第二壳层的碳缺陷调控CO2电催化还原的理论研究

doi:10.1016/S1872-2067(24)60131-2

催化学报 ›› 2024, Vol. 66: 247-256.DOI: 10.1016/S1872-2067(24)60131-2

第二壳层的碳缺陷调控CO₂电催化还原的理论研究

王梦娜^a^,^b, 王琪^a^,^*(), 刘天夫^b^,^c^,^*(), 汪国雄^b^,^*()

^a大连交通大学材料科学与工程学院, 辽宁大连 116028
^b中国科学院大连化学物理研究所催化基础国家重点实验室, 辽宁大连 116023
^c中国科学院大学, 北京 100039

收稿日期:2024-08-15 接受日期:2024-09-19 出版日期:2024-11-18 发布日期:2024-11-10
通讯作者: *电子信箱: qiwang@djtu.edu.cn (王琪),ltianfu@dicp.ac.cn (刘天夫),wanggx@dicp.ac.cn (汪国雄).
基金资助:
国家重点研发计划(2023YFA1508002);国家自然科学基金(22002158);国家自然科学基金(22172009);国家自然科学基金(22125205);国家自然科学基金(92045302);大连化物所创新研究基金(DNL201924);大连化物所创新研究基金(DNL202007);中国科学院碳中和光子科学中心项目

Unexpected effect of second-shell defect in iron-nitrogen-carbon catalyst for electrochemical CO₂ reduction reaction: A DFT study

Mengna Wang^a^,^b, Qi Wang^a^,^*(), Tianfu Liu^b^,^c^,^*(), Guoxiong Wang^b^,^*()

^aSchool of Materials and Engineering, Dalian Jiaotong University, Dalian 116028, Liaoning, China
^bState Key Laboratory of Catalysis, Dalian National Laboratory for Clean Energy, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, Liaoning, China
^cUniversity of Chinese Academy of Sciences, Beijing 100039, China

Received:2024-08-15 Accepted:2024-09-19 Online:2024-11-18 Published:2024-11-10
Contact: *E-mail: qiwang@djtu.edu.cn (Q. Wang),ltianfu@dicp.ac.cn (T. Liu),wanggx@dicp.ac.cn (G. Wang).
Supported by:
National Key R&D Program of China(2023YFA1508002);National Natural Science Foundation of China(22002158);National Natural Science Foundation of China(22172009);National Natural Science Foundation of China(22125205);National Natural Science Foundation of China(92045302);Dalian National Laboratory for Clean Energy(DNL201924);Dalian National Laboratory for Clean Energy(DNL202007);Photon Science Center for Carbon Neutrality

摘要/Abstract

摘要：

CO₂电催化还原提供了一种利用可再生能源将CO₂转化为燃料和化学品的负碳技术, 对于实现双碳目标具有重要意义. 单原子金属-氮-碳催化剂在CO₂电催化还原反应中展现了将CO₂高效还原为CO的性能. 目前关于金属-氮-碳催化剂的研究大多集中在对于金属种类、氮配位等结构与性能之间的关系. 但是对于金属-氮-碳催化剂结构中的第二壳层碳缺陷的研究很少. 在理论计算中广泛使用的计算氢电极模型是一种恒电荷模型, 与实验中实际采用的恒电位条件相差很大. 值得注意的是, 在铁-氮-碳(Fe-N-C)催化剂中的pH无关效应显示, 限速步骤可能不是质子-电子耦合转移, 而是质子-电子分步骤转移, 文献中常见报道的*COOH生成并不是速控步骤, 而CO₂吸附可能更加重要.

本文利用恒电位方法, 计算了Fe-N-C催化剂中第二壳层的三种碳缺陷(5577, 55577, 58)对CO₂电催化还原反应的影响, 并与恒电荷方法比较, 进而揭示*COOH的生成、CO₂吸附与电催化性能之间的关系. 研究结果表明, 加入碳缺陷并没有显著改变Fe-N-C的结构稳定性, 说明其可以在Fe-N-C催化剂中的第二壳层稳定存在. 恒电荷方法计算中得到的CO₂电催化限制电位约为-0.5 V (vs. RHE, 下同), 与实验中得到的-0.2 V相比有很大的误差, 而且恒电荷方法无法描述Fe-N-C催化剂上的pH无关效应. 利用恒电位与显式溶剂环境结合的方法发现, *COOH的生成在H₂O溶剂分子网络存在下非常容易发生, 而且在负电位下进一步降低了反应能垒, 说明*COOH生成不是速控步骤. 利用恒电位和显式溶剂化方法研究不同电位条件下的CO₂在Fe-N-C催化剂上的吸附过程, 发现CO₂吸附是一个随电位变负而增强的过程, CO₂可以在恒电位在Fe位点上形成稳定的吸附构型. 在-0.2 V的施加电位下, Fe-N-C催化剂上CO₂吸附能开始变负, 与实验结果一致. 加入第二壳层碳缺陷之后, CO₂吸附得到了显著增强, 说明第二壳层的碳缺陷可以有效改善CO₂吸附. 在三种碳缺陷当中, 5577缺陷能够引起在费米能级附近态密度的提升, 并使得Fe-N-C结构具有一定的柔性, 对于CO₂吸附具有最强的促进作用.

综上, 本研究利用恒电位和显式溶剂环境耦合的方法研究了Fe-N-C催化剂上的速控步骤, 揭示了第二壳层碳缺陷的重要作用, 对于CO₂电催化还原反应机理研究和高活性金属-氮-碳催化剂的设计提供参考.

关键词: 铁-氮-碳催化剂, CO₂电催化还原, 缺陷工程, 恒电位方法, 密度泛函计算

Abstract:

Metal-nitrogen-carbon catalysts (M-N-C) with single-atom active site are highly efficient catalysts for electrochemical CO₂ reduction reactions (CO₂RR). Abundant M-N-C catalysts have been developed, and the coordinated adjacent nitrogen atoms as first-shell environment have been the focus of research of activity-tuning. However, the effect of second-shell carbon environment around the metal-nitrogen moiety is still unclear. Moreover, it is confusing for the discrepancy between the experimental onset potential of around -0.2 V (vs. reversible hydrogen electrode, RHE, unless otherwise noted) and theoretical predictions of -0.5 V or higher by the widely-used computational hydrogen electrode (CHE) model. Herein, using the explicit solvent model and constant potential method (CPM), the electrochemical interface on Fe-N-C is simulated for CO₂RR. It reveals that the *COOH formation is facilitated in water solvent environment, while the CO₂ adsorption is potential-dependent. The predicted onset potential of around -0.2 V on Fe-N-C is consistent with experimental results. The sp² non-hexatomic defects introduced into second-shell carbon environment are significantly influential for the CO₂RR. The double five-seven ring (5577) defect is the most active, compared to that with triple five-seven ring (55577) or five-eight ring (58) defects. The highly flexible structure and altered density of states of Fe site induced by 5775 defects are key to CO₂adsorption. This study provides new insights into the role of second-shell carbon environment for effective CO₂RR, and underlines the importance of CPM and solvent environment in accurate simulation for electrochemical interface.

Key words: Iron-nitrogen-carbon catalysts, Electrochemical CO₂ reduction reaction, Defect engineering, Constant potential method, Density functional theory calculations

王梦娜, 王琪, 刘天夫, 汪国雄. 第二壳层的碳缺陷调控CO₂电催化还原的理论研究[J]. 催化学报, 2024, 66: 247-256.

Mengna Wang, Qi Wang, Tianfu Liu, Guoxiong Wang. Unexpected effect of second-shell defect in iron-nitrogen-carbon catalyst for electrochemical CO₂ reduction reaction: A DFT study[J]. Chinese Journal of Catalysis, 2024, 66: 247-256.

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图/表 6

Fig. 1. (a) The configurations of pristine, 5577, 55577, and 58 Fe-N-C catalysts. (b) The formation energy and the Fe binding energy of catalysts. Color code: grey for carbon, blue for nitrogen, orange for iron.

Fig. 2. (a) The illustration of weak adsorption of CO2 on Fe-N-C and the *COOH formation as the potential-determining step (PDS). (b) The CO2 adsorption energy and *COOH formation free energy. (c) The atomic configurations of CO2 adsorption and *COOH formation on Fe-N-C catalysts. Color code: grey for carbon, blue for nitrogen, white for hydrogen, red for oxygen, orange for iron.

Fig. 3. (a-d) The energy profile of the *COOH formation on Fe-N-C. The initial state (IS), transition state (TS), final state (FS) are shown in the inset figures. Noted that for pristine, 5577, and 58 catalysts, one of the intermediate images was used as TS, and the FS is the one with the highest energy. Color code: grey for carbon, blue for nitrogen, white for hydrogen, red for oxygen, orange for iron.

Fig. 4. (a) The energy change between the final states and initial states on pristine, 5577, 58 or transition state and initial state on 55577 dependent on applied potentials, (b) illustration of *COOH formation in aqueous solution facilitated by hydrogen-bond network and applied potential. Color code: dark grey for carbon, blue for nitrogen, light grey for hydrogen, red for oxygen, orange for iron.

Fig. 5. (a) The configurations CO2 adsorption on Fe-N-C at the applied potential of 0 V. (b) The CO2 adsorption free energy of energy profile with applied potential. The line serves as a visual guide, with markers representing the actual data points. Color code: grey for carbon, blue for nitrogen, white for hydrogen, red for oxygen, orange for iron.

Fig. 6. (a) The CO2 adsorption configurations using CHE model and CPM at potential of 0 V. The distance between C in CO2 and Fe site and the angle of O-C-O are shown. Color code: grey for carbon, blue for nitrogen, white for hydrogen, red for oxygen, orange for iron. (b) The partial density of states (PDOS) on the d-orbital of Fe site on pristine, 5577, 55577, and 58 Fe-N-C.

参考文献

[1]	D. Gao, R. M. Arán-Ais, H. S. Jeon, B. Roldan Cuenya, Nat. Catal., 2019, 2, 198-210.
[2]	K. Liu, C. Yang, R. Wei, X. Ma, C. Peng, Z. Liu, Y. Chen, Y. Yan, M. Kan, Y. Yang, G. Zheng, Sci. Bull., 2022, 67, 1042-1048.
[3]	Z. Wei, M. Cao, R. Cao, J. Electrochem., 2023, 29, 2215008.
[4]	G. Zou, W. Feng, Y. Song, G. Wang, J. Electrochem., 2023, 29, 2215006.
[5]	L. Kong, M. Wang, Y. Tuo, S. Zhou, J. Wang, G. Liu, X. Cui, J. Wang, L. Jiang, J. Energy Chem., 2024, 88, 183-193.
[6]	Y. Zhai, P. Han, Q. Yun, Y. Ge, X. Zhang, Y. Chen, H. Zhang, eScience, 2022, 2(5), 467-485.
[7]	X. Teng, Y. Niu, S. Gong, X. Liu, Z. Chen, J. Electrochem., 2022, 28, 2108441.
[8]	Y. Yang, J. Fu, T. Tang, S. Niu, L. Zhang, J. Zhang, J. Hu, Chin. J. Catal., 2022, 43, 1674-1679.
[9]	J. Gu, C. Hsu, L. Bai, H. M. Chen, X. Hu, Science, 2019, 364, 1091-1094.
[10]	Y. Yang, J. Li, C. Zhang, Z. Yang, P. Sun, S. Liu, Q. Cao, J. Phys. Chem. C, 2022, 126, 4338-4346.
[11]	J. Wang, Y. Huang, Y. Wang, H. Deng, Y. Shi, D. Wei, M. Li, C. Dong, H. Jin, S. S. Mao, S. Shen, ACS Catal., 2023, 13, 2374-2385.
[12]	Z. Shi, W. Yang, Y. Gu, T. Liao, Z. Sun, Adv. Sci., 2020, 7, 2001069.
[13]	J. Sun, X. Wu, P. Liu, J. Chen, Y. Liu, Z. Lou, J. Zhao, H. Yuan, A. Chen, X. Wang, M. Zhu, S. Dai, H. Yang, Nat. Commun., 2023, 14, 1599.
[14]	K. Liu, J. Fu, Y. Lin, T. Luo, G. Ni, H. Li, Z. Lin, M. Liu, Nat. Commun., 2022, 13, 2075.
[15]	X. Qin, S. Zhu, F. Xiao, L. Zhang, M. Shao, ACS Energy Lett., 2019, 4, 1778-1783.
[16]	W. Wang, L. Shang, G. Chang, C. Yan, R. Shi, Y. Zhao, G. I. N. Waterhouse, D. Yang, T. Zhang, Adv. Mater., 2019, 31, 1808276.
[17]	Ç. Ö. Girit, J. C. Meyer, R. Erni, M. D. Rossell, C. Kisielowski, L. Yang, C. Park, M. F. Crommie, M. L. Cohen, S. G. Louie, A. Zettl, Science, 2009, 323, 1705-1708.
[18]	A. Hashimoto, K. Suenaga, A. Gloter, K. Urita, S. Iijima, Nature, 2004, 430, 870-873.
[19]	J. Kim, N. Lee, D. Choi, D. Y. Kim, R. Kawai, Y. Yamada, J. Phys. Chem. Lett., 2021, 12, 9955-9962.
[20]	Y. Wei, J. Wu, H. Yin, X. Shi, R. Yang, M. Dresselhaus, Nat. Mater., 2012, 11, 759-763.
[21]	B. W. Jeong, J. Ihm, G. Lee, Phys. Rev. B, 2008, 78, 165403.
[22]	Y. Kim, J. Ihm, E. Yoon, G. Lee, Phys. Rev. B, 2011, 84, 075445.
[23]	S. Back, J. Lim, N. Kim, Y. Kim, Y. Jung, Chem. Sci., 2017, 8, 1090-1096.
[24]	F. Chen, Z. Yao, Z. Lyu, J. Fu, X. Zhang, J. Hu, eScience, 2024, 4, 100172.
[25]	W. Ju, A. Bagger, X. Wang, Y. Tsai, F. Luo, T. Möller, H. Wang, J. Rossmeisl, A. S. Varela, P. Strasser, ACS Energy Lett., 2019, 4, 1663-1671.
[26]	S. Ringe, C. G. Morales-Guio, L. D. Chen, M. Fields, T. F. Jaramillo, C. Hahn, K. Chan, Nat. Commun., 2020, 11, 33.
[27]	H. Cao, Z. Zhang, J. Chen, Y. Wang, ACS Catal., 2022, 12, 6606-6617.
[28]	R. Sundararaman, W. A. Goddard, III, T. A. Arias, J. Chem. Phys., 2017, 146, 114104.
[29]	J. D. Goodpaster, A. T. Bell, M. Head-Gordon, J. Phys. Chem. Lett., 2016, 7, 1471-1477.
[30]	H. Zhang, W. A. Goddard, Q. Lu, M. Cheng, Phys. Chem. Chem. Phys., 2018, 20, 2549-2557.
[31]	J. Liu, F. Luo, J. Li, J. Am. Chem. Soc., 2023, 145, 25264-25273.
[32]	Z. Zhang, H. Li, Y. Shao, L. Gan, F. Kang, W. Duan, H. A. Hansen, J. Li, Nat. Commun., 2024, 15, 612.
[33]	G. Kresse, J. Furthmüller, Comput. Mater. Sci., 1996, 6, 15-50.
[34]	G. Kresse, J. Furthmüller, Phys. Rev. B, 1996, 54, 11169-11186.
[35]	P. E. Blöchl, Phys. Rev. B, 1994, 50, 17953-17979.
[36]	G. Kresse, D. Joubert, Phys. Rev. B, 1999, 59, 1758-1775.
[37]	S. Grimme, J. Antony, S. Ehrlich, H. Krieg, J. Chem. Phys., 2010, 132, 154104.
[38]	G. Henkelman, B. P. Uberuaga, H. Jónsson, J. Chem. Phys., 2000, 113, 9901-9904.
[39]	A. A. Peterson, F. Abild-Pedersen, F. Studt, J. Rossmeisl, J. K. Nörskov, Energy Environ. Sci., 2010, 3, 1311-1315.
[40]	K. Mathew, R. Sundararaman, K. Letchworth-Weaver, T. A. Arias, R. G. Hennig, J. Chem. Phys., 2014, 140, 084106.
[41]	Z. Xia, H. Xiao, J. Chem. Theory Comput., 2023, 19, 5168-5175.
[42]	R. Sundararaman, K. Letchworth-Weaver, K. A. Schwarz, D. Gunceler, Y. Ozhabes, T. A. Arias, SoftwareX, 2017, 6, 278-284.
[43]	J. M. Clary, D. Vigil-Fowler, J. Phys. Chem. C., 2023, 127, 16405-16413.
[44]	C. Ryu, J.-S. Kim, S.-B. Rim, S.-H. Choe, C.-J. Yu, Appl. Surf. Sci., 2022, 573, 151495.
[45]	K. F. Garrity, J. W. Bennett, K. M. Rabe, D. Vanderbilt, Comput. Mater. Sci., 2014, 81, 446-452.
[46]	M. Ernzerhof, G. E. Scuseria, J. Chem. Phys., 1999, 110, 5029-5036.
[47]	L. Liu, H. Xiao, J. Am. Chem. Soc., 2023, 145, 14267-14275.
[48]	P. Li, Y. Jiang, Y. Hu, Y. Men, Y. Liu, W. Cai, S. Chen, Nat. Catal., 2022, 5, 900-911.
[49]	J. P. Perdew, A. Ruzsinszky, G. I. Csonka, O. A. Vydrov, G. E. Scuseria, L. A. Constantin, X. Zhou, K. Burke, Phys. Rev. Lett., 2008, 100, 136406
[50]	R. Sundararaman, W. A. Goddard, III, J. Chem. Phys., 2015, 142, 064107.
[51]	R. Nelson, C. Ertural, J. George, V. L. Deringer, G. Hautier, R. Dronskowski, J. Comput. Chem., 2020, 41, 1931-1940.
[52]	V. L. Deringer, A. L. Tchougréeff, R. Dronskowski, J. Phys. Chem. A., 2011, 115, 5461-5466.
[53]	A. Chen, H. Tong, C. Wu, S. Li, P. Jia, W. Zhou, Phys. Chem. Chem. Phys., 2024, 26, 421-429.
[54]	P. Vajeeston, R. Vidya, P. Ravindran, H. Fjellvåg, A. Kjekshus, A. Skjeltorp, Phys. Rev. B, 2002, 65, 075101.
[55]	R. Y. Rohling, I. C. Tranca, E. J. M. Hensen, E. A. Pidko, J. Phys. Chem. C., 2019, 123, 2843-2854.
[56]	T. Zheng, C. Liu, C. Guo, M. Zhang, X. Li, Q. Jiang, W. Xue, H. Li, A. Li, C. Pao, J. Xiao, C. Xia, J. Zeng, Nat. Nanotechnol., 2021, 16, 1386-1393.
[57]	T. N. Huan, N. Ranjbar, G. Rousse, M. Sougrati, A. Zitolo, V. Mougel, F. Jaouen, M. Fontecave, ACS Catal., 2017, 7, 1520-1525.
[58]	L. Lin, H. Li, Y. Wang, H. Li, P. Wei, B. Nan, R. Si, G. Wang, X. Bao, Angew. Chem. Int. Ed., 2021, 60, 26582-26586.
[59]	Q. Wu, C. Dai, F. Meng, Y. Jiao, Z. J. Xu, Nat. Commun., 2024, 15, 1095.
[60]	X. Nie, M. R. Esopi, M. J. Janik, A. Asthagiri, Angew. Chem. Int. Ed., 2013, 52, 2459-2462.
[61]	Y. Yang, J. Fu, Y. Ouyang, T. Tang, Y. Zhang, L. Zheng, Q. Zhang, X. Liu, J. Wang, J. Hu, Natl. Sci. Rev., 2023, 10, nwac248.

第二壳层的碳缺陷调控CO₂电催化还原的理论研究

Unexpected effect of second-shell defect in iron-nitrogen-carbon catalyst for electrochemical CO₂ reduction reaction: A DFT study

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