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https://github.com/pauliacomi/awesome-adsorption

Awesome list of open source tools that can help simulate, treat understand or disseminate adsorption data.
https://github.com/pauliacomi/awesome-adsorption

List: awesome-adsorption

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Awesome list of open source tools that can help simulate, treat understand or disseminate adsorption data.

Awesome Lists containing this project

README 

        
# Adsorption Awesome [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)



Awesome list of open source / freely available tools that help treat,

understand, disseminate or simulate adsorption and adsorption-based processes in

porous materials.



What it does NOT contain:



- Proprietary / closed source programs or datasets

- Databases of structures of adsorbent materials

- General atomistic simulation software and related tools

- Stuff that you know and use but have not yet added here!



Go ahead and submit a PR if you found something interesting!



**Disclaimer**: I am the main maintainer of the pyGAPS package.



## Table of Contents



- [Free resources for learning about adsorption](#free-resources-for-learning-about-adsorption)

- [Adsorption data standardization](#adsorption-data-standardization)

- [Databases of adsorption data](#databases-of-adsorption-data)

- [Adsorption data treatment and material characterization](#adsorption-data-treatment-and-material-characterization)

- [Multicomponent adsorption](#multicomponent-adsorption)

- [Process design](#process-design)

- [Adsorption-specific molecular simulation](#adsorption-specific-molecular-simulation)

- [Interfaces with adsorption devices](#interfaces-with-adsorption-devices)



## Free resources for learning about adsorption



- [Interactive Module](https://learncheme.com/quiz-yourself/interactive-self-study-modules/adsorption/adsorption-introduction/) 

  from University of Colorado Boulder: excellent resource containing videos of

  annotated lecture slides, simple equilibrium simulations and multiple choice questions.



## Adsorption data standardization



- [Adsorption Information Format](https://adsorptioninformationformat.com/): A

  universal file format for gas adsorption experiments, similar to a

  crystallographic CIF file.



## Databases of adsorption data



- [NIST ISODB](https://adsorption.nist.gov): A centralized database of pure and

  multicomponent adsorption isotherms from experimental published data.

- [Bison 20](https://pubs.acs.org/doi/10.1021/acs.iecr.0c05398?goto=supporting-info):

  A collection of multicomponent adsorption isotherms. Some has been integrated

  in the [NIST ISODB](https://adsorption.nist.gov).

- [MOFX-DB](https://mof.tech.northwestern.edu/): An online computational database for pure and multicomponent adsorption in MOFs and zeolites. 



## Adsorption data treatment and material characterization



- [pyGAPS](https://pygaps.readthedocs.io/): General purpose adsorption data

  treatment, characterization and isotherm fitting, including specific surface

  area, pore size distributions, isosteric enthalpy, isotherm model fitting and

  more.

- [pyGAPS-gui](https://github.com/pauliacomi/pyGAPS-gui): Graphical user

  interface for [pyGAPS](https://pygaps.readthedocs.io/), offering interactive

  simple-to-use access to all its functionality.

- [BETSI-gui](https://github.com/fairen-group/betsi-gui): BET Surface

  Identification, an interactive graphical program for determining BET

  area using a statistical multiple region fit approach in combination with

  the Rouquerol criteria.

- [BEaTmap](https://github.com/PMEAL/beatmap): BET surface area analysis from

  adsorption data implementing the Rouquerol criteria and offering useful

  visualisations. An interactive Web App version exists allowing for easy use.

- [SESAMI](https://pubs.acs.org/doi/10.1021/acs.jpcc.9b02116), a script

  to estimate surface areas of porous materials using either/both the BET and

  excess sorption work model and later extended with machine learned (ML) estimations of monolayers as

  [SESAMI ML](https://pubs.acs.org/doi/10.1021/acs.jpclett.0c01518).

  One may find the interfaces from the Kulik group useful for the

  [web](https://github.com/hjkgrp/SESAMI_web) and for a

  [GUI](https://github.com/hjkgrp/SESAMI_GUI).

- [Micromeritics](https://github.com/Micromeritics/micromeritics)-provided

  various adsorption calculations and other support tools for their instruments.

- [pyPUC](https://github.com/sblanky/pyPUC): pyPUC (Python Porosity Uptake

  Correlator) determines the optimum pore size range of some type of material

  for gas uptake in a pressure range. The calculation uses experimental data

  and a brute force first principles calculation.



## Multicomponent adsorption



- [pyIAST](https://github.com/CorySimon/pyIAST): predicts mixed-gas adsorption

  isotherms in a nanoporous material from pure-component gas adsorption

  isotherms using the Ideal Adsorbed Solution Theory (IAST).

- [pyGAPS](https://pygaps.readthedocs.io/) and

  [pyGAPS-gui](https://github.com/pauliacomi/pyGAPS-gui): integrate

  functionality of [pyIAST](https://github.com/CorySimon/pyIAST) and alongside

  providing other IAST functions, like selectivity vs. pressure and bulk to

  adsorbed fractional composition graphs.

- [IASTpp](https://github.com/Sangwon91/IASTpp): graphical software written in

  C++ for Ideal Adsorbed Solution Theory Calculations.

- [MPTA](https://github.com/RaphaelGervaisLavoie/MPTA): Numerical implementation

  of the Multicomponent Potential Theory of Adsorption in Python

- [MCIAST](https://github.com/eliasboegel/MCIAST): A numerical code on

  breakthrough curve modelling for multicomponent gas mixtures based on Ideal

  Adsorption Theory.

- [GraphIAST](https://github.com/ORC-WUR/GraphIAST): Graphical User Interface 

  Software for the pyIAST Ideal Adsorption Solution Theory code.

- [RUPTURA](https://github.com/iRASPA/RUPTURA): Command-line simulation package to 

  fit pure component isotherms, then compute breakthrough curves and IAST mixture 

  predictions.



## Process design



- [CADET](https://github.com/modsim/CADET): A modular, fast, and accurate

  simulation framework for (column) liquid chromatography breakthrough curves.

- [MAPLE](https://github.com/ArvindRajendran/MAPLE) (Machine-assisted Adsorption

  Process Learner and Emulator) and

  [PANACHE](https://github.com/ArvindRajendran/PANACHE) (Physics-based

  artificial neural network framework for adsorption and chromatography

  emulation), two neural network based codes that assist in simulating

  adsorption processes with and without requiring isotherm parameters.



## Adsorption-specific molecular simulation



- [RASPA](https://github.com/iRASPA/RASPA2): Classical molecular simulation

  code, particularly geared towards simulating adsorption and diffusion in

  nanoporous materials.

- [PorousMaterials.jl](https://github.com/SimonEnsemble/PorousMaterials.jl) A

  pure-Julia package for classical molecular modeling of adsorption in porous

  crystals.



## Interfaces with adsorption devices



- [NuMAT 3flex driver](https://github.com/numat/threeflex): a python package for

  interfacing with the Micromeritics 3Flex.