Liang Ding

A series of Zn-modified HBeta (Zn/HBeta) catalysts were prepared via the wetness impregnation method with different zinc precursors such as ZnSO₄·7H₂O, ZnCl₂, C₄H₆O₄Zn·2H₂O and Zn(NO₃)₂·6H₂O, and their catalytic performance in the conversion of ethanol to propylene reaction was evaluated. Results indicate that the amount and strength distribution of the acid sites of the Zn/HBeta catalysts were easily tuned by employing different types of zinc precursors. More importantly, when the zinc species were introduced to the HBeta, the propylene yield was significantly enhanced, whereas the yields of ethylene and C₂–C₄ alkanes were remarkably suppressed. For the catalyst prepared by using the ZnCl₂ precursor, a higher propylene yield of up to 43.4% for Zn/HBeta-C was achieved as a result of the moderate amount and strength distribution of acid sites. The average coking rate of the used Zn/HBeta catalysts strongly depended on the amount of total acid sites, especially the strong acid sites, i.e., the higher the amount of total acid sites of the catalyst, the greater the average coking rate. For the catalyst prepared by using the ZnSO₄·7H₂O precursor, Zn/HBeta-S exhibited a better stability even after depositing more coke, which was due to the higher amount of strong acid sites.

A series of Zn-modified Hβ (Zn/Hβ) catalysts were prepared by using the different zinc precursors such as ZnSO4·7H2O, ZnCl2, C4H6O4Zn·2H2O and Zn(NO3)2·6H2O, and their catalytic performance in the ethanol conversion to propylene reaction was evaluated. Results indicate the amount and strength distribution of acid sites of the Zn/Hβ catalysts were easily tuned by employing different type of zinc precursors. More importantly, when the Zn species were introduced to the Hβ, the propylene yield was significantly enhanced, whereas the yields of the byproducts such as ethylene and C2-C4 alkanes were remarkably suppressed. For the catalyst prepared by using the ZnCl2 precursor (Zn/Hβ-C), a higher propylene yield up to 43.4% was achieved as a result of the moderate amount and distribution of acid sites. The average coking rate of the used Zn/Hβ catalysts strongly depended on the amount of total acid sites, especially the strong acid sites, i.e., the higher the amount of total acid sites of the catalyst, the greater the average coking rate. For the catalyst prepared by using the ZnSO4·7H2O precursor, Zn/Hβ-S exhibited a better stability even after depositing more coke, which is due to the higher amount of strong acid sites.

The maximum gasification rate of corn stalk char (CSC) appeared at high conversion range, and its quite different gasification behaviors from other carbonaceous materials are all derived from the catalytic effect of alkali and alkali earth metals (AAEMs), so it is necessary to study the effect of AAEMs and gasification kinetics of such biomass char. However, there are few systematic discussions about this effect and kinetic modeling. Thus, in this study, CSC samples were prepared in a fast pyrolysis fixed-bed reactor, and its gasification experiments were conducted on a pressurized magnetic suspension balance at various total pressures (0.1–0.7 MPa), steam concentrations (10–70 vol.%) and temperatures (725–900 °C). Moreover, a water-leached CSC (H₂O-CSC) was also prepared to evaluate the impact of AAEMs on the gasification performance of CSC, and some well-known models were adopted to describe the gasification behaviors. On the basis of these results, the effect of primary AAEMs on the gasification behaviors of CSC and gasification kinetic modeling were obtained. Results showed total pressure had no obvious influence on the gasification rate of CSC, and the reaction order varied at 0.43–0.55 with respect to steam partial pressures. In addition, the modified random pore model (MRPM) and Langmuir–Hinshelwood (L-H) model were satisfactorily applied to predict the gasification behaviors of CSC. The catalytic effect of AAEMs on CSC gasification was weakened due to water-leaching treatment. A random pore model (RPM) could describe the gasification behavior of H₂O-CSC well, followed by grain model (GM) and volumetric model (VM).