新型炭材料2022，Vol.37Issue(6)：1135-1144,10.DOI:10.1016/S1872-5805(22)60619-X
氧掺杂氮化碳多孔纳米片高效光电催化CO2还原制甲酸
Oxygen-incorporated carbon nitride porous nanosheets for highly efficient photoelectrocatalytic CO2 reduction to formate
摘要
Abstract
Using CO2 as a renewable carbon source for the production of high-value-added fuels and chemicals has recently re-ceived global attention.The photoelectrocatalytic(PEC)CO2 reduction reaction(CO2RR)is one of the most realistic and attractive ways of achieving this,and can be realized effectively under sunlight illumination at a low overpotential.Oxygen-incorporated car-bon nitride porous nanosheets(CNs)were synthesized from urea or melamine by annealing in nitrogen or N2/O2 gas mixtures.They were used as the photoanode with Bi2CuO4 as the photocathode to realize PEC CO2 reduction to the formate.The electrical conduct-ivity and the photoelectric response of the CNs were modified by changing the oxygen source.Oxygen in CNs obtained from an oxy-gen-containing precursor improved the conductivity because of its greater electronegativity,whereas oxygen in CNs obtained from the calcination atmosphere had a lower photoelectric response due to a down shift of the energy band structure.The CN prepared by annealing urea,which served as the source of oxygen and nitrogen,at 550℃for 2 h in nitrogen is the best.It has a photocurrent density of 587 μA cm-2 and an activity of PEC CO2 reduction to the formate of 273.56 μmol cm-2 h-1,which is nearly 19 times high-er than a conventional sample.The CN sample shows excellent stability with the photocurrent remaining constant for 24 h.This work provides a new way to achieve efficient catalysts for PEC CO2 reduction to the formate,which may be expanded to different PEC re-actions using different cathode catalysts.关键词
氧掺杂/氮化碳/光电化学/二氧化碳还原反应/甲酸Key words
Oxygen-incorporated/Carbon nitride/Photoelectrocatalytic/CO2 reduction reaction/Formate分类
通用工业技术引用本文复制引用
王虹智,赵悦竹,杨中学,毕鑫泽,王照亮,吴明铂..氧掺杂氮化碳多孔纳米片高效光电催化CO2还原制甲酸[J].新型炭材料,2022,37(6):1135-1144,10.基金项目
This work was financially supported by the Na-tional Natural Science Foundation of China(52072409),Natural Science Foundation of Shan-dong Province(ZR2021QE062),Major Scientific and Technological Innovation Project of Shandong Province(2020CXGC010402),Qingdao postdoctoral applied research project(qdyy20200063),and Taishan Scholar Project(ts201712020). 基金项目:国家自然科学基金(52072409) （52072409）
山东省 自然科学基金(ZR2021QE062) （ZR2021QE062）
山东省科技创新重大专项(2020CXGC010402) （2020CXGC010402）
青岛市博士后应用研究项目(qdyy20200063) （qdyy20200063）
泰山学者项目(ts201712020). （ts201712020）
