Exploring advanced catalysts and reaction systems operated at mild reaction conditions is crucial for conducting the direct methane oxidation reaction toward oxygenate products. Many efforts have been put into research on pentasil−type (MFI) zeolites based on mononuclear and/or binuclear iron sites, using H₂O₂ as the oxidant. In this work, we present a modified liquid ion−exchange method to better control Fe loading in a mordenite−type (MOR) zeolite with a Si/Al molar ratio of 9. The optimized Fe/MOR catalyst showed excellent performance in the direct methane oxidation reaction with turnover frequencies (TOFs) of 555 h⁻¹ to C₁ oxygenates, significantly better than the reported activity. Multiple comparative experiments were conducted to reveal the mechanism behind the performance. Strikingly, the active sites in the Fe/MOR catalyst were found to be mononuclear iron sites, confirmed by transmission electron microscopy (TEM), ultraviolet−visible diffuse reflectance spectroscopy (UV−vis DRS), and X-ray absorption spectroscopy (XAS). Increasing the iron loading led to the aggregation of the iron sites, which tend to trigger undesirable side reactions (i.e., H₂O₂ decomposition and over−oxidation), resulting in a significant decrease in TOFs to C₁ oxygenates.

Solid oxide fuel cells are globally recognized as a very promising technology in the area of highly efficient electricity generation with a low environmental impact. In this paper, a novel hybrid krill herd algorithm (nhKHA) is proposed for modeling the solid oxide fuel cells (SOFCs). In nhKHA, the operation inspired by the foraging behavior of fish-swarm is adopted to improve the global search ability, and the operation inspired by the virus search is used to improve the search efficiency and accuracy. The nhKHA is applied to optimize the parameters of the SOFC, the experiment results show that this nhKHA can achieve more higher precision between mathematical model and experimental data compared with some other optimization algorithms.