Automatic mechanism generation for pyrolysis of di-tert-butyl sulfide
文献信息
Caleb A. Class, Mengjie Liu, Aäron G. Vandeputte, William H. Green
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. Simulation results were compared with data from pyrolysis experiments with and without the addition of a cyclohexene inhibitor. Purely free-radical chemistry did not properly explain the reactivity of di-tert-butyl sulfide, as the previous experimental work showed that the sulfide decomposed via first-order kinetics in the presence and absence of the radical inhibitor. The concerted unimolecular decomposition of di-tert-butyl sulfide to form isobutene and tert-butyl thiol was found to be a key reaction in both cases, as it explained the first-order sulfide decomposition. The computer-generated kinetic model predictions quantitatively match most of the experimental data, but the model is apparently missing pathways for radical-induced decomposition of thiols to form elemental sulfur. Cyclohexene has a significant effect on the composition of the radical pool, and this led to dramatic changes in the resulting product distribution.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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