"The model in teqp requires the user to specify the values of ``sigma``, ``epsilon/kB``, and ``m`` for each substance. A very few substances are hardcoded in teqp, for testing purposes. "
"The model in teqp requires the user to specify the values of ``sigma``, ``epsilon/kB``, and ``m`` for each substance. A very few substances are hardcoded in teqp, for testing purposes. "
]
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"The Python class is here: :py:class:`PCSAFTEOS <teqp.teqp.PCSAFTEOS>`"
]
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...
@@ -113,6 +123,7 @@
...
@@ -113,6 +123,7 @@
}
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...
...
%% Cell type:markdown id:f406bbb5 tags:
%% Cell type:markdown id:f406bbb5 tags:
# PC-SAFT
# PC-SAFT
The PC-SAFT implementation in teqp is based on the implementation of Gross and Sadowski (https://doi.org/10.1021/ie0003887), with the typo from their paper fixed. It does NOT include the association contribution, only the dispersive contributions.
The PC-SAFT implementation in teqp is based on the implementation of Gross and Sadowski (https://doi.org/10.1021/ie0003887), with the typo from their paper fixed. It does NOT include the association contribution, only the dispersive contributions.
The model in teqp requires the user to specify the values of ``sigma``, ``epsilon/kB``, and ``m`` for each substance. A very few substances are hardcoded in teqp, for testing purposes.
The model in teqp requires the user to specify the values of ``sigma``, ``epsilon/kB``, and ``m`` for each substance. A very few substances are hardcoded in teqp, for testing purposes.
%% Cell type:raw id:d9efd027 tags:
The Python class is here: :py:class:`PCSAFTEOS <teqp.teqp.PCSAFTEOS>`
Fine-tuned values of $k_{ij}$ can be provided when instantiating the model. A complete matrix of all the $k_{ij}$ values must be provided. This allows for asymmetric mixing models in which $k_{ij}\neq k_{ji}$.
Fine-tuned values of $k_{ij}$ can be provided when instantiating the model. A complete matrix of all the $k_{ij}$ values must be provided. This allows for asymmetric mixing models in which $k_{ij}\neq k_{ji}$.
%% Cell type:code id:a32c41b5 tags:
%% Cell type:code id:a32c41b5 tags:
``` python
``` python
k_01=0.01;k_10=k_01
k_01=0.01;k_10=k_01
kmat=[[0,k_01,0],[k_10,0,0],[0,0,0]]
kmat=[[0,k_01,0],[k_10,0,0],[0,0,0]]
teqp.PCSAFTEOS(coeffs,kmat)
teqp.PCSAFTEOS(coeffs,kmat)
```
```
%% Output
%% Output
<teqp.teqp.PCSAFTEOS at 0x26ec5dde870>
<teqp.teqp.PCSAFTEOS at 0x26ec5dde870>
%% Cell type:markdown id:ca52e844 tags:
%% Cell type:markdown id:ca52e844 tags:
## Superancillary
## Superancillary
The superancillary equation for PC-SAFT has been developed, and is much more involved than that of the cubic EOS. As a consequence, the superancillary equation has been provided as a separate package rather than integrating it into to teqp to minimize the computational overhead. It can be installed from PYPI with: ``pip install PCSAFTsuperanc``
The superancillary equation for PC-SAFT has been developed, and is much more involved than that of the cubic EOS. As a consequence, the superancillary equation has been provided as a separate package rather than integrating it into to teqp to minimize the computational overhead. It can be installed from PYPI with: ``pip install PCSAFTsuperanc``
