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pyGAPS: A Python-Based Framework for Adsorption Isotherm Processing and Material Characterisation

revised on 19.08.2019, 12:31 and posted on 19.08.2019, 16:24 by Paul Iacomi, Philip L. Llewellyn
Material characterisation through adsorption is a widely-used laboratory technique. The isotherms obtained through volumetric or gravimetric experiments impart insight through their features but can also be analysed to determine material characteristics such as specific surface area, pore size distribution, surface energetics, or used for predicting mixture adsorption. The pyGAPS (python General Adsorption Processing Suite) framework was developed to address the need for high-throughput processing of such adsorption data, independent of the origin, while also being capable of presenting individual results in a user-friendly manner. It contains many common characterisation methods such as: BET and Langmuir surface area, t and α plots, pore size distribution calculations (BJH, Dollimore-Heal, Horvath-Kawazoe, DFT/NLDFT kernel fitting), isosteric heat calculations, IAST calculations, isotherm modelling and more, as well as the ability to import and store data from Excel, CSV, JSON and sqlite databases. In this work, a description of the capabilities of pyGAPS is presented. The code is then be used in two case studies: a routine characterisation of a UiO-66(Zr) sample and in the processing of an adsorption dataset of a commercial carbon (Takeda 5A) for applications in gas separation.


Horizon 2020 No. 641887 (acronym DEFNET)


Email Address of Submitting Author


Laboratoire MADIREL, UMR 7246, Aix-Marseille Université / CNRS, 13013 Marseille, France



ORCID For Submitting Author


Declaration of Conflict of Interest

No conflict of interest

Version Notes

Added ORCID, chemrxiv DOI and updated references