Language-oriented rule-based reaction network generation and analysis: Applications of RING

Srinivas Rangarajan; Aditya Bhan; Prodromos Daoutidis

doi:10.1016/j.compchemeng.2012.06.003

Language-oriented rule-based reaction network generation and analysis: Applications of RING

Srinivas Rangarajan, Aditya Bhan, Prodromos Daoutidis

Chemical Engineering and Materials Science

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

Applications of RING in the generation and analysis of complex thermochemical reaction networks are presented. Automated generation and topological network analysis features in RING allow for: (a) constructing reaction networks exhaustively in a rule-based manner, (b) identifying dominant pathways in networks using estimates of kinetic parameters, (c) hypothesis and testing of mechanisms by comparing pathway results from RING with experimental data, and (d) predicting atom-efficient synthetic routes to valuable chemicals from known chemistries and commonly available chemicals. Case studies involving three chemical systems are used to demonstrate these features in RING: (a) acid-catalyzed propane aromatization, (b) glycerol and acetone dehydration on acid catalysts, and (c) C ₄-C ₉ mono-alcohols synthesis from C ₂ and C ₃ oxygenates on acid, base, and metal catalyzed chemistries. Through these case studies, we demonstrate that RING can be used to postulate mechanisms and predict likely products for a given system, thereby guiding experimentation and computational analysis.

Original language	English (US)
Pages (from-to)	141-152
Number of pages	12
Journal	Computers and Chemical Engineering
Volume	46
DOIs	https://doi.org/10.1016/j.compchemeng.2012.06.003
State	Published - Nov 15 2012

Bibliographical note

Funding Information:
The authors would like to thank Prof. Eric Van Wyk and Ted Kaminski, Department of Computer Science and Engineering, University of Minnesota, for helpful suggestions on computer science algorithms and collaboration on developing the reaction language for RING. Financial support from the Initiative for Renewable Energy (Large Grant: RL-0004-09 ) at the University of Minnesota, the National Science Foundation Emerging Frontiers in Research and Innovation program , Grant #0937706 is gratefully acknowledged. AB was supported as part of the Catalysis Center for Energy Innovation, an Energy Frontier Research Center funded by the US Department of Energy , Office of Science, Office of Basic Energy Sciences under Award number DE-SC0001004 .

Keywords

Mechanism elucidation
Mechanism hypothesis testing
Pathway analysis
Reaction network analysis
Rule-based network generation
Synthesis routes prediction

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10.1016/j.compchemeng.2012.06.003

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title = "Language-oriented rule-based reaction network generation and analysis: Applications of RING",

abstract = "Applications of RING in the generation and analysis of complex thermochemical reaction networks are presented. Automated generation and topological network analysis features in RING allow for: (a) constructing reaction networks exhaustively in a rule-based manner, (b) identifying dominant pathways in networks using estimates of kinetic parameters, (c) hypothesis and testing of mechanisms by comparing pathway results from RING with experimental data, and (d) predicting atom-efficient synthetic routes to valuable chemicals from known chemistries and commonly available chemicals. Case studies involving three chemical systems are used to demonstrate these features in RING: (a) acid-catalyzed propane aromatization, (b) glycerol and acetone dehydration on acid catalysts, and (c) C 4-C 9 mono-alcohols synthesis from C 2 and C 3 oxygenates on acid, base, and metal catalyzed chemistries. Through these case studies, we demonstrate that RING can be used to postulate mechanisms and predict likely products for a given system, thereby guiding experimentation and computational analysis.",

keywords = "Mechanism elucidation, Mechanism hypothesis testing, Pathway analysis, Reaction network analysis, Rule-based network generation, Synthesis routes prediction",

author = "Srinivas Rangarajan and Aditya Bhan and Prodromos Daoutidis",

note = "Funding Information: The authors would like to thank Prof. Eric Van Wyk and Ted Kaminski, Department of Computer Science and Engineering, University of Minnesota, for helpful suggestions on computer science algorithms and collaboration on developing the reaction language for RING. Financial support from the Initiative for Renewable Energy (Large Grant: RL-0004-09 ) at the University of Minnesota, the National Science Foundation Emerging Frontiers in Research and Innovation program , Grant #0937706 is gratefully acknowledged. AB was supported as part of the Catalysis Center for Energy Innovation, an Energy Frontier Research Center funded by the US Department of Energy , Office of Science, Office of Basic Energy Sciences under Award number DE-SC0001004 . ",

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doi = "10.1016/j.compchemeng.2012.06.003",

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AU - Rangarajan, Srinivas

AU - Bhan, Aditya

AU - Daoutidis, Prodromos

N1 - Funding Information: The authors would like to thank Prof. Eric Van Wyk and Ted Kaminski, Department of Computer Science and Engineering, University of Minnesota, for helpful suggestions on computer science algorithms and collaboration on developing the reaction language for RING. Financial support from the Initiative for Renewable Energy (Large Grant: RL-0004-09 ) at the University of Minnesota, the National Science Foundation Emerging Frontiers in Research and Innovation program , Grant #0937706 is gratefully acknowledged. AB was supported as part of the Catalysis Center for Energy Innovation, an Energy Frontier Research Center funded by the US Department of Energy , Office of Science, Office of Basic Energy Sciences under Award number DE-SC0001004 .

PY - 2012/11/15

Y1 - 2012/11/15

N2 - Applications of RING in the generation and analysis of complex thermochemical reaction networks are presented. Automated generation and topological network analysis features in RING allow for: (a) constructing reaction networks exhaustively in a rule-based manner, (b) identifying dominant pathways in networks using estimates of kinetic parameters, (c) hypothesis and testing of mechanisms by comparing pathway results from RING with experimental data, and (d) predicting atom-efficient synthetic routes to valuable chemicals from known chemistries and commonly available chemicals. Case studies involving three chemical systems are used to demonstrate these features in RING: (a) acid-catalyzed propane aromatization, (b) glycerol and acetone dehydration on acid catalysts, and (c) C 4-C 9 mono-alcohols synthesis from C 2 and C 3 oxygenates on acid, base, and metal catalyzed chemistries. Through these case studies, we demonstrate that RING can be used to postulate mechanisms and predict likely products for a given system, thereby guiding experimentation and computational analysis.

AB - Applications of RING in the generation and analysis of complex thermochemical reaction networks are presented. Automated generation and topological network analysis features in RING allow for: (a) constructing reaction networks exhaustively in a rule-based manner, (b) identifying dominant pathways in networks using estimates of kinetic parameters, (c) hypothesis and testing of mechanisms by comparing pathway results from RING with experimental data, and (d) predicting atom-efficient synthetic routes to valuable chemicals from known chemistries and commonly available chemicals. Case studies involving three chemical systems are used to demonstrate these features in RING: (a) acid-catalyzed propane aromatization, (b) glycerol and acetone dehydration on acid catalysts, and (c) C 4-C 9 mono-alcohols synthesis from C 2 and C 3 oxygenates on acid, base, and metal catalyzed chemistries. Through these case studies, we demonstrate that RING can be used to postulate mechanisms and predict likely products for a given system, thereby guiding experimentation and computational analysis.

KW - Mechanism elucidation

KW - Mechanism hypothesis testing

KW - Pathway analysis

KW - Reaction network analysis

KW - Rule-based network generation

KW - Synthesis routes prediction

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Language-oriented rule-based reaction network generation and analysis: Applications of RING

Abstract

Bibliographical note

Keywords

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