The Rareytec platform is built on openly-licensed software and data. This page lists every external component we use, its license, and the citation it requires.
| Component | License | Use |
|---|---|---|
| Python | PSF License | Runtime language |
| RDKit | BSD-3-Clause | Cheminformatics: structure parsing, InChIKey, formula, 2D depiction |
| ugropy | MIT | UNIFAC / Dortmund group fragmentation from SMILES (ILP set-cover assignment) |
| thermo / chemicals / fluids | MIT | Build-time verified source for published UNIFAC parameters and independent validation oracle (Caleb Bell) |
| NumPy | BSD-3-Clause | Numerics |
| Flask / Jinja2 / Werkzeug | BSD-3-Clause | Web framework + templating + auth hashing |
| Bootstrap | MIT | User-interface layout |
| Plotly.js | MIT | σ-profile and VLE charts |
| PubChemPy | MIT | Chemical-name resolution via PubChem |
σ-profiles and σ-surfaces (COSMO-SAC cavity segments), dipole moments and molecular descriptors for the 53,078-component registry. Bundled (preinstalled) with the platform.
Cite: Jirasek et al., “CHAOS — A Consistent Large-scale Database for Sigma-Profiles and Other Molecular Descriptors,” arXiv:2511.19002; Zenodo doi:10.5281/zenodo.17691924. Licensed under CC-BY-4.0 (creativecommons.org/licenses/by/4.0/). Modified by Rareytec: indexed and reformatted into the component registry, with σ-profiles and cavity segments extracted for property prediction and 3-D visualisation. link
Experimental thermophysical data (VLE, LLE, SLE, excess enthalpy, activity coefficients, density, viscosity, …) shown alongside predictions and used for validation. Bundled (preinstalled) with the platform; every data set keeps its original literature citation and DOI. The bundled copy is the complete free public release (v2020-09-30), covering the 2003–2019 calendar years — the last freely distributed ThermoML bulk archive. Later data is available only under your own license (see “Importing your own licensed data” below).
Cite: Data from the NIST/TRC ThermoML Archive (doi:10.18434/mds2-2422), a work of the U.S. Government not subject to copyright in the United States and distributed by NIST for reuse. Archive/format: Chirico, Frenkel, Diky et al., “ThermoML: An XML-Based Approach for Storage and Exchange of Experimental and Critically Evaluated Thermophysical and Thermochemical Property Data,” J. Chem. Eng. Data. The underlying measurements are credited to their respective authors through the per-data-set citation shown with each set. link
Chemical identity — resolving names to structures.
Cite: Kim et al., “PubChem 2023 update,” Nucleic Acids Res. 2023, 51, D1373. link
Activity-coefficient model — original parameter set.
Cite: Hansen, Rasmussen, Fredenslund, Schiller, Gmehling, Ind. Eng. Chem. Res. 1991, 30, 2352–2355. Fredenslund, Jones, Prausnitz, AIChE J. 1975, 21, 1086.
Activity-coefficient model — published modified-UNIFAC (Dortmund) parameter matrix.
Cite: Constantinescu & Gmehling, “Further Development of Modified UNIFAC (Dortmund): Revision and Extension 6,” J. Chem. Eng. Data 2016, 61, 2738. Also in Gmehling, Kolbe, Kleiber, Rarey, “Chemical Thermodynamics for Process Simulation,” free companion site chemthermo.ddbst.com.
Activity-coefficient model — NIST critically-evaluated parameter set (89 main groups, 984 interactions).
Cite: Kang, Diky, Frenkel, “New modified UNIFAC parameters using critically evaluated phase equilibrium data,” Fluid Phase Equilibria 388 (2015) 128–141; doi:10.1016/j.fluid.2014.12.042.
Activity-coefficient model — machine-learning completion of the published original-UNIFAC parameter table.
Cite: Hayer, Wendel, Mandt, Hasse, Jirasek, “Advancing thermodynamic group-contribution methods by machine learning: UNIFAC 2.0,” Chemical Engineering Journal 504 (2025) 158667; arXiv:2408.05220.
SMILES → UNIFAC / Dortmund subgroup assignment.
Cite: ugropy: an optimal functional-group identification package, Ind. Eng. Chem. Res. 2025; doi:10.1021/acs.iecr.5c02552.
These are not bundled and never redistributed by Rareytec. If your organisation already holds a license, they can be connected on your own installation and read live under that license — their data never enters our database or a delivered build.
If you or your organisation owns a TDE license, its experimental SOURCE archive (compounds, references, pure & binary measurements) can be imported as a private data source on your installation (user or company layer). Import feasibility has been verified — TDE's database is technically readable (older versions are a Microsoft Access/Jet file; newer ones via the Access database engine).
Import feasibility verified.
If you or your organisation is entitled to DIPPR, its pure-component constants and temperature-dependent correlations can be connected as a private source under your license (user or company layer).
Not yet tested — import from the DIPPR distribution format has not been verified.
If you or your organisation holds a DDB license, its experimental phase-equilibrium, excess-property and pure-component data can be connected as a private source under your license (user or company layer) — read live on your installation and shown alongside our predictions.
Not yet tested — import from the DDB distribution format has not been verified, and connection is subject to the terms of your DDB license.
The free DDBST online search reports WHAT data exist for a system (data banks, set/point counts, temperature and pressure ranges) without revealing any values. DDBST states explicitly that “no copyright is reserved for the search results,” so the platform may run these lookups automatically and cache the availability tables. Value ranges DDBST masks as “(hidden)” are shown as such — the platform never tries to infer values from availability metadata. To obtain the data itself: request a quote from DDBST, or use your own DDB license (export the system as PPDS in the Dortmund Data Bank application and import the file here).
Sources that are free to consult but not openly licensed (the Korea Thermophysical Properties Data Bank KDB; the NIST Chemistry WebBook, whose Standard Reference Data is copyrighted under the U.S. SRD Act unlike the public-domain ThermoML archive) are searched and retrieved only when you ask, for your specific system, into your project only. Each user’s retrieval is a small, task-scoped extraction under the lawful-user provisions of database law; the platform keeps no shared cache and never pools such retrievals across users or into the shipped baseline. Every dataset carries the source’s requested citation.
Any external query necessarily sends your component identities (name/CAS/structure) to the external source’s server. Projects can be flagged confidential — at creation or any time later — which disables all AUTOMATIC external queries; you can still query explicitly with a click.
Data is kept in three separate databases by provenance and entitlement, so the redistributable baseline is never mixed with tenant- or user-licensed data.
The clean, redistributable baseline: Rareytec’s own Rarey–Nannoolal and COSMO-SAC predictions over the public component registry, the CHAOS σ-profiles, and the free public NIST/TRC ThermoML experimental archive (2003–2019). Everything here is open-licensed or public-domain.
Data the organisation is entitled to and chooses to share in-house: values imported under the company’s own licenses, and project data that has been reviewed and promoted (see below). Private to the deployment; never redistributed by Rareytec.
Where each user works: imported data files (IK-CAPE / DDB exports, ThermoML, Reaxys, PPDS, CHEMCAD .ccsim / .nf), manual entries, and regressed parameters — held per project and used for that user’s own calculations and exports.
Propose Pending review Audited & published to the company bank — with a full who/when/source audit trail.
Proprietary, paywalled commercial databases whose licenses restrict USE — not merely redistribution. To keep the platform’s data provenance clean and unencumbered we do not use them for any purpose, including internal development or validation. DIPPR data, where a user is entitled to it, is accessed only per-user under that user’s own license and is never stored in our database.
We use the PUBLISHED modified-UNIFAC (Dortmund) parameter table (J. Chem. Eng. Data 2016 revision; free companion download of the Gmehling et al. textbook) — see Model parameters above. What we do NOT use is the consortium-only complete/current commercial matrix distributed by DDBST to members, nor the Dortmund Data Bank experimental databank.
Last reviewed 2026-07-08. If you believe a source is mis-attributed, contact Rareytec.