Neural network potential-based molecular investigation of pollutant formation of ammonia and ammonia-hydrogen combustion

Abstract

This study developed neural network potentials (NNPs) specifically designed for ammonia and ammonia-hydrogen combustion systems for the first time. The NNPs were employed to perform reactive molecular dynamics (RMD) simulations, combining the precision of density functional theory (DFT) calculations with the efficiency of empirical force fields. NNP-based RMD simulations provide a more detailed and comprehensive understanding of chemical reaction mechanisms. The impacts of different equivalence ratios and hydrogen addition on ammonia combustion as well as NOX and N2O formation were analysed. The results indicate that both the addition of hydrogen and the reduction of equivalence ratios contribute to enhancing ammonia combustion. The primary reason is the enhancement of the oxidative environment within the system, leading to a significant increase in the frequency of reactions associated with oxidising radicals such as OH, O, and HO2. This is also the cause for the increased production of NO and NO2, because the formation of NO depends on the oxidation of NH and NH2, while NO2 is formed through the oxidation of NO. An interesting finding is that the addition of hydrogen decelerates the generation of N2O, while reducing the equivalence ratio promotes N2O production. This phenomenon is attributed to the additional H radicals generated during hydrogen decomposition, which hinders the binding between NH and NO, resulting in a reduction in the formation of the precursor HN2O required for N2O formation.