基态氧原子与HO2及C2H2的反应是碳氢燃料燃烧过程中的重要反应。近年来对相关反应的动力学性质已有较多的理论与实验研究，但动力学机制尚不清楚。理解燃烧过程中基元反应的微观动力学机制是提高燃烧效率的关键因素。由于这两个反应都涉及多通道和深势阱，对势能面的构建和量子动力学的计算都是很大的挑战。本项目拟结合高级别量子化学从头算方法和置换对称多项式-神经网络方法，分别构建HO3和C2H2O的电子基态和低激发态势能面和非绝热耦合，建立合适的量子波包动力学模型，提高计算效率，深入研究基态氧原子与HO2及C2H2反应在不同碰撞条件下的动力学性质，获得精确的速率常数和反应分支比以及振动激发对动力学性质的影响等，剖析非绝热效应对燃烧反应动力学的影响，揭示其细致的微观反应机理。通过本项目的研究，可以增强对碳氢燃料燃烧动力学的认识，帮助寻找提高燃烧效率的有效途径，为改进燃烧模型和相关实验研究提供重要的理论依据。

The reactions of the ground state oxygen atom with HO2 and C2H2 play important roles in combustion of hydrocarbon fuel. The related reactions have been studied extensively from the kinetics standpoint using a variety of experimental techniques and theoretical methods. However, their dynamic mechanisms are still unclear. A well understanding of the microscopic mechanisms for the elementary reactions in combustion process is a critical factor for improving combustion efficiency. Due to the involvement of multi channels and deep potential wells for those reactions, the construction of potential energy surfaces and quantum dynamic calculations are of great challenges. In this proposal, based on high level ab initio methods, we will construct the potential energy surfaces for the electronic ground and excited states including possible non-adiabatic couplings for the HO3 and C2H2O systems using permutation invariant polynomial neural network approach. Appropriate quantum wavepacket dynamic models will be developed to improve the computational efficiency. We will investigate the dynamic features under different collision conditions for the reactions of the ground state oxygen atom with HO2 and C2H2. In addition, we will generate accurate rate constants, branching ratio, and their dependence on the initial vibrational excitation. We will also investigate the influence of the non-adiabatic effect on the reaction dynamics. The outputs of studies will greatly enhance our understanding of combustion dynamics of hydrocarbon fuel, help to find the effective way of increasing the combustion efficiency, and provide useful information for improving combustion models and further related experimental studies.