Abstract
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.
Highlights
Production processes in chemical, pharmaceutical, or biotechnological industries typically require the separation of products from side products or impurities
When considering the many advanced operating modes mentioned above, this gives rise to an unmanageable number of specific process models and optimization schemes that may have to be implemented when seeking for an optimal process for a given separation task
We demonstrate the setup of a simple ProcessModel and OptimizationProblem for the case of a two-component separation by batch chromatography, which is the simplest and most widely used operating concept
Summary
Production processes in chemical, pharmaceutical, or biotechnological industries typically require the separation of products from side products or impurities. The use of multiple columns gives rise to various concepts ranging from clever series or parallel arrangements of multiple batch columns [10,11], over pseudo-continuous processes, up to the many variants of the powerful continuous simulated moving bed (SMB) concept Details on such advanced chromatographic operating modes are given, for example, in [2,3,12]. When considering the many advanced operating modes mentioned above, this gives rise to an unmanageable number of specific process models and optimization schemes that may have to be implemented when seeking for an optimal process for a given separation task Against this background, a general-purpose tool is needed that allows an efficient and flexible handling of the different subtasks in the development of optimal chromatographic processes. The code can be obtained from https://github.com/fau-advanced-separations/CADET-Process
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