Decomposition of the Benzyl Radical:  Quantum Chemical and Experimental (Shock Tube) Investigations of Reaction Pathways

1997 ◽  
Vol 101 (38) ◽  
pp. 7105-7113 ◽  
Author(s):  
Jeffrey Jones ◽  
George B. Bacskay ◽  
John C. Mackie
Keyword(s):  
Shock Tube ◽  
Quantum Chemical ◽  
Reaction Pathways ◽  
Benzyl Radical ◽  
Experimental Shock

The Pyrolysis of 3-Picoline: Ab Initio Quantum Chemical and Experimental (Shock Tube) Kinetic Studies

1996 ◽  
Vol 36 (3) ◽  
pp. 239-248 ◽  
Author(s):  
Jeffrey Jones ◽  
George B. Bacskay ◽  
John C. Mackie
Keyword(s):  
Shock Tube ◽  
Ab Initio ◽  
Quantum Chemical ◽  
Kinetic Studies ◽  
Experimental Shock

Ab Initio Quantum Chemical and Experimental (Shock Tube) Studies of the Pyrolysis Kinetics of Acetonitrile

1999 ◽  
Vol 103 (8) ◽  
pp. 1054-1072 ◽  
Author(s):  
Karina Sendt ◽  
Emi Ikeda ◽  
George B. Bacskay ◽  
John C. Mackie
Keyword(s):  
Shock Tube ◽  
Ab Initio ◽  
Quantum Chemical ◽  
Pyrolysis Kinetics ◽  
Experimental Shock ◽  
Kinetics Of

Thermal Reactions of Benzoxazole. Single Pulse Shock Tube Experiments and Quantum Chemical Calculations

2006 ◽  
Vol 110 (13) ◽  
pp. 4607-4613 ◽  
Author(s):  
Assa Lifshitz ◽  
Carmen Tamburu ◽  
Aya Suslensky ◽  
Faina Dubnikova
Keyword(s):  
Shock Tube ◽  
Quantum Chemical Calculations ◽  
Quantum Chemical ◽  
Single Pulse ◽  
Thermal Reactions

Predicting Feasible Organic Reaction Pathways Using Heuristically Aided Quantum Chemistry

2018 ◽  
Author(s):  
Dmitrij Rappoport ◽  
Alan Aspuru-Guzik
Keyword(s):  
Quantum Chemistry ◽  
Reaction Mechanisms ◽  
Quantum Chemical ◽  
Organic Reactions ◽  
Reaction Pathways ◽  
Empirical Knowledge ◽  
Organic Reaction ◽  
Chemical Methods ◽  
Quantum Chemical Methods ◽  
Wide Range

Studying organic reaction mechanisms using quantum chemical methods requires from the researcher an extensive knowledge of both organic chemistry and first-principles computation. The need for empirical knowledge arises because any reasonably complete exploration of the potential energy surfaces (PES) of organic reactions is computationally prohibitive. We have previously introduced the Heuristically-Aided Quantum Chemistry (HAQC) approach to modeling complex chemical reactions, which abstracts the empirical knowledge in terms of chemical heuristics—simple rules guiding the PES exploration—and combines them with structure optimizations using quantum chemical methods. The HAQC approach makes use of heuristic kinetic criteria for selecting reaction paths that are not only plausible, that is, consistent with the empirical rules of organic reactivity, but also feasible under the reaction conditions. In this work, we develop heuristic kinetic feasilibity criteria, which correctly predict feasible reaction pathways for a wide range of simple polar (substitutions, additions, and eliminations) and pericyclic organic reactions (cyclizations, sigmatropic shifts, and cycloadditions). In contrast to knowledge-based reaction mechanism prediction methods, the same kinetic heuristics are successful in classifying reaction pathways as feasible or infeasible across this diverse set of reaction mechanisms. We discuss the energy profiles of HAQC and their potential applications in machine learning of chemical reactivity.<br>

Predicting Feasible Organic Reaction Pathways Using Heuristically Aided Quantum Chemistry

2018 ◽  
Author(s):  
Dmitrij Rappoport ◽  
Alan Aspuru-Guzik
Keyword(s):  
Quantum Chemistry ◽  
Reaction Mechanisms ◽  
Quantum Chemical ◽  
Organic Reactions ◽  
Reaction Pathways ◽  
Empirical Knowledge ◽  
Organic Reaction ◽  
Chemical Methods ◽  
Quantum Chemical Methods ◽  
Wide Range

Studying organic reaction mechanisms using quantum chemical methods requires from the researcher an extensive knowledge of both organic chemistry and first-principles computation. The need for empirical knowledge arises because any reasonably complete exploration of the potential energy surfaces (PES) of organic reactions is computationally prohibitive. We have previously introduced the Heuristically-Aided Quantum Chemistry (HAQC) approach to modeling complex chemical reactions, which abstracts the empirical knowledge in terms of chemical heuristics—simple rules guiding the PES exploration—and combines them with structure optimizations using quantum chemical methods. The HAQC approach makes use of heuristic kinetic criteria for selecting reaction paths that are not only plausible, that is, consistent with the empirical rules of organic reactivity, but also feasible under the reaction conditions. In this work, we develop heuristic kinetic feasilibity criteria, which correctly predict feasible reaction pathways for a wide range of simple polar (substitutions, additions, and eliminations) and pericyclic organic reactions (cyclizations, sigmatropic shifts, and cycloadditions). In contrast to knowledge-based reaction mechanism prediction methods, the same kinetic heuristics are successful in classifying reaction pathways as feasible or infeasible across this diverse set of reaction mechanisms. We discuss the energy profiles of HAQC and their potential applications in machine learning of chemical reactivity.<br>

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