Insights into the Mechanism of Ozone Activation and Singlet Oxygen Generation on N-Doped Defective Nanocarbons: A DFT and Machine Learning Study
文献类型：期刊论文
| 作者 | Yu, Guangfei1,2,4; Wu, Yiqiu2,4; Cao, Hongbin2; Ge, Qingfeng1; Dai, Qin5; Sun, Sihan2; Xie, Yongbing2,3 |
| 刊名 | ENVIRONMENTAL SCIENCE & TECHNOLOGY
 |
| 出版日期 | 2022-06-21 |
| 卷号 | 56期号:12页码:7853-7863 |
| 关键词 | catalytic ozonation DFT machine learning N-doped nanocarbons ozone activation mechanism |
| ISSN号 | 0013-936X |
| DOI | 10.1021/acs.est.1c08666 |
| 英文摘要 | N-doped defective nanocarbon (N-DNC) catalysts have been widely studied due to their exceptional catalytic activity in many applications, but the O-3 activation mechanism in catalytic ozonation of N-DNCs has yet to be established. In this study, we systematically mapped out the detailed reaction pathways of O-3 activation on 10 potential active sites of 8 representative configurations of N-DNCs, including the pyridinic N, pyrrolic N, N on edge, and porphyrinic N, based on the results of density functional theory (DFT) calculations. The DFT results indicate that O-3 decomposes into an adsorbed atomic oxygen species (O-ads) and an O-3(2) on the active sites. The atomic charge and spin population on the O-ads species indicate that it may not only act as an initiator for generating reactive oxygen species (ROS) but also directly attack the organics on the pyrrolic N. On the N site and C site of the N4V2 system (quadri-pyridinic N with two vacancies) and the pyridinic N site at edge, O-3 could be activated into O-1(2) in addition to O-3(2). The N4V2 system was predicted to have the best activity among the N-DNCs studied. Based on the DFT results, machine learning models were utilized to correlate the O-3 activation activity with the local and global properties of the catalyst surfaces. Among the models, XGBoost performed the best, with the condensed dual descriptor being the most important feature. |
| WOS关键词 | FENTON-LIKE CATALYST ; GRAPHENE ; REDUCTION ; OZONATION ; PERFORMANCE ; ADSORPTION ; EVOLUTION ; OXIDATION ; CO2 |
| 资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences[XDA21021102] ; State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization[2021P4FZG04A] |
| WOS研究方向 | Engineering ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000815705700001 |
| 出版者 | AMER CHEMICAL SOC |
| 资助机构 | Strategic Priority Research Program of the Chinese Academy of Sciences ; State Key Laboratory of Vanadium and Titanium Resources Comprehensive Utilization |
| 源URL | [http://ir.ipe.ac.cn/handle/122111/54190]  |
| 专题 | 中国科学院过程工程研究所 |
| 通讯作者 | Ge, Qingfeng; Xie, Yongbing |
| 作者单位 | 1.Southern Illinois Univ, Dept Chem & Biochem, Carbondale, IL 62901 USA 2.Chinese Acad Sci, Inst Proc Engn, Chem & Chem Engn Data Ctr, Beijing Engn Res Ctr Proc Pollut Control, Beijing 100190, Peoples R China 3.Pangang Grp Res Inst Co Ltd, State Key Lab Vanadium & Titanium Resources Compr, Panzhihua 617000, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.North China Elect Power Univ, Coll Environm Sci & Engn, Beijing 102206, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Guangfei,Wu, Yiqiu,Cao, Hongbin,et al. Insights into the Mechanism of Ozone Activation and Singlet Oxygen Generation on N-Doped Defective Nanocarbons: A DFT and Machine Learning Study[J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY,2022,56(12):7853-7863. |
| APA | Yu, Guangfei.,Wu, Yiqiu.,Cao, Hongbin.,Ge, Qingfeng.,Dai, Qin.,...&Xie, Yongbing.(2022).Insights into the Mechanism of Ozone Activation and Singlet Oxygen Generation on N-Doped Defective Nanocarbons: A DFT and Machine Learning Study.ENVIRONMENTAL SCIENCE & TECHNOLOGY,56(12),7853-7863. |
| MLA | Yu, Guangfei,et al."Insights into the Mechanism of Ozone Activation and Singlet Oxygen Generation on N-Doped Defective Nanocarbons: A DFT and Machine Learning Study".ENVIRONMENTAL SCIENCE & TECHNOLOGY 56.12(2022):7853-7863. |
入库方式： OAI收割
来源：过程工程研究所
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