RMG

RMG generates detailed chemical kinetic models to predict and analyze reaction networks in gas-phase, liquid-phase, and heterogeneous catalysis systems using thermochemical and kinetic data.

Key Features:

• Automatic Model Generation: Automates creation of detailed kinetic models by leveraging a comprehensive database of thermochemical and kinetic parameters.
• Compatibility with Python 3: RMG v3.0 is compatible with Python 3 to enable integration with contemporary cheminformatics and machine learning packages.
• Heterogeneous Catalysis Support: Extends modeling capabilities beyond gas- and liquid-phase systems to include heterogeneous catalysis models.
• Uncertainty and Sensitivity Analysis: Implements local and global uncertainty analysis alongside traditional first-order sensitivity analyses.
• Extensive Thermochemistry and Kinetics Database: Provides a significantly expanded database covering a wider variety of chemical species and reactions.
• Parallelization and On-the-fly Quantum Calculations: Supports parallel processing during reaction generation and incorporates on-the-fly quantum calculations.
• Molecule Isomorphism Optimization: Uses a novel molecule isomorphism approach to improve computational performance for large chemical systems.

Scientific Applications:

• Combustion science: Generation and analysis of large kinetic mechanisms for combustion reaction networks.
• Atmospheric chemistry: Construction of reaction models for atmospheric chemical processes and pollutant formation.
• Astrochemistry: Modeling complex reaction networks relevant to interstellar and planetary chemistry.
• Materials science: Mechanistic model generation for reaction processes relevant to materials synthesis and degradation.
• Catalyst design: Exploration and analysis of heterogeneous catalytic reaction mechanisms to inform catalyst development.
• Environmental modeling: Development of kinetic models to support environmental fate and reactive transport studies.

Methodology:

Automated generation of kinetic mechanisms from a database of thermochemical and kinetic parameters; parallel reaction generation; on-the-fly quantum calculations; local and global uncertainty analysis and first-order sensitivity analysis; molecule isomorphism algorithm for performance optimization.