Skip to main content
All tools

Tools · Fluids & Thermodynamics

Hansen Solubility Parameters

Estimate Hansen δD/δP/δH from SMILES and rank solvents by HSP distance, RED, and Flory–Huggins χ

Open in the appRun via API

Hardware and price

Price per run

What a typical run reserves from your wallet: the catalog's expected runtime on each piece of hardware × your plan's per-second rate. Larger inputs reserve more, and you're charged only for the seconds the job actually runs.

Hansen Solubility Parameters: reservation per run, USD
HardwareTypical runtimeBasicStarterProEnterprise
CPUDefault2 min$0.017$0.0096$0.006$0.0036

In workflows

Chain it with other steps.

Each input and output has a data kind, so the builder only connects steps that fit.

Inputs

  • Molecules (list)SMILES
  • Molecules (list) · optionalSMILES

Outputs

  • ArchiveZIP
  • TableCSV
  • TableCSV
  • MoleculesSMILES

References

The method behind it.

  1. Emmanuel Stefanis, Costas Panayiotou (2008). Prediction of Hansen Solubility Parameters with a New Group-Contribution Method. International Journal of Thermophysics. doi:10.1007/s10765-008-0415-z (opens in a new tab)
  2. Charles M. Hansen (2007). Hansen Solubility Parameters. CRC Press. doi:10.1201/9781420006834 (opens in a new tab)
  3. Thomas Lindvig, Michael L. Michelsen, Georgios M. Kontogeorgis (2002). A Flory–Huggins model based on the Hansen solubility parameters. Fluid Phase Equilibria. doi:10.1016/s0378-3812(02)00184-x (opens in a new tab)
  4. Manuel Díaz de los Ríos, Rubén Murcia Belmonte (2022). Extending Microsoft excel and Hansen solubility parameters relationship to double Hansen’s sphere calculation. SN Applied Sciences. doi:10.1007/s42452-022-04959-4 (opens in a new tab)
  5. Abdulelah S. Alshehri, Anjan K. Tula, Fengqi You et al. (2022). Next generation pure component property estimation models: With and without machine learning techniques. AIChE Journal. doi:10.1002/aic.17469 (opens in a new tab)
  6. Risdon W. Hankinson, George H. Thomson (1979). A new correlation for saturated densities of liquids and their mixtures. AIChE Journal. doi:10.1002/aic.690250412 (opens in a new tab)

Run via API

Submit it from your own code.

Use an API key from your account. The estimate uses your plan's rates; submitting reserves that amount from your wallet.

# Estimate the reservation for your plan (payload fields: see the API reference)
curl -X POST https://api.cognichem.com/api/v1/jobs/estimate \
  -H "X-Api-Key: $COGNICHEM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"job_type": "hansen-hsp", "resource": "cpu", "payload": {}}'

# Submit (retrying with the same Idempotency-Key never submits twice)
curl -X POST https://api.cognichem.com/api/v1/jobs/submit \
  -H "X-Api-Key: $COGNICHEM_API_KEY" \
  -H "Idempotency-Key: $(uuidgen)" \
  -H "Content-Type: application/json" \
  -d '{"job_name": "hansen-hsp-1", "job_type": "hansen-hsp", "resource": "cpu", "payload": { ... }}'
Payload fields and examples in the docs

Fluids & Thermodynamics

Related tools

  • Cantera

    Chemical kinetics, thermodynamics, and transport simulations for combustion and reacting flows

  • VLE / Flash

    Multicomponent vapor–liquid phase equilibrium with cubic EOS and UNIFAC or NRTL activity models

  • VLE Thermodynamic Consistency Checker

    Audit binary Txy or Pxy vapor–liquid equilibrium data with Gibbs–Duhem area, point, endpoint, and infinite-dilution tests

  • VLE Parameter Regression

    Fit binary NRTL interaction parameters to measured Txy or Pxy vapor–liquid equilibrium data

  • Solid–Liquid Equilibrium / Eutectic Diagram

    Binary liquidus curves, eutectic point, and solubility versus temperature with ideal, NRTL, or UNIFAC activity

  • RMG Mechanism Generator

    Generate Chemkin / Cantera reaction mechanisms with RMG-Py from species, T/P, and termination

All tools