Iso-cetane serves as an ideal component representing branched-chain alkanes in surrogate fuels for diesel. However, the predictive accuracy of existing detailed chemical kinetic models for iso-cetane requires improvement. In this study, focusing on the reaction processes of iso-cetane and its key intermediates, we first updated the thermodynamic data of iso-cetane and some of its intermediates, systematically analyzed the effects of various reactions on ignition delay time (IDT), and made targeted modifications to the relevant reaction rate constants. The reaction types involved include fuel cracking reactions of iso-cetane, hydrogen abstraction reactions, cracking reactions of fuel radicals, as well as the oxidation of fuel radicals, isomerization of alkylperoxy radicals ($\mathrm{R}{\dot{\mathrm{O}}}_2$), concerted elimination reactions, formation of cyclic ethers, and the formation and decomposition of ketohydroperoxides (KHP). Additionally, reactions related to the formation and consumption of p-alkyl-dihydroperoxides ($\dot{\mathrm{P}}{(\mathrm{OOH})}_2$) were supplemented. Based on the above work, we developed a detailed chemical kinetic model for iso-cetane, comprising 4541 species and 18,359 elementary reactions. Through systematic validation against experimental data on ignition delay time and concentration variations of key species during oxidation, the improved predictive performance of the proposed model was demonstrated. Furthermore, using sensitivity analysis and reaction pathway analysis for the ignition process, we revealed that the formation of the low-temperature negative temperature coefficient (NTC) region for iso-cetane is intrinsically associated with the competition between chain-branching and chain-propagating pathways.

Real biodiesel contains numerous components with complex molecular structures, and thus a representative surrogate fuel is required to develop tractable chemical kinetic mechanisms for biodiesel combustion. In this study, how physicochemical properties and molecular–structural descriptors interact when used as target parameters in biodiesel surrogate fuel formulation was clarified. Specifically, waste cooking oil biodiesel was selected as the target fuel, and methyl decanoate, methyl 3-hexenoate, n-hexadecane, and 1,4-hexadiene were selected as candidate components. A multi-objective genetic algorithm was employed to optimize component mass fractions under three target schemes, including physicochemical properties only, molecular–structural descriptors only, and a coupled scheme. Weight-perturbation calculations were then performed to quantify weight-dependent changes in target-matching errors and component fractions and to analyze the coupling mechanism among target parameters. The result shows that the coupled scheme provides the most balanced matching performance across physicochemical properties and molecular–structural descriptors while retaining all four components. Density, molar mass, the O/C ratio, viscosity, cetane number, and key molecular–structural descriptors exhibit the strongest coupling and dominate composition redistribution. The observed coupling among target parameters is realized through coordinated changes in component fractions, providing a basis for key-parameter screening in biodiesel surrogate fuel formulation.