The conversion of CO2 into high-value fuels and chemicals has garnered research interest worldwide. The conversion and utilization of CO2 has become one of the most urgent tasks for society. In this context, using solar energy to convert CO2 into high-value fuels such as CH4 and CH3OH has extremely high potential application value. Herein, the research progress and results of applying various photocatalysts in photocatalytic CO2 reduction with various novel catalysts were reviewed. Furthermore, strategies for improving photocatalytic performance were reviewed. Finally, improving the catalytic mechanism of catalysts and designing novel high-activity, high-stability catalysts through comprehensive exploration of the reaction mechanism were suggested to meet the future requirements of industrial production.
A series of related experiments were carried out based on prepared hydrocracking catalyst, Catalyst-HC. Ni & W and USY molecular sieve were selected as the hydrogenation active component and the cracking component of Catalyst-HC, respectively. Meanwhile, a kinetic model for paraffin conversion was constructed based on paraffin conversion law. Results obtained through this work indicate that the impact of H2-pressure is relatively complex. As the H2-pressure changes, the degree of hydrocracking reaction may be influenced by both hydrogen supply capacity and hydrogen proton concentration. Obtained conversion priority for three types of hydrocarbons on USY molecular sieve is as follows, aromatic ≫ cycloalkane > paraffin. Aromatic content in SRGO can affect its paraffin-retention in Hydro-D. Compared with the hydrotreating of SRGO with low aromatic content, when SRGO with relatively higher aromatic content is hydrotreated, its paraffin-retention is higher and its paraffin loss is also relatively smaller. Base on constructed model, the calculated values of SRGO-BJ conversion rate and paraffin-retention in Hydro-D are within ±10 % and ±5 % error lines, respectively. Thus, model schematic diagram is reasonable and can provide modeling reference for relevant model research.