甲烷化
催化作用
非阻塞I/O
化学工程
色散(光学)
材料科学
选择性
焦炭
粒径
纳米线
甲烷
纳米颗粒
复合数
烧结
粒子(生态学)
纳米技术
冶金
化学
复合材料
有机化学
工程类
地质学
物理
光学
海洋学
作者
Wei Keen Fan,Muhammad Tahir,Hajar Alias,Abdul Rahman Mohamed
标识
DOI:10.1016/j.ijhydene.2023.06.241
摘要
In this study, TiO2 was morphologically engineered into three distinct structures, namely three-dimensional microparticles (MPs), zero-dimensional nanoparticles (NPs) and one-dimensional nanowires (NWs) to examine the effect of structure on CO2 methanation. Firstly, thermodynamic analysis was conducted, whereby it was observed that CH4 production is favoured at low temperature. Higher temperature will cause the CH4 selectivity to drop, in turn increasing the formation of other side products such as CO, C2H6 and solid coke. Then, Ni loaded on three different TiO2 supports, namely 3D TiO2 microparticles (MPs), 0D nanoparticles (NPs) and 1D nanowires (NWs), were prepared. It was noticed that the NPs have the smallest support particle size, followed by NWs and MPs. Despite TiO2 NWs having a larger particle size than NPs, the 15% Ni/TiO2 NWs boasted a higher surface area, smaller NiO crystalline and particle size, which resulted in an augmented NiO dispersion. Superior CO2 methanation performance with CO2 conversion, CH4 yield and selectivity of 88.44%, 87.53% and 98.97%, respectively was achieved over 15% Ni/TiO2 NWs. The stability of the TiO2 NWs counterpart over a 40 hours reaction time was the best among the three samples. Spent catalyst analysis also indicated that 15% Ni/TiO2 NWs are highly resistant to catalyst deactivation and coke formation. The prolonged durability was attributed to the 1D wire-like structure, which promoted a higher dispersion of active sites, facilitating an intimate contact between catalyst and reactants. The ameliorated dispersion also mitigates catalyst deactivation via sintering and coke formation. The findings elucidated that the morphology of the catalyst is more influential in enhancing the hydrogenation reaction than the support size.
科研通智能强力驱动
Strongly Powered by AbleSci AI