CHNOSZ

Thermodynamic Calculations and Diagrams for Geochemistry

What is it?

The CHNOSZ package for R offers an integrated set of tools for thermodynamic calculations in geochemistry and compositional biology. Thermodynamic properties are taken from a database for minerals and inorganic and organic aqueous species including biomolecules, or from amino acid group additivity for proteins (Dick et al., 2006). High-temperature properties are calculated using the Berman-Brown (1985) equations for minerals and the revised Helgeson-Kirkham-Flowers (1981) equations of state for aqueous species. The HKF equations are augmented with the Deep Earth Water (DEW) model (Sverjensky et al., 2014) and estimates of parameters in the extended Debye-Hückel equation (Manning et al., 2013) to calculate standard-state properties and activity coefficients for given ionic strength at high pressure (to 60 kb). Functions are provided to define a system using basis species, automatically balance reactions, calculate the chemical affinities of formation reactions for selected species, calculate equilibrium activities, and plot the results on chemical activity diagrams.

canprot is a package that uses CHNOSZ for compositional and thermodynamic analysis of proteomic datasets.

An example

After Yang et al., 2018.

Getting started

Download R from the Comprehensive R Archive Network (CRAN). Launch an R session, then use these commands to install and load the package and run the examples from the documentation.

install.packages("CHNOSZ")
library(CHNOSZ)
data(thermo)
examples()

Download and documentation

Around the web

canprot package

Download canprot from Github or CRAN. The online manual and the vignettes from the package can be viewed here:

See the papers in PeerJ (2016, 2017) for more information.

About

CHNOSZ is free software made available under the GPL.

The maintainer of this package is Jeffrey Dick. Please contact him at j3ffdick@gmail.com.

To cite CHNOSZ in publications, use this reference: Dick, 2008. The thermodynamic database is made possible by the work of many different authors. If you publish the results of calculations using any of these data, please cite the primary data sources! For a list of references, use the thermo.refs() function in the package, or access the table of references here.


Last updated: 2018-04-11