Boosting(机器学习)
甲醇
材料科学
金属
化学工程
化学
有机化学
计算机科学
冶金
机器学习
工程类
作者
Xiaoguang San,Xudong Li,Lei Zhang,Dan Meng,Xiangshuang Chang,Qi Jian
标识
DOI:10.1016/j.psep.2024.04.141
摘要
As global energy demand continues to increase and global climate change issues caused by greenhouse gas emissions gradually heat up, the effective conversion of carbon dioxide into high value-added methanol has become a key challenge in the energy and environmental fields. However, due to the chemical inertness of CO2 molecules, it is difficult to activate CO2 at low temperatures, resulting in extremely low conversion rates. Although increasing the reaction temperature is beneficial for the conversion of CO2, there is also competition in the reverse water gas reaction, resulting in lower methanol selectivity. Therefore, developing efficient catalysts is the key to improving CO2 conversion rate and methanol selectivity. In this work, we used zirconium-based UIO-66 metal-organic framework as a precursor, replaced the original terephthalic acid ligand with thermally unstable aminoterephthalic acid, and supported Cu on the MOF precursor by equal volume impregnation method. After heat treatment, the Cu/ZrO2-DM catalyst was prepared. The catalyst was compared with Cu/ZrO2 catalyst prepared by co-precipitation method, hydrothermal method and unmodified Cu/ZrO2-D catalyst. The Cu/ZrO2-DM catalyst exhibited the highest CO2 conversion and methanol selectivity in the hydrogenation reaction, reaching 13.95% and 90.78%, respectively. The main reason is attributed to the large specific surface area of the copper-based catalyst derived from MOF materials, the good dispersion of the active center and the strong interaction between Cu and the precursor. This work may provide a new perspective for the design and synthesis of related catalytic materials for efficient CO2 hydrogenation to methanol.
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