Published January 25, 2020 | Version 1.0
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R script for the automated generation of reaction coordinate diagrams (RCDs) of chemical reaction energies and transformation networks

  • 1. Tifany L.
  • 2. Paul G.


R script for the automated generation of reaction coordinate diagrams (RCDs) of chemical reaction energies and transformation networks. This R script is part of the supplementary information for Torralba-Sanchez TL, Bylaska EJ, Salter-Blanc A, Meisenheimer DE, Lyon MA, Tratnyek PG. Reduction of 1,2,3-trichloropropane (TCP): Pathways and mechanisms from computational chemistry calculations. Environ Sci : Processes Impacts. 2020. DOI: 10.1039/C9EM00557A.

RCDs are 2D figures in which reaction thermodynamic values (e.g., change in reaction Gibbs free energy, ΔGrxn) are plotted (y axis) vs. reaction coordinates (e.g., stages/reactions in a transformation pathway). RCDs are useful for graphically comparing the energetics of reaction pathways and activation energies (if transition states are included), and provide insight into reaction barriers and therefore kinetics.

The script given here automates the plotting of RCDs using R ( The script translates ΔGrxn data for large and complex networks of transformation pathways into RCD graphs. The script was originally written to generate RCDs for the transformation network of 1,2,3-trichloropropane (TCP, a halocarbon of environmental concern) presented in Figure 2 of Torralba-Sanchez et al. (citation above). The code was designed for easy adaptation to other chemical reactions and/or transformation networks.

Four files are provided as .zip or .rar archives. The contents of these archives include the same set of four files: (i) README.txt containing general instructions, (ii) ReactionCoordinateDiagram.r containing the R script, (iii) ReactionCoordinateDiagram_Input.csv as an example of the input data format, and (iv) ReactionCoordinateDiagram_Output.pdf as an example of the script output.


The authors' work in this area is supported by the Strategic Environmental Research and Development Program (SERDP), mainly through Project ER-1458, and secondarily by ER-2620 and -2621. The modeling portion of this research was performed using the Institutional Computing facility (PIC) at the Pacific Northwest National Laboratory (PNNL) and the Chinook, Barracuda, and Cascade computing resources at the Environmental Molecular Sciences Laboratory (EMSL). PNNL is operated by Battelle Memorial Institute for the U.S. Department of Energy (DOE). EMSL is a national scientific user facility, located at PNNL, and sponsored by the DOE's Office of Biological and Environmental Research (DE-AC06-76RLO 1830). We also acknowledge EMSL for supporting the development of NWChem.


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Is supplement to
Journal article: 10.1039/C9EM00557A (DOI)