In:
Physical Chemistry Chemical Physics, Royal Society of Chemistry (RSC), Vol. 23, No. 42 ( 2021), p. 24165-24174
Abstract:
In low temperature plasmas, energy transfer between asymmetric stretching excited CO 2 molecules can be highly efficient, which leads to further excitation (and de-excitation) of the CO 2 molecules: CO 2 ( v as ) + CO 2 ( v as ) → CO 2 ( v as + 1) + CO 2 ( v as − 1). Through such a vibrational ladder climbing mechanism, CO 2 can be activated and eventually dissociates. To gain mechanistic insight of such processes, a full-dimensional accurate potential energy surface (PES) for the CO 2 + CO 2 system is developed using the permutational invariant polynomial-neural network method based on CCSD(T)-F12a/AVTZ energies at about 39 000 geometries. This PES is used in quasi-classical trajectory (QCT) studies of the vibrational energy transfer between CO 2 molecules excited in the asymmetric stretching mode. A machine learning algorithm is used to determine state-specific rate coefficients for the vibrational transfer processes from a limited data set. In addition to the CO 2 ( v as + 1) + CO 2 ( v as − 1) channel, the QCT simulations revealed significant contributions from the CO 2 ( v as + 2,3) + CO 2 ( v as − 2,3) channels, particularly at low collision energies/temperatures. These multi-vibrational-quantum processes are attributed to enhanced energy flow in the collisional complex formed by enhanced dipole–dipole interaction between asymmetric stretching excited CO 2 molecules.
Type of Medium:
Online Resource
ISSN:
1463-9076
,
1463-9084
Language:
English
Publisher:
Royal Society of Chemistry (RSC)
Publication Date:
2021
detail.hit.zdb_id:
1476283-3
detail.hit.zdb_id:
1476244-4
detail.hit.zdb_id:
1460656-2
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