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Publications¶
As an open-source project, CADET-Core relies on the support and recognition from users and researchers to thrive. Therefore, we kindly ask that any publications or projects leveraging the capabilities of CADET-Core acknowledge its creators and their contributions by citing an adequate selection of our publications.
General CADET-Core publications¶
Publication of CADET-Core with its current C++ architecture
Samuel Leweke and Eric von Lieres. Chromatography analysis and design toolkit (cadet). Computers & Chemical Engineering, 113:274–294, 2018. doi:10.1016/j.compchemeng.2018.02.025.
Original Publication of chromatography models and their FV discretization in CADET
Eric von Lieres and Joel Andersson. A fast and accurate solver for the general rate model of column liquid chromatography. Computers & Chemical Engineering, 34(8):1180–1191, August 2010. doi:10.1016/j.compchemeng.2010.03.008.
CADET-Core Numerics and Modeling¶
Publication on DG discretization of axial transport models (GRM, LRMP, LRM) in CADET-Core
Jan Michael Breuer, Samuel Leweke, Johannes Schmölder, Gregor Gassner, and Eric von Lieres. Spatial discontinuous galerkin spectral element method for a family of chromatography models in cadet. Computers & Chemical Engineering, 177:108340, 2023. doi:10.1016/j.compchemeng.2023.108340.
Publications on Crystallization models and their entropy-preserving FV discretization in CADET-Core
Wendi Zhang, Todd Przybycien, Jan Michael Breuer, and Eric von Lieres. Solving crystallization/precipitation population balance models in cadet, part ii: size-based smoluchowski coagulation and fragmentation equations in batch and continuous modes. Computers & Chemical Engineering, 192:108860, 2025. doi:10.1016/j.compchemeng.2024.108860.
Wendi Zhang, Todd Przybycien, Johannes Schmölder, Samuel Leweke, and Eric von Lieres. Solving crystallization/precipitation population balance models in cadet, part i: nucleation growth and growth rate dispersion in batch and continuous modes on nonuniform grids. Computers & Chemical Engineering, pages 108612, 2024. doi:10.1016/j.compchemeng.2024.108612.
Publications on Parameter sensitivites and (compressed) algorithmic differentiation
Andreas Püttmann, Sebastian Schnittert, Samuel Leweke, and Eric von Lieres. Utilizing algorithmic differentiation to efficiently compute chromatograms and parameter sensitivities. Chemical Engineering Science, 139:152–162, January 2016. doi:10.1016/j.ces.2015.08.050.
Andreas Püttmann, Sebastian Schnittert, Uwe Naumann, and Eric von Lieres. Fast and accurate parameter sensitivities for the general rate model of column liquid chromatography. Computers & Chemical Engineering, 56:46–57, September 2013. doi:10.1016/j.compchemeng.2013.04.021.
CADET-Core SELECTED APPLICATIONS AND USE-CASES¶
Juliane Diedrich, William Heymann, Samuel Leweke, Stephen Hunt, Robert Todd, Christian Kunert, Will Johnson, and Eric von Lieres. Multi-state steric mass action model and case study on complex high loading behavior of mab on ion exchange tentacle resin. Journal of Chromatography A, 1525:60–70, 2017. doi:10.1016/j.chroma.2017.09.039.
Qiao-Le He, Samuel Leweke, and Eric von Lieres. Efficient numerical simulation of simulated moving bed chromatography with a single-column solver. Computers & Chemical Engineering, 111:183–198, 2018. doi:https://doi.org/10.1016/j.compchemeng.2017.12.022.
Ronald Colin Jäpel and Johannes Felix Buyel. Bayesian optimization using multiple directional objective functions allows the rapid inverse fitting of parameters for chromatography simulations. Journal of Chromatography A, 1679:463408, 2022. doi:10.1016/j.chroma.2022.463408.
Hannah Lanzrath, Eric von Lieres, Ralf Metzner, and Gregor Johannes Huber. Analyzing Time Activity Curves from Spatio-Temporal Tracer Data to Determine Tracer Transport Velocity in Plants. September 2024. doi:10.2139/ssrn.4957804.
Johannes Schmölder and Malte Kaspereit. A Modular Framework for the Modelling and Optimization of Advanced Chromatographic Processes. Processes, 8(1):65, 2020. doi:10.3390/pr8010065.