Linux, OSX, Windows
A code for calculating the standard state thermodynamic properties of substances and reactions at a given temperature and pressure.
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- Using a json database file
#!c++
int main()
{
// Create the batch object using a database file in JSON
ThermoFun::Batch batch("Resources/Databases/aq17-thermofun.json");
// Optional: set units, default units are in SI
batch.setPropertiesUnits({"temperature", "pressure"},{"degC","bar"});
// Optional: change default significant digits
batch.setPropertiesDigits({"gibbs_energy","entropy", "volume", "enthalpy", "temperature", "pressure"}, {0, 1, 2, 0, 0, 0});
// Retrieve the entropy of H2O
double H2Oentropy = batch.thermoPropertiesSubstance( 300, 2000, "H2O@", "entropy").toDouble();
// Retrieve the derivative of G with respect to T
double H2OdGdT = batch.thermoPropertiesSubstance( 300, 2000, "H2O", "entropy").toThermoScalar().ddt;
// Write results to a comma separate files for a list of T-P pairs, substances, and properties
batch.thermoPropertiesSubstance({{25, 1},{40, 1},{70, 100},{90, 100},{100, 100}}, // list of T-P pairs
{"Al+3", "OH-", "SiO2@"}, // list of substance symbols
{"gibbs_energy","entropy", "volume", "enthalpy"} // list of properties
).toCSV("results.csv"); // output
return 0;
}
- Using the database client and retrieving a ThermoDataSet from the remote database
#!c++
int main()
{
// Set the file path to the database connection and preferences file (provided in the Resources/ folder)
setDatabaseConnectionFilePath("fun-hubclient-config.json");
// Initialize a database client object
ThermoFun::DatabaseClient dbc;
// Retrieve list of records given a ThermoDataSet symbol
auto records = dbc.recordsFromThermoDataSet("psinagra07");
// Create a ThermoFun database using the records list
ThermoFun::Database db = databaseFromRecordList(dbc, records);
// Initialize an batch object using the database
ThermoFun::Batch batch (db);
// Optional set calculation and output preferences
ThermoFun::OutputSettings op;
op.isFixed = true;
op.outputSolventProperties = true;
op.reactionPropertiesFromReactants = false;
op.substancePropertiesFromReaction = false;
batch.setOutputSettings(op);
// Optional set units and significant digits
batch.setPropertiesUnits({"temperature", "pressure"},{"degC","bar"});
batch.setPropertiesDigits({ "reaction_gibbs_energy","reaction_entropy", "reaction_volume",
"reaction_enthalpy","logKr", "temperature", "pressure"}, {0, 4, 4, 4, 4, 0, 0});
batch.thermoPropertiesReaction({{25,1}}, {"AmSO4+", "MgSiO3@"}, {"reaction_gibbs_energy", "reaction_entropy",
"reaction_volume", "reaction_enthalpy", "logKr"}).toCSV("results.csv");
batch.thermoPropertiesReaction({0,20,50,75},{0,0,0,0},{"AmSO4+", "MgSiO3@"}, {"reaction_gibbs_energy", "reaction_entropy",
"reaction_volume", "reaction_enthalpy", "logKr"}).toCSV("results.csv");
}
- Using a json database file
#!Python
import thermofun as fun
import thermohubclient as hubclient
properties = fun.ThermoPropertiesSubstance
engine = fun.ThermoEngine("Resources/Databases/aq17-thermofun.json")
prop = engine.thermoPropertiesSubstance(373.15, 100000000, "H2O@")
print(prop.gibbs_energy.val)
print(prop.gibbs_energy.ddt)
print(prop.entropy.val)
print(prop.gibbs_energy.ddp)
print(prop.gibbs_energy.err)
print(prop.gibbs_energy.sta)
# Create the engine object using a database file in JSON
batch = fun.ThermoBatch("Resources/aq17new-format.json")
# Optional: change default units
batch.setPropertiesUnits(["temperature", "pressure"],["degC","bar"])
# Optional: change default significant digits
batch.setPropertiesDigits(["gibbs_energy","entropy", "volume", "enthalpy", "temperature", "pressure"], [0, 1, 2, 0, 0, 0])
H2Oentropy = batch.thermoPropertiesSubstance( 300, 2000, "H2O@", "entropy").toDouble()
print(H2Oentropy)
V = batch.thermoPropertiesSubstance( 250, 1000, "H2O@", "volume").toThermoScalar()
# Write results to a comma separate files for a list of T-P pairs, substances, and properties
batch.thermoPropertiesSubstance( [[25, 1],[40, 1],[70, 100],[90, 100],[100, 100]], # // list of T-P pairs
["Al+3", "OH-", "SiO2@"], # // list of substance symbols
["gibbs_energy","entropy", "volume", "enthalpy"] # // list of properties
).toCSV("results.csv") # // output
- Using the database client and retrieving a ThermoDataSet from the remote database
#!Python
hubclient.setDatabaseConnectionFilePath("Resources/fun-hubclient-config.json")
print("\n# Initialize a database client object\n")
dbc = hubclient.DatabaseClient()
print("\n# Retrieve list of records given a ThermoDataSet symbol\n")
records = dbc.recordsFromThermoDataSet("cemdata18")
print("\n# Create a ThermoFun database using the records list\n")
db = hubclient.databaseFromRecordList(dbc, records)
print("\n# Initialize an interface object using the database\n")
batch2 = fun.ThermoBatch(db)
print("\n# Optional: set the solvent symbol used for calculating properties of aqueous species\n")
batch2.setSolventSymbol("H2O@")
print("\n# Optional set calculation and output preferences\n")
op = fun.BatchPreferences()
op.isFixed = True
op.outputSolventProperties = True
op.reactionPropertiesFromReactants = False
op.substancePropertiesFromReaction = False
batch2.setBatchPreferences(op)
print("\n# Optional set units and significant digits\n")
batch2.setPropertiesUnits(["temperature", "pressure"],["degC","bar"])
batch2.setPropertiesDigits(["gibbs_energy","entropy", "volume",
"enthalpy","logKr", "temperature", "pressure"], [0, 4, 4, 4, 4, 0, 0])
print("\n# Do calculations and write output\n")
batch2.thermoPropertiesSubstance([[25,1]], ["Na(CO3)-", "Mg+2"], ["gibbs_energy", "entropy",
"volume", "enthalpy"]).toCSV("results_dbc.csv")
ThermoFun can be easily installed using Conda package manager. If you have Conda installed, install ThermoFun by executing the following command:
#!bash
conda install thermofun
Conda can be installed by installing Miniconda.
- Make sure you have g++, cmake and git installed. If not, install them (on Ubuntu Linux):
#!bash
sudo apt-get install g++ cmake git
- In a terminal, at the home directory level e.g.
<user>@ubuntu:~$copy-paste and run the following code:
#!bash
git clone https://github.com/thermohub/thermofun.git && cd thermofun
- In the terminal you should be in
~/thermofun$.
This option allows the user to build thermofun library that works with a user provided thermodynamic database file in json format and has only one thirdpary library dependency. To build thermofun with access to the thermohub thermodynamic database cloud and local server see bellow.
The thermofun library uses nlohmann/json.hpp as thirdparty dependency to parse database files in json format. To install the header only json library in a terminal ~/thermofun$ execute the following:
#!bash
sudo ./install-dependencies.sh
In the terminal ~/thermofun$, execute the following commands:
#!bash
mkdir build && \
cd build && \
cmake .. && \
make
To take advantage of parallel compilation use make -j3. 3 representing the number of threads.
For a global installation of the compiled libraries in your system, execute:
#!bash
sudo make install
This will install Thermofun library and header files in the default installation directory of your system (e.g, /usr/local/ ).
For a local installation, you can specify a directory path for the installed files as follows:
#!bash
cmake .. -DCMAKE_INSTALL_PREFIX=/home/username/local/
then execute:
sudo make install
To compile ThermoFun library in debug mode:
#!bash
cmake .. -DCMAKE_BUILD_TYPE=Debug
then execute:
sudo make install
(B) Build and install ThermoFun library (working with access to the local and cloud ThemroHub database)
This option builds thermofun library together with the dbclient, which provides access to the local and cloud thermohub databases, allowing specific a ThermoDataSet to be used or a selection on elements of the thermodynamic data.
Clone and install ThermoHubClient library
#!bash
git clone https://bitbucket.org/gems4/thermohubclient.git
cd thermohubclient
sudo ./install-dependencies.sh
mkdir build
cd build
cmake ..
make
For a global installation of the compiled library in your system, execute:
#!bash
sudo make install
This procedure uses Conda for handling all the dependencies of ThermoFun and builds ThermoFun for Windows, Mac OS X, and Linux.
Once you have conda installed execute:
#!bash
conda install -n base conda-devenv
This installs conda-devenv, a conda tool used to define and initialize conda environments.
Download ThermoFun from github
#!bash
git clone https://github.com/thermohub/thermofun.git && cd thermofun
In the next step we create a clean environment with all dependencies necessary to build ThermoFun, executing:
#!bash
conda devenv
In the next step we need to activate the thermofun environment
#!bash
conda activate thermofun
Remember to always activate thermofun environment whenever you use ThermoFun from C++ or Python. This is because conda will adjust some environment variables in your system.
Now we can proceed and build ThermoFun using CMake.