for catalytic hydrodechlorination can result in pronounced adsorption of reactants, intermediates and products. The influence of these sorption processes on the activity and selectivity upon 4-chlorophenol (4-CP) hydrodechlorination in aqueous solution has been studied using four commercial Pd/Al2O3 and Pd/AC catalysts at ambient pressure within the temperature range of 20-40°C ([4-CP]0=0.78-2.90mmolL-1, [catalyst]=1gL-1, 50NmLH2min-1). The adsorption capacity of the catalysts was independently evaluated. The Al2O3-based catalyst did not show any significant adsorption of those species whereas the activated carbon materials presented in all cases high uptakes (e.g. up to 2.4mmol4-CPgcat -1). In order to deduce true kinetic constants also for these catalysts, a kinetic model was developed, which accounts for the consecutive reaction and sorption processes in parallel. This expanded model resulted in a reasonable fit, can thus be used for comparison of different catalysts regardless their sorption capacity and allows predicting successfully the selectivity to the reaction productsThe authors gratefully acknowledge the funding of the German Research Council (DFG), which within the framework of its “Excellence Initiative” supports the Cluster of Excellence “Engineering of Advanced Materials” (www.eam.fau.de) at the University of Erlangen-Nurember

Separation of Molar Weight-Distributed Polyethylene Glycols by Reversed-Phase Chromatography—Analysis and Modeling Based on Isocratic Analytical-Scale Investigations

The separation of polyethylene glycols (PEGs) into single homologs by reversed-phase chromatography is investigated experimentally and theoretically. The used core–shell column is shown to achieve the baseline separation of PEG homologs up to molar weights of at least 5000 g/mol. A detailed study is performed elucidating the role of the operating conditions, including the temperature, eluent composition, and degree of polymerization of the polymer. Applying Martin’s rule yields a simple model for retention times that holds for a wide range of conditions. In combination with relations for column efficiency, the role of the operating conditions is discussed, and separations are predicted for analytical-scale chromatography. Finally, the approach is included in an efficient process model based on discrete convolution, which is demonstrated to predict with high accuracy also advanced operating modes with arbitrary injection profiles

Modelling diffusive transport of particles interacting with slit nanopore walls: The case of fullerenes in toluene filled alumina pores

Accurate modeling of diffusive transport of nanoparticles across nanopores is a particularly challenging problem. The reason is that for such narrow pores the large surface-to-volume ratio amplifies the relevance of the nanoscopic details and of the effective interactions at the interface with pore walls. Close to the pore wall, there is no clear separation between the length scales associated with molecular interactions, layering of the solvent at the interface with the pore and the particle size. Therefore, the standard hydrodynamic arguments may not apply and alternative solutions to determining average transport coefficients need to be developed. We here address this problem by offering a multiscale ansatz that uses effective potentials determined from molecular dynamics simulations to parametrise a four state stochastic model for the positional configuration of the particle in the pore. This is in turn combined with diffusivities in the centre of the pore and at the pore wall to calculate the average diffusion constant. We apply this model to the diffusion of fullerenes in a toluene filled slit nanopore and calculate the mean diffusion coefficient as a function of the pore size. We show that the accuracy of our model is affected by the partial slip of the toluene on the pore wall

Separation of Racemic Bicalutamide by an Optimized Combination of Continuous Chromatography and Selective Crystallization

A racemic mixture of bicalutamide, a drug substance used in the treatment of prostate cancer, was separated by simulated moving bed chromatography, with the objective of maximizing throughput at reduced outlet purity. The enriched extract stream was purified further by a crystallization process exploiting a shift in the eutectic composition. The optimal purity in between both process steps was identified. The separation scheme developed was validated on a scale of 600 g, and the results were compared to those of state-of-the art and discussed. The investigated scheme revealed a wide range of promising coupling conditions while showing superior productivities and enhanced process robustness