Welcome to the AIOMFAC website

This website is designed to provide access to the thermodynamic model AIOMFAC in the form of an interactive web application and to provide supporting information.

Overview

News and latest changes
Learn about the AIOMFAC model
How to use AIOMFAC-web
Run the model
Source code
Citation and references
Acknowledgments

News and latest changes ↑Top

This section lists important events and changes related to AIOMFAC-web in reverse chronological order.

October 09, 2026: AIOMFAC-web model update to v3.15. An minor bug was fixed (regression since v3.10). It affected calculations involving the partial dissociation of bicarbonate ions. We thank Kee-Youn Yoo for bringing this issue to our attention. Other changes in v3.15 include the use of a Neumaier-type pairwise summation function for certain numerically delicate composition summations (primarily a speed improvement over the previous approach used).
August 24, 2026: AIOMFAC-web model update to v3.14. This major version update includes the addition of new features summarized in the following.
(1) A SMILES (Simplified Molecular Input Line Entry System) input option for defining organic components has been added. SMILES are processed using the SMILES to AIOMFAC subgroups (S2AS) method developed by Amaladhasan et al. (2026).
(2) The default method for pure-component viscosity prediction has been changed to make use of a SMILES-based prediction of the glass transition temperature (T_g) via a machine learning method developed by Armeli et al. (2023). We thank the authors of Armeli et al. for making their model available to the community (see also their T_g Online Calculator website). This new option is by default applied to organic compounds entered via SMILES Input and to those selected from the Predefined List on the input form page. Users can deselect the machine-learning-based method under a new Calculation Options section of the input form, in which case the simpler method by DeRieux et al. (2018) will be used to estimate T_g (as until now). The machine-learning-based method will typically provide more reliable mixture viscosity predictions for organics-containing systems.
(3) As a consequence of the new calculation options, the AIOMFAC input file structure has slightly changed; however, the previous file formatting is compatible and remains supported for running the online model via file upload. For the older input files, the pure-component viscosity prediction will default to the method by DeRieux et al.
(4) The parameters for binary interactions among Ca⁺⁺ and NO₃^- ions have been updated to provide better agreement with available experimental data under conditions of concentrated aqueous Ca(NO₃)₂ solutions. We thank Jan-Hendrik Peters for initiating this improvement.
(5) The Hints & Examples page has been updated to reflect the changes introduced.
October 16, 2025: AIOMFAC-web model update to v3.13. An error concerning the calculation of solution viscosity, specific to mixtures involving aqueous CO₂ as a species, has been resolved. We thank Hanyi Seok for bringing this issue to our attention.
September 1, 2025: AIOMFAC-web model update to v3.12. This version update is based on the corresponding updated Fortran code release on https://github.com/andizuend/AIOMFAC. This version includes updated short-range and middle-range interaction parameter arrays. Specifically, the updated parameters are related to a subset of main group interactions involving the nitrogen-containing groups CNO₂ and ACNO₂ as well as a few interactions of ACOH and several estimated (by analogy) or fitted organic and ion interactions of the oxyethylene group CH₂OCH₂[PEG].
April 23, 2024: AIOMFAC-web model update to v3.10. This version update is based on the corresponding updated Fortran code release on https://github.com/andizuend/AIOMFAC and fixes an incorrect middle-range interaction parameter that was present in v3.01–v3.05. The incorrect parameter affected activity coefficient calculations of mixtures containing H⁺ and organics with ether, hydroperoxide and/or peroxide functionalities. We thank Florian Couvidat for reporting this issue.
Archive of "News and latest changes".

Learn about the AIOMFAC model ↑Top

Use the navigation bar on top or the following link to learn more about AIOMFAC, its concept, development, and range of applications.

How to use AIOMFAC-web ↑Top

The model version made available online, termed AIOMFAC-web, allows the calculation of activity coefficients in organic–inorganic mixtures – from simple binary solutions to complex multicomponent systems.

The Hints & Examples page offers a step-by-step guide on how to use AIOMFAC-web, as well as useful information referring to the mode of calculation. Different examples of AIOMFAC-web calculations and related output analysis are described. In addition, you will find helpful information regarding model error and warning messages, browser compatibility, and technical problems.

Run the model ↑Top

Go directly to the model input form, enter the data for your system of interest and run the model.

Source code ↑Top

The Fortran source code of the AIOMFAC-web model (version 2.20 or newer) as well as supporting information are availabe publicly under a GNU GPL license v3.0 via https://github.com/andizuend/AIOMFAC.

Citation and references ↑Top

If you use results from AIOMFAC-web calculations for scientific publications or other forms of reports, please cite this website and the scientific articles describing the model as detailed here.

Check the list of references given at the end of About AIOMFAC and the information in the text on that page to find a number of sources describing the AIOMFAC model and its various applications reported in the scientific literature.

Acknowledgments ↑Top

Starting as the PhD thesis project of Andreas Zuend at ETH Zurich back in 2004, the AIOMFAC model has been under development for many years by now, involving a number of project partners. This website is one of the more recent products of that development process, with the goal of making the model available to the wider community. We are grateful for the financial support received from the following funding agencies, enabling the research and development of the AIOMFAC model and this website over the past 17+ years:

– AIOMFAC model development

Swiss National Science Foundation (SNSF), project no. 200020-103651.
Swiss National Science Foundation (SNSF), project no. PA00P2_126227.
Competence Center Environment and Sustainability of the ETH Domain (CCES), project IMBALANCE.
Office of Science (SC, BER), US Department of Energy, grant DE-FG02-05ER63983.
US Environmental Protection Agency (EPA), STAR research assistance agreement RD-833749.
Electric Power Research Institute (EPRI).
ETH Zurich, Switzerland (ETHZ), research grant ETH-0210-1.
US National Science Foundation (NSF), grant AGS-1057183.
McGill University (Start-up Grant, A. Zuend)
Natural Sciences and Engineering Research Council of Canada (NSERC), Grants RGPIN/04315-2014 and RGPIN-2021-02688.
Fonds de recherche du Québec – Nature et technologies (FRQNT), Grant no. PR-286433.
Alfred P. Sloan Foundation (Chemistry of Indoor Environments) under prime award no. G-2020-13912 (MOCCIE).
The government of Canada through the federal Department of Environment and Climate Change (ECCC), grant no. GCXE20S049.

– Website & Server Hardware

US National Science Foundation (NSF), grant AGS-1057183.

Natural Sciences and Engineering Research Council of Canada (NSERC), grant RGPIN/04315-2014).

Future development and improvement of the AIOMFAC model and this website, as well as the maintenance of the technical infrastructure and services, will depend on funds available. If you would like to support our future projects financially or as a project partner, please contact us.