Goal
AutoMech is an Open-Source Programming Package designed for large-scale, high-level computational thermochemistry and kinetics. The goal of AutoMech Project is to improve combustion chemical modeling. In part this is accomplished by providing the large database of information we have already gathered with AutoMech and in part by providing tutorials and easy conda downloadfor outside users to explore their own mechanisms.
Automated Workflow
The packages run collectively through the mechdriver workflow for the automatic prediction of the kinetics for large sets of reactions via ab initio transition-state-theory based master-equation calculations. The primary input is simply the mechanism, a dictionary relating chemically identifiable species descriptors (e.g., SMILES or InChIs) to species labels in the mechanism, and a specification of the electronic structure and transition state theory models to be implemented.
Modular Design
While each library was designed with the holistic workflow in mind they can be used standalone. They include tools for chemical transformation and identification (AutoChem), input, output, and parsing of electronic structure and related operations (AutoIO), databasing of molecular properties (AutoFile), and mechansims manipulation and statistical thermodynamics calculations (mechanalyzer).
Resources
News
Argonne AutoMech developers recognized in 2023 Physical Sciences & Engineering (PSE) Excellence Award for Scientific Achievement [Fall 2023]. See full announcement. Initial AutoMech Publication Recognized as a Distinguished Paper at the 38th International Symposium on Combustion [Apr. 19, 2021]. See full announcement.
Acknowledgments
This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two U.S. Department of Energy (DOE) organizations, the Office of Science and the National Nuclear Security Administration, responsible for the planning and preparation of a capable exascale ecosystem including software, applications, hardware, advanced system engineering, and early test bed platforms to support the nation’s exascale computing imperative. This research was conducted using the Blues and Bebop computing resources, two high-performance computing clusters operated by the Laboratory Computing Resource Center at Argonne National Laboratory. This material is based on work supported by the DOE, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences at Argonne under Contract No. DE-AC02–06CH11357.
Contact
Sarah Elliott [email protected]