CADET is a fast and accurate solver for a comprehensive model family of biotechnological processes. Applications include chromatography, filtration, crystallization, and fermentation. The open source software implements state-of-the-art mathematical algorithms and scientific computing techniques.


Cite this software

What CADET can do for you

CADET is developed at the Institute of Bio- and Geosciences 1 (IBG-1) of Forschungszentrum Jülich (FZJ). The heart of the CADET software is a fast and accurate solver for a comprehensive model family. Typical applications include but are not limited to chromatography, filtration, crystallization, and fermentation. CADET can handle arbitrary sequences and networks of unit operations, including reactors, tanks, tubes, pumps, valves, detectors, etc. The resulting models are solved at system level with state-of-the-art mathematical algorithms and scientific computing techniques. In addition to the solver, tools for parameter estimation and process optimization are provided.

Key Features:

  • Fast and accurate solution of strongly coupled partial differential algebraic equations (PDAE)
  • Computation of parameter sensitivities with algorithmic differentiation (AD)
  • Shared memory parallelization using Intel TBB
  • Python interface (recommended) and native MATLAB interface (deprecated)
  • Support of HDF5 and XML data formats
  • Flexible and extensible through modular design
  • Works on Windows, Linux, and Mac OS X
Logo of CADET
Programming languages
  • C++ 97%
  • CMake 3%
  • GPL-3.0-or-later
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Participating organisations

Forschungszentrum Jülich

Reference papers



We owe a special thanks to Eric von Lieres and the entire CADET team for making this valuable computational tool available to the scientific community.
Timothy Pabst et al. (2022): Evaluation of recent Protein A stationary phase innovations for capture of biotherapeutics.
The remarkable open-source and more variable toolbox named CADET was developed and successfully used for the modeling of affinity chromatography processes [...].
Ryunosuke Kitamura et al. (2022): Robustness assessment of cation-exchange chromatography with in-silico peak deconvolution in monoclonal antibody purification
For their educational and patient introduction to chromatographic modelling and the training I received in using the CADET system, I would like to thank Eric von Lieres, Juliane Diedrich and William Heymann of Forschungszentrum Jülich. The discussions about mixing behaviors and the general capabilities of a system like CADET and the possibilities it provides were eye-opening.
Jürgen Beck (2018): Separation of BSA multimers on anion exchange media: chromatographic modelling including extra-column effect
We also thank Prof. Eric von Lieres of Forschungszentrum Jülich for making CADET available for the simulations.
Ohnmar Khanal et al. (2018): Multi-column displacement chromatography for separation of charge variants of monoclonal antibodies
The authors would like to acknowledge excellent support from Dr. Eric von Lieres and his research group at Forschungszentrum Jülich GmbH Germany with respect to CADET simulations.
Lalita Kanwar Shekhawat et al. (2015): Enablers for QbD implementation: Mechanistic modeling for ion-exchange membrane chromatography