Hierarchical zeolites attract people’s attention due to their enhanced mass transfer properties in catalytic reactions. The research over obtaining these zeolites in green and efficient methods is of great significance for the current post-treatments and templating strategies tend to be costly for hierarchical zeolite synthesis. In this research, nanosized mesoporous ZSM-5 (SN-ZSM-5) zeolites have been synthesized without the addition of mesoscale templates under highly concentrated conditions. The physicochemical characteristics were systematically investigated by XRD, SEM, N2 sorption, TEM, and NMR. The SEM images showed ZSM-5 crystals with sizes between 50–110 nm were obtained. N₂ sorption and high-resolution TEM images gave direct evidence for the hierarchical structure of SN-ZSM-5. The forming mechanism for the hierarchical structure was proposed that the etching effect of the highly alkaline environment for the starting gels played a critical role in the formation of hierarchical structure. Catalytic tests in methanol-to-olefins (MTO) showed the SN-ZSM-5 performed a longer catalyst lifetime and higher propylene selectivity than the conventional ZSM-5 zeolites (C-ZSM-5) obtained from a traditional hydrothermal method. The features of hierarchical structure in the SN-ZSM-5 crystals and the sustainability for synthesis method could show a promising choice for wide applications of these SN-ZSM-5 zeolites in the future.

Electrochemical oxygen reduction via the two-electron pathway (2e-ORR) is an emerging method for producing H₂O₂. It is cleaner, safer, and more convenient compared to the anthraquinone process. Graphite felt is one of the cathode candidates for large-scale cells due to its excellent mechanical properties. However, commercial graphite felt often fails to achieve the desired hydrogen-peroxide yield because of its low catalytic selectivity for the 2e-ORR pathway. Fluorine-doped carbon materials are expected to enhance 2e-ORR selectivity. This is because the electronic structure of carbon atoms adjacent to fluorine atoms may facilitate the production of hydrogen peroxide while hindering its further reduction. In this study, fluorine-doped graphene oxide (FGO) was prepared by the hydrothermal method. Subsequently, graphite felt modified with FGO was fabricated and used as the cathode for H₂O₂ production. The results indicated that in alkaline media, the graphite felt modified with FGO achieved a catalytic selectivity of 93% and a generation rate of 8.91 mg cm⁻² h⁻¹. In comparison, commercial graphite felt had a catalytic selectivity of 75% and a generation rate of 2.10 mg cm⁻² h⁻¹. Moreover, graphite felt modified by FGO also exhibited excellent electrocatalytic performance for H₂O₂ generation in neutral media. This research provides a fundamental study to promote the application of graphite felt in the environmentally friendly electrocatalytic production of hydrogen peroxide in industries.

Safety design is a critical concern for energetic materials, with sensitivities and performance parameters becoming increasingly important as energy density rises. However, obtaining experimental data for these properties is costly and risky. Although linear methods and neural networks have been applied to predict these properties, the limited sample size of experimental data has led to models with limitations, including inadequate accuracy, lack of effective predictive models, and inevitable reliance on experimental properties. To address these challenges, this study utilizes kernel methods and heuristic algorithms, including Genetic Algorithm and Particle Swarm Optimization, to develop effective models for predicting the impact sensitivity, electric spark sensitivity, and detonation velocity of energetic materials. After optimizing the modeling process with Particle Swarm Optimization, the models achieved R² values of 0.871, 0.898, and 0.942 on the test sets, respectively, surpassing those of neural network models, with R² values of 0.827, 0.826, and 0.909, and support vector regression models, with R² values of 0.822, 0.862, and 0.894. The proposed models significantly improve the accuracy of impact sensitivity predictions and, for the first time, offer an effective model for predicting electric spark sensitivity. By being entirely based on computational descriptors, these models expand the application range compared to previous empirical formulas. These results demonstrate the high effectiveness and accuracy of this methodology in predicting the hazardous properties of chemicals with limited experimental data.

Synthesis of zeolites in more efficient and greener methods is of great significance in both industrial and academic fields. However, the relative long time for zeolite crystallization and much consumption of water solvent make the target challengeable. Herein, a route for ultrafast synthesis of nano Silicalite-1 zeolites in 10 min with much less water consumption has been developed. Comprehensive characterizations, i.e., X-ray powder diffraction, N₂ sorption, scanning electron microscope, and NMR, confirm the high quality of such obtained Silicalite-1 zeolites. In the catalytic deoxygenation of O₂-containing ethylene (mixture of O₂ and ethylene), these reported Silicalite-1 zeolite samples show the comparable performance with the conventional Silicalite-1 zeolites synthesized under hydrothermal conditions. This research therefore provides a new trial toward the ultrafast synthesis of zeolite materials in an environment-friendly route.