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pyDMS

Python package for dual-mode sorption (DMS) analysis

https://raw.githubusercontent.com/SmithLabMIT/pyDMS/main/images/pyDMS_logo.png

pyDMS is a Python program for the computation of dual-mode sorption (DMS) parameters using linear free energy relationship (LFER) and Van’t Hoff constraints.

pyDMS is developed in the Smith Lab in the Department of Chemical Engineering at the Massachusetts Institute of Technology.

pyDMS documentation is hosted on Read the Docs.

The journal article describing pyDMS is published in AIChE J. which can be found here.

Features

  • Compute reproducible DMS parameters: \(C_\mathrm{H}^\prime\), \(k_\mathrm{D}\), and \(b\) with uncertainty via LFERs and van’t Hoff constraints.

  • Access computed results in Python objects or via the automatically output PDF.

  • Compute pure and mixed-gas sorption isotherms from the DMS parameters with uncertainty values.

  • Calculate ideal and mixed-gas sorption selectivities with uncertainty values.

  • Calculate fugacity from pressure via Virial and Peng–Robinson implementation.

Installation

pyDMS can be installed using:

  • conda: conda install package-not-yet-available

  • pip: pip install package-not-yet-available

Alternatively, users can install the latest version from GitHub, either directly:

python -m pip install git+https://github.com/SmithLabMIT/pyDMS.git

or by downloading the source code:

git clone https://github.com/SmithLabMIT/pyDMS.git
cd pyDMS
python -m pip install .

For developers, it is recommended to download the source code and install in editable mode by replacing python -m pip install . with python -m pip install -e ..

Citation(s)

If you used pyDMS, please cite:

Tapia, B. C.; Dean, P. A.; Yeo, J. Y.; Wu, A. X., Smith, Z. P. pyDMS: A Python package for the determination of physics-informed, reproducible dual-mode sorption (DMS) parameters. AIChE J. Accepted 2026.

We also recommend citing the following works which provide relevant background and theory on van’t Hoff sorption energetics, LFERs, and their application to constrained DMS optimization, respectively:

Koros, W. J.; Paul, D. R.; Huvard, G. S. Energetics of Gas Sorption in Glassy Polymers. Polymer 1979, 20 (8), 956–960. https://doi.org/10.1016/0032-3861(79)90192-7.

Freeman, B. D. Basis of Permeability/Selectivity Tradeoff Relations in Polymeric Gas Separation Membranes. Macromolecules 1999, 32 (2), 375–380. https://doi.org/10.1021/ma9814548.

Wu, A. X.; Drayton, J. A.; Mizrahi Rodriguez, K.; Benedetti, F. M.; Qian, Q.; Lin, S.; Smith, Z. P. Elucidating the Role of Fluorine Content on Gas Sorption Properties of Fluorinated Polyimides. Macromolecules 2021, 54 (1), 22–34. https://doi.org/10.1021/acs.macromol.0c01746.

License

Copyright © 2026 The Massachusetts Institute of Technology

This work is licensed under the 3-clause BSD license (see LICENSE).

Acknowledgements

This work was supported by a MathWorks Fellowship, NSF CAREER Award (no. 2146422), and the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Separation Science Program under Award DE-SC0023252.

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