pyCHNOSZ

Author: Dr. Grayson Boyer, GEOPIG Lab, Arizona State University

CHNOSZ is a package written by Dr. Jeff Dick for performing thermodynamic calculations in aqueous geochemistry and biogeochemistry. pyCHNOSZ is a wrapper for CHNOSZ that allows these calculations to be carried out in Python 3 Jupyter notebooks.

Features

The following CHNOSZ functions are supported in pyCHNOSZ:

• info - Search for chemical species by name or formula and retrieve their thermodynamic parameters.
• add_OBIGT - Add or overwrite species in the OBIGT thermodynamic database by supplying a comma separated value (csv) file with custom data.
• mod_OBIGT - Modify species in the OBIGT thermodynamic database. Optionally, supply a Pandas dataframe containing custom data.
• reset - reset data to default values.
• subcrt - Calculate standard state partial molal thermodynamic properties of reactions at elevated temperatures and pressures.
• basis - Define basis species of a chemical system.
• species - Define the species of interest in a system.
• equilibrate - Calculate equilibrium chemical activities of species from the affinities of formation of the species at unit activity.
• affinity - Calculate the chemical affinities of formation reactions of species.
• diagram - Plot equilibrium chemical activity (1-D speciation) or equal-activity (2-D predominance) diagrams as a function of chemical activities of basis species, temperature and/or pressure.
• And more. See the documentation for pyCHNOSZ

Requirements

This package must be installed into an environment with an R installation. See these instructions for installing R with Anaconda. Additionally, the CHNOSZ package for R must be installed (see instructions below).

Installation

Installing CHNOSZ

Open an R session. Install the CHNOSZ package with:

r install.packages("CHNOSZ")

Once CHNOSZ is installed you may quit the R session.

Installing pyCHNOSZ

Install pyCHNOSZ using pip:

$ pip install pyCHNOSZ

Usage

Import pyCHNOSZ in your python code with: python import pyCHNOSZ

In the following examples, pyCHNOSZ functions are imported with: python from pyCHNOSZ import info, add_OBIGT, mod_OBIGT, reset, subcrt

Search for chemical species

The info() function can be used to look up chemical species by name or formula. If names or formulas are provided, database index integers are returned. A list of integers will look up chemical species by index and return a table of thermodynamic properties. See the info() function's original documentation to learn more about what this function can do. A few examples are shown below.

Look up the database index value of Fe+2:

python info("Fe+2")

Look up multiple chemical species:

python info(["HCO3-", "CH4"])

Define chemical states:

python info(["HCO3-", "CH4"], state=["aq", "gas"])

Search species by index values to look up their thermodynamic parameters.

python info([13, 872])

Nest info functions to look up thermodynamic properties directly from names or formulas:

python info(info("Fe+2"))

Look up and add a protein to the database:

python info("LYSC_CHICK")

Add or replace thermodynamic data in the database

See the original R documentation for add_OBIGT() and reset() for basic useage. A few examples are given below.

Load the SUPCRT92 database.

python a = add_OBIGT("SUPCRT92")

The variable a is assigned a list of integers corresponding to the indices of chemical species that are added or replaced in the OBIGT thermodynamic database used by pyCHNOSZ.

It is possible to add a custom table of thermodynamic parameters.

python a = add_OBIGT("my_custom_entries.csv") info(a) # confirm new entries have been added

The entries of my_custom_entries.csv would then be available for thermodynamic calculations with subcrt(), for example.

Reset thermodynamic database to its original configuration.

python reset()

Modify values in the thermodynamic database with mod_OBIGT():

python mod_OBIGT("HCO3-", G = -140283.7, Cp = -9) info(info("HCO3-"))

Calculate thermodynamic properties of reactions

See the original documentation for subcrt(). Useage in pyCHNOSZ is the same, except python lists are used in place of R's vectors. The function produces a dictionary of results stored in pandas dataframes. An example is shown below for the reaction H_{2 (aq)} + 0.5 O_{2 (gas)} = H₂O_(liq) at 30 and 50 degrees C and 100 bars pressure:

python subcrt(species=["H2", "O2", "H2O"], coeff=[-1.0, -0.5, 1.0], state=["aq", "gas", "liq"], T=[30, 50], P=100)

Output is a python dictionary of dataframes: ``` subcrt: 3 species at 2 values of T (ºC) and P (bar) (wet) [energy units: cal]

{'reaction': coeff name formula state ispecies 62 -1.0 H2 H2 aq 62.0 2612 -0.5 oxygen O2 gas 2612.0 1 1.0 water H2O liq 1.0, 'out': T P rho logK G H S \ 1 30.0 100 1.000017 43.855086 -60832.380282 -67420.887872 -21.89070
2 50.0 100 0.992305 40.834419 -60379.262657 -67882.530994 -23.36663

       V         Cp  

1 -7.494052 -24.126268
2 -8.259704 -20.941879 } ```

More examples:

For more examples, like plotting activity and predominance diagrams, check out the pyCHNOSZ demo notebook.