Increasing aviation activities have heightened concerns about particulate emissions from aircraft engines. Current ICAO standards mainly focus on large civil turbofan engines, leaving a gap in the research on PN emissions from small aircraft engines. This study examined the PN emission characteristics of micro-turbojet engines, including the morphology, PN, and size distribution under different load conditions, compared with a micro-piston engine. The results showed that the nvPM from micro-turbojet engines was larger and more complex than typical aviation soot, likely due to reduced combustion efficiency and incomplete fuel combustion. Micro-turbojet engines exhibited fewer fluctuations in their emission index number (EIn) and emission index mass (EIm) at lower speeds. The geometric mean diameter (GMD) of particles was inversely correlated with thrust, while the geometric standard deviation (GSD) slightly increased with thrust. Quantitative comparisons indicated that PN emissions from micro-turbojet engines were higher, with EIn values ranging from 2.0 to 3.3 × 10¹⁶/kg fuel compared with 1.2 to 1.5 × 10¹⁶/kg fuel for micro-piston engines. EIm values for micro-turbojet engines ranged from 8 to 40 mg/kg fuel, while micro-piston engines had slightly higher values due to better carbonization. These findings validated the measurement methodology used to accurately assess PN emissions under low-thrust conditions in micro-turbojet engines. These results provide crucial insights and support for the future monitoring and regulation of PN emissions across all thrust conditions in small aircraft engines.

Molecular-level nucleation has not been clearly understood due to the complexity of multi-body potentials and the stochastic, rare nature of the process. This work utilizes molecular dynamics (MD) simulations, incorporating a first-principles-based deep neural network (DNN) potential model, to investigate homogeneous water vapor condensation. The nucleation rates and critical nucleus sizes predicted by the DNN model are compared against commonly used semi-empirical models, namely extended simple point charge (SPC/E), TIP4P, and OPC, in addition to classical nucleation theory (CNT). The nucleation rates from the DNN model are comparable with those from the OPC model yet surpass the rates from the SPC/E and TIP4P models, a discrepancy that could mainly arise from the overestimated bulk free energy by SPC/E and TIP4P. The surface free energy predicted by CNT is lower than that in MD simulations, while its bulk free energy is higher than that in MD simulations, irrespective of the potential model used. Further analysis of cluster properties with the DNN model unveils pronounced variations of O–H bond length and H–O–H bond angle, along with averaged bond lengths and angles that are enlarged during embryonic cluster formation. Properties such as cluster surface free energy and liquid-to-vapor density transition profiles exhibit significant deviations from CNT assumptions.