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Updated: Jun 29, 2025

Isolating Free Carbenes, their Mixed Dimers and Organic Radicals
Published on: April 19, 2019
Comparative Study on the H-Abstraction Reactions of Isopropyl Acetate and Propyl Acetate by HO2 and OH Radicals
Mengjiao Gao1, Jiuning He1, Lilan Tian1
1College of Mathematics and Physics, Chengdu University of Technology, Chengdu, Sichuan 610059, China.
Abstract:
Isopropyl acetate (IPA) and propyl acetate (PA) are recognized as promising biofuels suitable for applications as fuel additives and biodiesel models. The H-abstraction reactions with radicals stand out as the fundamental initiating reactions in the combustion kinetic models for IPA and PA. In the present work, the kinetic calculations of IPA and PA plus HO2 and OH radicals were investigated at M06-2X/cc-pVTZ//G4, M08-HX/maug-cc-pVTZ, and CCSD(T)/jul-cc-pVTZ levels. The thermodynamic calculations were obtained based on the G4 and CBS-APNO methods. Rate coefficients were calculated using both transition state theory and canonical variational transition state theory with tunneling correction at the temperature range of 250-2000 K. The total rate constants for the IPA + OH system were fitted as follows: k = 0.4674 × T3.927 exp(2128/T) (cm3 mol-1 s-1), and for the PA + OH system, the total rate constants were determined using the following equation: k = 0.0161 × T4.373 exp(2220/T) (cm3 mol-1 s-1). The rate coefficients of IPA + OH reactions determined based on the M08-HX/maug-cc-pVTZ level effectively replicate the experimental data, while H-abstraction rate coefficients of PA + OH by the CCSD(T)/jul-cc-pVTZ method accurately reproduce the experimental data. Refining the H-abstraction rate coefficients in the kinetic mechanism of PA, as proposed by Dayma et al. [Proc. Combust. Inst. 37 (2019) 429-436], has been achieved through incorporating the present calculated data, leading to the development of a revised mechanism. The validation of the updated mechanism against jet-stirred reactor data is presented, showcasing its effective performance in predicting JSR data.
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