Updating Our Understanding of JP-10 Decomposition Chemistry: A Detailed JP-10 Combustion Mechanism Constructed Using RMG, an Automatic Reaction Mechanism Generator

2010 ◽  
Author(s):  
Gregory Magoon ◽  
William Green ◽  
Oluwayemisi Oluwole ◽  
Hsi-Wu Wong ◽  
Simon Albo ◽  
...  
Keyword(s):  
Reaction Mechanism ◽  
Combustion Mechanism ◽  
Reaction Mechanism Generator ◽  
Decomposition Chemistry

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

2020 ◽  
Author(s):  
Mengjie Liu ◽  
Alon Grinberg Dana ◽  
Matthew Johnson ◽  
Mark Goldman ◽  
Agnes Jocher ◽  
...  
Keyword(s):  
Reaction Mechanism ◽  
Kinetic Parameters ◽  
Important Change ◽  
Elementary Reactions ◽  
Chemical Systems ◽  
Chemical Mechanisms ◽  
Computational Performance ◽  
Reaction Mechanism Generator ◽  
Automatic Mechanism ◽  
Global Uncertainty

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. One important change is that RMG v3.0 is now Python 3 compatible, which supports the most up-to-date versions of cheminformatics and machine learning packages that RMG depends on. Additionally, RMG can now generate heterogeneous catalysis models, in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release also includes parallelization for reaction generation and on-the-fly quantum calculations, and a new molecule isomorphism approach to improve computational performance. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

scholarly journals Detailed kinetic model for hexyl sulfide pyrolysis and its desulfurization by supercritical water

2019 ◽  
Vol 21 (20) ◽  
pp. 10311-10324 ◽  
Author(s):  
Caleb A. Class ◽  
AnGayle K. Vasiliou ◽  
Yuko Kida ◽  
Michael T. Timko ◽  
William H. Green
Keyword(s):  
Reaction Mechanism ◽  
Kinetic Model ◽  
Supercritical Water ◽  
Reaction Mechanism Generator ◽  
Detailed Kinetic Model

The automated reaction mechanism generator is used to model the decomposition of hexyl sulfide with and without supercritical water.

Extending Reaction Mechanism Generator to Silicon Hydride Chemistry

2016 ◽  
Vol 55 (49) ◽  
pp. 12507-12515 ◽  
Author(s):  
Belinda L. Slakman ◽  
Harsono Simka ◽  
Harinath Reddy ◽  
Richard H. West
Keyword(s):  
Reaction Mechanism ◽  
Silicon Hydride ◽  
Reaction Mechanism Generator

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

2021 ◽  
Author(s):  
Mengjie Liu ◽  
Alon Grinberg Dana ◽  
Matthew S. Johnson ◽  
Mark J. Goldman ◽  
Agnes Jocher ◽  
...  
Keyword(s):  
Reaction Mechanism ◽  
Reaction Mechanism Generator ◽  
Automatic Mechanism

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

2020 ◽  
Author(s):  
Mengjie Liu ◽  
Alon Grinberg Dana ◽  
Matthew Johnson ◽  
Mark Goldman ◽  
Agnes Jocher ◽  
...  
Keyword(s):  
Reaction Mechanism ◽  
Kinetic Parameters ◽  
Important Change ◽  
Elementary Reactions ◽  
Chemical Systems ◽  
Chemical Mechanisms ◽  
Computational Performance ◽  
Reaction Mechanism Generator ◽  
Automatic Mechanism ◽  
Global Uncertainty

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. One important change is that RMG v3.0 is now Python 3 compatible, which supports the most up-to-date versions of cheminformatics and machine learning packages that RMG depends on. Additionally, RMG can now generate heterogeneous catalysis models, in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release also includes parallelization for reaction generation and on-the-fly quantum calculations, and a new molecule isomorphism approach to improve computational performance. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

scholarly journals Reaction Mechanism Generator: Automatic construction of chemical kinetic mechanisms

2016 ◽  
Vol 203 ◽  
pp. 212-225 ◽  
Author(s):  
Connie W. Gao ◽  
Joshua W. Allen ◽  
William H. Green ◽  
Richard H. West
Keyword(s):  
Reaction Mechanism ◽  
Chemical Kinetic ◽  
Automatic Construction ◽  
Reaction Mechanism Generator ◽  
Kinetic Mechanisms

scholarly journals Automatic mechanism generation for pyrolysis of di-tert-butyl sulfide

2016 ◽  
Vol 18 (31) ◽  
pp. 21651-21658 ◽  
Author(s):  
Caleb A. Class ◽  
Mengjie Liu ◽  
Aäron G. Vandeputte ◽  
William H. Green
Keyword(s):  
Thermal Decomposition ◽  
Reaction Mechanism ◽  
Ab Initio ◽  
Reaction Networks ◽  
Tert Butyl ◽  
Reaction Mechanism Generator ◽  
Automatic Mechanism

The automated Reaction Mechanism Generator (RMG), using rate parameters derived from ab initio CCSD(T) calculations, is used to build reaction networks for the thermal decomposition of di-tert-butyl sulfide.

scholarly journals Modeling study of the anti-knock tendency of substituted phenols as additives: an application of the reaction mechanism generator (RMG)

2018 ◽  
Vol 20 (16) ◽  
pp. 10637-10649 ◽  
Author(s):  
Peng Zhang ◽  
Nathan W. Yee ◽  
Sorin V. Filip ◽  
Casey E. Hetrick ◽  
Bin Yang ◽  
...  
Keyword(s):  
Reaction Mechanism ◽  
Kinetic Modeling ◽  
Substituted Phenols ◽  
Reaction Mechanism Generator ◽  
Gasoline Additives ◽  
Modeling Study

This work presents kinetic modeling efforts to evaluate the anti-knock tendency of several substituted phenols if used as gasoline additives.

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