This package contains thermophysical property data for the following solutions used in absorption:
- NaOH-water
- LiBr-water
- LiCl-water
- CaCl2-water
If you want to use this package, please cite:
Höffner et al. 2025 - Potentials of absorption thermal energy storage systems in seasonal application
DOI: https://doi.org/10.18462/iir.tptpr2025.1130
pip install absorptionlib
# Import
from absorptionlib import NaOH, LiBr, LiCl, CaCl2
# Example Usage
p = 100000 # [Pa]
x = 0.4 # [%] = [kgNaOH / kgSolution]
t_sat = NaOH.saturation_temperature(x, p)
print(t_sat)Output
129.75
Each of the submodules have their own "in-line" documentation, which can be called by the "documentation"-method. Each thermophysical property function has a separate docstring, which can be called by the "explain"-method.
# How to get quick documentation on the modules
NaOH.documentation() # or
LiBr.documentation() # or
LiCl.documentation() # or
CaCl2.documentation()
# How to get quick documentation for functions
NaOH.explain("enthalpy") # returns docstring for NaOH.enthalpy
LiCl.explain("pTDiagram") # returns docstring for LiCl.pTDiagram| Function | Parameter 1 | Parameter 2 | Parameter 3 | Return Unit |
|---|---|---|---|---|
| saturation_temperature(P, x1) | P (Pa) | x (kgNaOH/kgSolution) | - | °C |
| saturation_pressure(x, T) | x (kgNaOH/kgSolution) | T (°C) | - | Pa |
| saturation_concentration(x, T) | P (Pa) | T (°C) | - | kg/kg |
| enthalpy(x, T) | x (kgNaOH/kgSolution) | T (°C) | - | kJ/kg |
| differential_enthalpy_AD(x, T) | x (kgNaOH/kgSolution) | T (°C) | - | kJ/kg |
| specific_heat_capacity(x, T) | x (kgNaOH/kgSolution) | T (°C) | - | kJ/kg·K |
| density(x, T) | x (kgNaOH/kgSolution) | T (°C) | - | kg/m³ |
| dynamic_viscosity(x, T) | x (kgNaOH/kgSolution) | T (°C) | - | Pa·s |
| diffusion_coefficient(x, T) | x (kgNaOH/kgSolution) | T (°C) | - | m2/s |
| thermal_conductivity(x, T, p) | x (kgNaOH/kgSolution) | T (°C) | p (Pa) | W/m·K |
| solubility_temperature(x) | x (kgNaOH/kgSolution) | - | - | W/m·K |
| Function | Description | Boolean Options + Defaults |
|---|---|---|
| hxDiagram() | shows hx-Diagram | |
| pTDiagram() | shows pT-Diagram | log=True, invT=True |
| editablePlot=False, show_percentages=True | ||
| crystallization_curve() | shows crystallization curve | return_data=False (if True, only data returned, no plot) |
As stated before, you can construct diagrams (pT-Diagram, hx-Diagram, crystallization-curve) with the package. For example:
NaOH.pTDiagram()
Note: The plots can be styled with usual matplotlib syntax. If the plot should be editable, use NaOH.pTDiagram(editablePlot=True). To reproduce the same-looking plot, set up matplotlib using:
# matplotlib font to geogia
import matplotlib.pyplot as plt
plt.rcParams['font.family'] = 'Georgia'
plt.rcParams['mathtext.fontset'] = 'custom'
plt.rcParams['mathtext.rm'] = 'Georgia'
plt.rcParams['mathtext.it'] = 'Georgia:italic'