Collisional energy transfer in CH3 radical decomposition—experiment versus theory
文献信息
E. Goos, H. Hippler, C. Kachiani, H. Svedung
Experimentally determined incubation times in the thermal decomposition of methyl radicals were used to obtain collisional energy transfer probability information by adopting a discrete vibrational energy level master-equation scheme with specific rate constants from the statistical adiabatic channel model. The agreement with information from classical molecular dynamic, MD, simulations of CH3–Ar collisions was shown to be remarkably good. Results from MD simulations also support the assumption of thermally equilibrated rotations used here and in earlier work. The sensitivity of the pressure fall-off behaviour of the decomposition channels to remaining uncertainties in the energy transfer profiles is shown to be significant, in this case, as a consequence of the large number of collisions needed to reach activation. Nevertheless, we find classical molecular dynamics simulation to be useful and a good starting point in obtaining the collisional energy transfer kernel to be used in master-equation calculations treating the most obvious quantum effects through the use of discrete energy levels at low energies.
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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.














