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Add predicted kij from Hemprich et al #379

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20 changes: 16 additions & 4 deletions parameters/pcsaft/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -6,14 +6,26 @@ The files named according to the pattern `NameYear.json` correspond to published
For most applications, we recommend using the recent parametrization by [Esper et al.](https://doi.org/10.1021/acs.iecr.3c02255) together with binary interaction parameters from [Rehner et al.](https://doi.org/10.1007/s10765-023-03290-3) In Python reading parameters from the two JSON files is done by

```python
from feos.pcsaft import PcSaftParameters
from feos.pcsaft import Parameters

params = PcSaftParameters.from_json(
params = Parameters.from_json(
["acetone", "hexane"],
"esper2023.json",
"rehner2023_binary.json"
)
```

For mixtures that lack binary interaction parameters in [Rehner et al.](https://doi.org/10.1007/s10765-023-03290-3), the predicted interaction parameters by [Hemprich et al.]() might be a good starting point. Because of the number of mixtures (> 1 M) they are not stored as JSON file, but rather as sqlite database.

```python
from feos.pcsaft import Parameters

params = Parameters.from_json(
["acetone", "hexane"],
"hemprich2026.db"
)
```

For some applications (e.g., aqueous systems) more specialized parametrizations are required. See below for a full list of PC(P)-SAFT pure-component parameter sets available in the repository.

## Individual Parameters
Expand All @@ -33,15 +45,15 @@ For some applications (e.g., aqueous systems) more specialized parametrizations
## Group-Contribution (GC) Methods
Parameters can also be constructed from group-contribution methods. In Python only and if you have [`rdkit`](https://pypi.org/project/rdkit/) installed in your environment, you can generate parameters directly from a SMILES code:
```Python
PcSaftParameters.from_json_smiles(
GcParameters.from_json_smiles(
["CCC(C)=O"],
"sauer2014_smarts.json",
"sauer2014_homo.json"
)
```
or
```Python
PcSaftParameters.from_json_smiles(
GcParameters.from_json_smiles(
[Identifier(name="2-butanone", smiles="CCC(C)=O")],
"sauer2014_smarts.json",
"sauer2014_homo.json"
Expand Down