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ARC - Automated Rate Calculator is a software written in Python for automating quantum electronic structure calculations and determination of thermoproperties and reaction rates.
ARC is currently in beta (under development), and features are constantly being added. For example, it performs quite well for thermoproperties determination, yet reaction rates haven't been fully implemented yet.
In it's current version, ARC is meant to be run on a computer that can SSH into server/s with ESS (electronic structure software) installed. We do plan to eventually to make ARC compatible with running "locally" on a server.
ARC currently supports Gaussian, QChem, and Molpro, additional ESS support such as NWChem and Orca is planned.
Principally, ARC accepts 2D geometric representations of molecules (either xyz coordinates, SMILES, adjacency list, or RMG's Species / Molecule objects) and does the following:
- Generates numerous 3D conformers using RDKit and OpenBabel and rates them by energy using force fields
- Optimizes the best conformers at a low level DFT (or whatever specified by the user, see Advanced features)
- Optimizes the lowest energy conformer at a high level DFT (or whatever specified by the user, see Advanced features)
- Calculates frequencies, single point energies and performs 1D hindered rotor scans
- If a stable species has one or more imaginary frequencies ARC will perturb the geometry and search for a stable conformer. Alternatively, if a rotor scan shows that the initial geometry isn't the most stable conformation on the potential, ARC will change the respective dihedral angle and restart the jobs for the species.
- If any calculation fails, ARC automatically attempts to apply its troubleshooting methods
- Calculates thermoproperties (enthalpy, entropy, heat capacity) using Arkane
- Determines thermoproperties using RMG's database and generate parity plots for reality checks.
- The final output of ARC is mainly thermodynamic data for Species, and soon kinetic rates, see File structure for detailed description of all its output
Principally this GitHub repository should be cloned, and several packages including RMG must be installed.
See the Installation instructions
ARC can be run with an input file directly from the terminal, or can be executed using a script (such as via a Jupyter Notebook).
See Running ARC for detailed instructions
In addition to the running instructions, advanced features worth looking at are available.
Found a bug? Have comments? Issues should be reported in this GitHub repo on the issues page.
Contributions are most welcome! Contributions are in the form of a Pull Request, generally following the Contributor Guidelines of RMG.