空位缺陷
过渡金属
氧气
材料科学
密度泛函理论
结晶学
吸附
金属
化学
物理化学
化学物理
催化作用
无机化学
计算化学
冶金
有机化学
作者
Dong Tian,Kongzhai Li,Yonggang Wei,Xing Zhu,Chunhua Zeng,Xianming Cheng,Yane Zheng,Hua Wang
摘要
The effects of transition metal (Fe, Co and Ni) modification (adsorption, insertion and substitution) of CeO2 surfaces on oxygen vacancy formation and CH4 activation are studied on the basis of first principles calculations. The results indicate that the hollow, O-O-bridge and Ce-O-bridge sites are the most stable sites for Fe, Co and Ni atom adsorption on the CeO2(111) surface, and the double O-bridge, O-top and double O-bridge sites are the corresponding most favorable sites for the CeO2(110) surface. Most of the configurations that are generated by the transition metal modification of CeO2(111) and (110) surfaces are accompanied by the reduction of Ce4+ to Ce3+. Based on the calculated subsurface (SS) and sublayer (SL) oxygen vacancies of the CeO2(111) surface, the results show that the substitution of transition metals on the CeO2(111) surface can promote SS oxygen vacancy formation spontaneously, whereas the most stable adsorption of transition metal Fe and Ni atoms on the CeO2(111) surface can promote SL oxygen vacancy formation spontaneously. For the CeO2(110) surface, the substitution of transition metals can facilitate plain (P) and spilt (S)-type oxygen vacancy formation spontaneously. With respect to CH4 activation, the results show that Co atom substitution on the CeO2(110) surface can greatly facilitate the first C-H bond activation step, with an energy barrier of 0.783 eV and a reaction energy of 0.229 eV. However, Co atom substitution on the CeO2(110) surface with P and S-type oxygen vacancies is not conducive to C-H activation. The obtained results could provide new insights into the structural features of transition metal-modified CeO2 at the atomistic level, leading to the more efficient design of oxygen carriers and the optimization of the activation pathways of methane over this type of catalyst.
科研通智能强力驱动
Strongly Powered by AbleSci AI