Abstract
We present the RUPTURA code (https://github.com/iraspa/ruptura) as a free and open-source software package (MIT license) for (1) the simulation of gas adsorption breakthrough curves, (2) mixture prediction using methods like the Ideal Adsorption Solution Theory (IAST), segregated-IAST and explicit isotherm models, and (3) fitting of isotherm models on computed or measured adsorption isotherm data. The combination with the RASPA software enables computation of breakthrough curves directly from adsorption simulations in the grand-canonical ensemble. RUPTURA and RASPA have similar input styles. IAST is implemented near machine precision but we also provide several explicit mixture prediction methods that are non-iterative and potentially faster than IAST. The code supports a wide variety of isotherm models like Langmuir, Anti-Langmuir, BET, Henry, Freundlich, Sips, Langmuir-Freundlich, Redlich-Peterson, Toth, Unilan, O'Brian & Myers, Asymptotic Temkin, and Bingel & Walton. The isotherm model parameters can easily be obtained by the fitting module. Breakthrough plots and animations of the column properties are automatically generated. In addition to highlighting the code, we also review all the developed techniques from literature for mixture prediction, breakthrough simulations, and isotherm model fitting, and provide a tutorial discussing the workflows.
Original language | English |
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Pages (from-to) | 893-953 |
Journal | Molecular Simulation |
Volume | 49 |
Issue number | 9 |
DOIs | |
Publication status | Published - 2023 |
Keywords
- Breakthrough
- fixed-bed
- IAST
- isotherm model
- RUPTURA
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Simulation input files and datasets for the article: "RUPTURA: Simulation Code for Breakthrough, Ideal Adsorption Solution Theory Computations, and Fitting of Isotherm Models"
Sharma, S. (Creator), Balestra, S. R. G. (Creator), Vlugt, T. J. H. (Creator), Baur, R. (Creator), Agarwal, U. (Creator), Zuidema, E. (Creator), Rigutto, M. (Creator), Calero, S. (Creator) & Dubbeldam, D. (Creator), TU Delft - 4TU.ResearchData, 14 Apr 2023
DOI: 10.4121/4943DC0F-D908-4215-89CE-B9A6163930D2.V1
Dataset/Software: Dataset