REACTION v.1.0

This software, where the primary application has been in combustion processes, is used to automatically generate complete viable oxidative hydrocarbon mechanisms in a form that can be readily used in numeric simulations. The key to the generation process is the extensive set of, user modifiable, reaction classes, generic descriptions of a reactive process. Within the database are about a thousand classes already defined. The basic input to the generation process is a seed molecule, representing what species is to be reacted, a pathway of reaction classes. This generates a reactive submechanism. A complete mechanism consists of a combined set of generated submechanisms and a base mechanism of non generated reactions. The software also includes an array of other helpful reaction mechanism analysis tools to aid in the process of generation and validation. The system itself is built upon a more general system for data analysis and machine learning. This tool could also be used for teaching reactivity of hydrocarbon species.It shows, through examples and graphical output, the details and complexity of large hydrocarbon mechanisms. The available software has actually two purposes. The first as a tool to perform state of the art research, especially in the field of combustion science and chemistry in general. The software has been used to generate several oxidative combustion mechanisms for larger hydrocabons and has been published in several major journals. These tools can also be used as teaching aids for graduate courses in chemistry. The combustion software can be used to help the student understand the working and oxidative combustion behavior of larger hydrocarbons in a wide variety of temperature and pressure regimes. More generally, with the field of organic chemistry, the extensive database and molecular representation is ideal to study general principles of physical organic chemistry, both in terms of molecular properties and reactive properties.

This software, where the primary application ...

combustion, reaction, machine learning, organic chemistry