理论设计和实验研究吡啶掺杂聚合氮化碳提升光催化CO2还原性能

doi:10.1016/S1872-2067(22)64159-7

催化学报 ›› 2023, Vol. 46: 91-102.DOI: 10.1016/S1872-2067(22)64159-7

理论设计和实验研究吡啶掺杂聚合氮化碳提升光催化CO₂还原性能

陈成成^a, 刘芳庭^a, 张巧钰^a, 张正国^a^,^c, 刘琼^b^,^*(), 方晓明^a^,^c^,^*()

^a华南理工大学化学与化工学院, 传热强化与过程节能教育部重点实验室, 广东广州 510640
^b广东省科学院测试分析研究所(中国广州分析测试中心), 广东广州 510070
^c华南理工大学广东省热能高效储存与利用工程技术研究中心, 广东广州 510640

收稿日期:2022-09-29 接受日期:2022-11-02 出版日期:2023-03-18 发布日期:2023-02-21
通讯作者: *电子信箱: cexmfang@scut.edu.cn (方晓明),liuqiong@fenxi.com.cn (刘琼)
基金资助:
广东省自然科学基金(2022A1515011737);广东省科学院科技发展项目(2021GDASYL-20210102010)

Theoretical design and experimental study of pyridine-incorporated polymeric carbon nitride with an optimal structure for boosting photocatalytic CO₂ reduction

Chengcheng Chen^a, Fangting Liu^a, Qiaoyu Zhang^a, Zhengguo Zhang^a^,^c, Qiong Liu^b^,^*(), Xiaoming Fang^a^,^c^,^*()

^aKey Laboratory of Heat Transfer Enhancement and Energy Conservation of Education Ministry, School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
^bInstitute of Analysis, Guangdong Academy of Sciences (China National Analytical Center, Guangzhou), Guangzhou 510070, Guangdong, China
^cGuangdong Engineering Technology Research Center of Efficient Heat Storage and Application, South China University of Technology, Guangzhou 510640, Guangdong, China

Received:2022-09-29 Accepted:2022-11-02 Online:2023-03-18 Published:2023-02-21
Contact: *E-mail: cexmfang@scut.edu.cn (X. Fang), liuqiong@fenxi.com.cn (Q. Liu)
Supported by:
Natural Science Foundation of Guangdong Province(2022A1515011737);The Guangdong Academy of Sciences Project of Science and Technology Development(2021GDASYL-20210102010)

摘要/Abstract

摘要：

光催化CO₂还原是利用太阳光和水将CO₂转化为高价值化学品或燃料(如CO、甲醇、甲烷等), 被认为是解决CO₂问题的理想途径之一. CO₂分子中C=O离解能高而活化困难, 且光催化CO₂还原涉及多质子耦合多电子转移过程且产物多样, 因而研制效率高且选择性好的光催化剂是该技术的关键. 聚合物氮化碳(PCN)作为一种结构可调的有机光催化剂, 具有化学稳定性好且能带位置适宜于还原CO₂的优势, 是一种具有发展潜力的CO₂还原光催化剂; 但是PCN也存在因其禁带宽度较大而对可见光响应范围有限以及因其结构由三均三嗪单元构成而缺乏足够活性位点来吸附和活化CO₂等不足. 目前在提升PCN的光催化CO₂还原性能方面已有不少研究, 但所得的PCN基光催化剂在效率和选择性上仍处于较低水平. 考虑到光催化CO₂还原涉及复杂的热力学和动力学要求, 对基于PCN的光催化剂进行精准设计和研究是非常必要的, 这有望获得同时具有可见光吸收增强、光生载流子复合减少、吸附和活化CO₂的位点增加以及能带位置适宜等特性的高性能光催化剂. 为此, 本论文采用理论设计与实验研究相结合的方法, 以吡啶掺杂PCN为模型, 研制了一种用于CO₂还原的高性能PCN基光催化剂.

本文设计了将吡啶掺杂到PCN结构单元中不同位置的两种结构, 并运用理论计算确定其中禁带宽度较窄、更利于光生载流子分离、更有助于CO₂吸附和活化以及总能量较低的结构作为最优结构. 然后, 采用尿素与适量的2-氨基吡啶共聚的方法, 制备了吡啶掺杂的PCN样品, 并通过一系列表征确定结构设计成功. 还测定了所得吡啶掺杂PCN样品的光学和光电化学特性, 评价了它们光催化CO₂还原的活性和选择性. 最后, 通过理论计算和实验研究, 阐明了该吡啶掺杂PCN光催化剂的性能增强机制及其光催化还原CO₂的反应路径. 结果表明, 以CO(bpy)₂为助催化剂, 本文制备的吡啶掺杂PCN(CN-5%AP)光催化剂不仅取得了较高的CO产量, 而且还获得99.6%的CO选择性, 在λ = 420 nm处的表观量子效率可达2.86%. 研究表明, 该吡啶掺杂的PCN光催化性能增强主要源于其提升的CO₂吸附容量以及对CO₂还原为CO反应的促进. 综上, 本工作为设计和制备实现高效CO₂还原的光催化剂提供了参考.

关键词: 光催化CO₂还原, 先理论后实验, 聚合氮化碳, 密度泛函理论, 吡啶

Abstract:

Herein, pyridine-incorporated polymeric carbon nitride (PCN) was explored for boosting photocatalytic CO₂ reduction. First, theoretical calculations were performed on PCN models with pyridine molecules located at different positions to determine the optimal structure of pyridine-incorporated PCN with the lowest total energy, smallest bandgap, and most efficient CO₂ adsorption and activation processes. Subsequently, pyridine-incorporated PCN with the optimal structure was prepared experimentally by copolymerizing urea and 2-aminopyridine (AP). A high CO evolution rate with a selectivity of 99.6% was achieved by combining CN-5%AP with a Co(bpy)₂ co-catalyst, which resulted an apparent quantum efficiency of 2.86% at λ = 420 nm. The high performance of pyridine-incorporated PCN mainly originated from its strong CO₂ adsorption ability and facilitation of the CO₂-to-CO reduction reaction. This work paves the way for the precise design and preparation of photocatalysts with high CO₂ reduction efficiency.

Key words: Photocatalytic CO₂ reduction, Theoretical first and then experiment, Polymeric carbon nitride, Density functional theory, Pyridine

陈成成, 刘芳庭, 张巧钰, 张正国, 刘琼, 方晓明. 理论设计和实验研究吡啶掺杂聚合氮化碳提升光催化CO₂还原性能[J]. 催化学报, 2023, 46: 91-102.

Chengcheng Chen, Fangting Liu, Qiaoyu Zhang, Zhengguo Zhang, Qiong Liu, Xiaoming Fang. Theoretical design and experimental study of pyridine-incorporated polymeric carbon nitride with an optimal structure for boosting photocatalytic CO₂ reduction[J]. Chinese Journal of Catalysis, 2023, 46: 91-102.

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图/表 7

Fig. 1. The DFT model structures of BCN (a), CN-N2 (b) and CN-N3 (c), calculated band gaps of BCN (d), CN-N2 (e) and CN-N3(f), and density of states of BCN (g), CN-N2 (h) and CN-N3 (i).

Fig. 2. The DFT model structure of CO2 molecule on BCN (a), CO2 on CN-N2 (b), CO2 on CN-N3 (c), together with the electron density difference of CO2 on BCN(d), CO2 on CN-N2(e), CO2 on CN-N3 (f).

Fig. 3. XPS high resolution C 1s (a) and N 1s (b) spectra of BCN, CN-5%AP and CN-10%AP. (c) The XANES C K-edge profiles of BCN and CN-5%AP. (d) Solid-state 13C MAS NMR spectra of BCN and CN-5%AP. (e) TGA curves of urea, AP, and their mixture (the inset is the enlarge profile range from 200 to 300 °C). (f) High resolution mass spectrum of the product prepared by heating the mixture consisting of urea and 5% AP at 200 °C for 30 min.

Scheme 1. Speculated formation mechanism of the pyridine incorporated PCN containing the CN-N2 structure.

Fig. 4. DRS spectra (a), the Kubelk-Munk function (b) and PL emission spectra (c) of BCN, CN-3%AP, CN-5%AP and CN-7%AP. (d) Time-resolved PL decay spectra of BCN and CN-5%AP.

Fig. 5. CO release rate (a) and selectivity (b) of BCN and CN-x%AP under the illumination of a LED of 3 W. (c) A comparison in CO release rate between BCN and CN-5%AP under irradiation of the 300 W Xe lamp. (d) The AQE of CN-5%AP.

Fig. 6. CO2 TPD (a) and CO2 absorption uptake (b) of BCN and CN-5%AP and reaction coordination path (c) over BCN and CN-N2. (d) In situ FTIR spectra for the adsorption and activation of CO2 on CN-5%AP.

参考文献

[1]	S. J. Davis, K. Caldeira, H. D. Matthews, Science, 2010, 329, 1330-1333.
[2]	Z.-J. Wang, H. Song, H. Liu, J. Ye, Angew. Chem. Int. Ed., 2020, 59, 8016-8035.
[3]	A. Corma, H. Garcia, J. Catal., 2013, 308, 168-175.
[4]	N. N. Vu, S. Kaliaguine, T. O. Do, Adv. Funct. Mater., 2019, 29, 1901825.
[5]	P. Prabhu, V. Jose, J.-M. Lee, Adv. Funct. Mater., 2020, 30, 1910768.
[6]	X. Chang, T. Wang, J. Gong, Energy Environ. Sci., 2016, 9, 2177-2196.
[7]	W. A. Thompson, E. S. Fernandez, M. M. Maroto-Valer, ACS Sustainable Chem. Eng., 2020, 8, 4677-4692.
[8]	J. Bian, Z. Zhang, J. Feng, M. Thangamuthu, F. Yang, L. Sun, Z. Li, Y. Qu, D. Tang, Z. Lin, F. Bai, J. Tang, L. Jing, Angew. Chem. Int. Ed., 2021, 60, 20906-20914.
[9]	X. Li, J. Yu, M. Jaroniec, X. Chen, Chem. Rev., 2019, 119, 3962-4179.
[10]	M. Fujihira, Y. Satoh, T. Osa, Nature, 1981, 293, 206-208.
[11]	Y. Wang, S. Wang, S. L. Zhang, X. W. Lou, Angew. Chem. Int. Ed., 2020, 59, 11918-11922.
[12]	L. Mohapatra, K. Parida, J. Mater. Chem. A, 2016, 4, 10744-10766.
[13]	L. Du, Y. Chen, Q. Wang, Y. Zhao, L. Li, X. Liu, G. Tian, Small, 2021, 17, 2100412.
[14]	D. Liu, Y. Xu, M. Sun, Y. Huang, Y. Yu, B. Zhang, J. Mater. Chem. A, 2020, 8, 1077-1083.
[15]	F. He, A. Meng, B. Cheng, W. Ho, J. Yu, Chin. J. Catal., 2020, 41, 9-20.
[16]	K. Qi, B. Cheng, J. Yu, W. Ho, Chin. J. Catal., 2017, 38, 1936-1955.
[17]	J. Wang, G. Wang, B. Cheng, J. Yu, J. Fan, Chin. J. Catal., 2021, 42, 56-68.
[18]	Y. Fu, Z. Li, Q. Liu, X. Yang, H. Tang, Chin. J. Catal., 2017, 38, 2160-2170.
[19]	Z. Wang, T. Hu, K. Dai, J. Zhang, C. Liang, Chin. J. Catal., 2017, 38, 2021-2029.
[20]	H. Shen, T. Peppel, J. Strunk, Z. Sun, Solar RRL, 2020, 4, 1900546.
[21]	F. Zhao, Y. Feng, Y. Wang, X. Zhang, X. Liang, Z. Li, F. Zhang, T. Wang, J. Gong, W. Feng, Nat. Commun., 2020, 11, 1443.
[22]	L. Shi, X. Ren, Q. Wang, W. Zhou, J. Ye, J. Mater. Chem. A, 2021, 9, 2421-2428.
[23]	Y. Fang, X. Wang, Chem. Commun., 2018, 54, 5674-5687.
[24]	S. Cao, J. Low, J. Yu, M. Jaroniec, Ad. Mater., 2015, 27, 2150-2176.
[25]	J. Liang, Z. Jiang, P. K. Wong, C.-S. Lee, Solar RRL, 2021, 5, 2100401.
[26]	Y. Zhang, B. Xia, J. Ran, K. Davey, S. Z. Qiao, Adv. Energy Mater., 2020, 10, 1903879.
[27]	L. Cheng, D. Zhang, Y. Liao, J. Fan, Q. Xiang, Chin. J. Catal., 2021, 42, 131-140.
[28]	M. Majdoub, Z. Anfar, A. Amedlous, ACS Nano, 2020, 14, 12390-12469.
[29]	H. Qin, R.-T. Guo, X.-Y. Liu, X. Shi, Z.-Y. Wang, J.-Y. Tang, W.-G. Pan, Colloids. Surf. A, 2020, 600, 124912.
[30]	G. Gao, Y. Jiao, E. R. Waclawik, A. Du, J. Am. Chem. Soc., 2016, 138, 6292-6297.
[31]	P. Madhusudan, R. Shi, S. Xiang, M. Jin, B. N. Chandrashekar, J. Wang, W. Wang, O. Peng, A. Amini, C. Cheng, Appl. Catal. B, 2021, 282, 119600.
[32]	Y. Li, B. Li, D. Zhang, L. Cheng, Q. Xiang, ACS Nano, 2020, 14, 10552-10561.
[33]	X. Huang, W. Gu, Y. Ma, D. Liu, N. Ding, L. Zhou, J. Lei, L. Wang, J. Zhang, Res. Chem. Intermed., 2020, 46, 5133-5164.
[34]	P. Yang, H. Zhuzhang, R. Wang, W. Lin, X. Wang, Angew. Chem. Int. Ed., 2019, 58, 1134-1137.
[35]	P. Huang, J. Huang, S. A. Pantovich, A. D. Carl, T. G. Fenton, C. A. Caputo, R. L. Grimm, A. I. Frenkel, G. Li, J. Am. Chem. Soc., 2018, 140, 16042-16047.
[36]	J. Jiang, S. Cao, C. Hu, C. Chen, Chin. J. Catal., 2017, 38, 1981-1989.
[37]	Y. Ren, D. Zeng, W.-J. Ong, Chin. J. Catal., 2019, 40, 289-319.
[38]	Q. Liu, H. Cheng, T. Chen, T. W. B. Lo, J. Ma, A. Ling, F. Wang, Appl. Catal. B, 2021, 295, 120289.
[39]	J. A. Tossell, Comput. Theor. Chem., 2011, 977, 123-127.
[40]	E. E. Barton, D. M. Rampulla, A. B. Bocarsly, J. Am. Chem. Soc., 2008, 130, 6342-6344.
[41]	W. Yang, X. Shan, Y. Chen, Y. Gao, Diam. Relat. Mater., 2020, 108, 107926.
[42]	Z. H. Chen, P. Sun, B. Fan, Q. Liu, Z. G. Zhang, X. M. Fang, Appl. Catal. B, 2015, 170- 171, 10-16.
[43]	M. Li, L. Zhang, X. Fan, M. Wu, Y. Du, M. Wang, Q. Kong, L. Zhang, J. Shi, Appl. Catal. B, 2016, 190, 36-43.
[44]	R.-L. Cheng, X.-X. Jin, X.-Q. Fan, M. Wang, J.-J. Tian, L.-X. Zhang, J.-L. Shi, Acta Phys.-Chim. Sin., 2017, 33, 1436-1445.
[45]	Q. Meng, H. Lv, M. Yuan, Z. Chen, Z. Chen, X. Wang, ACS Omega, 2017, 2, 2728-2739.
[46]	C. M. Li, H. H. Wu, D. Q. Zhu, T. X. Zhou, M. Yan, G. Chen, J. X. Sun, G. Dai, F. Ge, H. J. Dong, Appl. Catal. B, 2021, 297, 120433.
[47]	B. Zhu, J. Zhang, C. Jiang, B. Cheng, J. Yu, Appl. Catal. B, 2017, 207, 27-34.
[48]	M. K. Barman, M. Chatterjee, B. Srivastava, B. Mandal, J. Chem. Eng. Data, 2015, 60, 2197-2208.
[49]	F. Zhang, J. Li, H. Wang, Y. Li, Y. Liu, Q. Qian, X. Jin, X. Wang, J. Zhang, G. Zhang, Appl. Catal. B, 2020, 269, 118772.
[50]	Q. Liu, X. Wang, Q. Yang, Z. Zhang, X. Fang, Appl. Catal. B, 2018, 225, 22-29.
[51]	CAS:2244140-57-4, Predicted NMR data calculated using Advanced Chemistry Development.
[52]	CAS:887001-51-6, Predicted NMR data calculated using Advanced Chemistry Development.
[53]	Q. Yang, C. C. Chen, Q. Y. Zhang, Z. G. Zhang, X. M. Fang, Carbon, 2020, 164, 337-348.
[54]	G. Fanchini, S. C. Ray, A. Tagliaferro, E. Laurenti, Diam. Relat. Mater., 2002, 11, 1143-1148.
[55]	G. Liu, G. Zhao, W. Zhou, Y. Liu, H. Pang, H. Zhang, D. Hao, X. Meng, P. Li, T. Kako, J. Ye, Adv. Funct. Mater., 2016, 26, 6822-6829.
[56]	L. Lin, H. Ou, Y. Zhang, X. Wang, ACS Catal., 2016, 6, 3921-3931.
[57]	D. Gao, Q. Xu, J. Zhang, Z. Yang, M. Si, Z. Yan, D. Xue, Nanoscale, 2014, 6, 2577-2581.
[58]	X. Fan, L. Zhang, R. Cheng, M. Wang, M. Li, Y. Zhou, J. Shi, ACS Catal., 2015, 5, 5008-5015.
[59]	G. Zhang, X. Wang, J. Catal., 2013, 307, 246-253.
[60]	Q. Liu, H. Cheng, T. Chen, T. W. B. Lo, Z. Xiang, F. Wang, Energy Environ. Sci., 2022, 15, 225-233.
[61]	Y. Pu, Y. Luo, X. Wei, J. Sun, L. Li, W. Zou, L. Dong, Appl. Catal. B, 2019, 254, 580-586.
[62]	Q. Liu, C. Chen, K. Yuan, C. D. Sewell, Z. Zhang, X. Fang, Z. Lin, Nano Energy, 2020, 77, 105104.

理论设计和实验研究吡啶掺杂聚合氮化碳提升光催化CO₂还原性能

Theoretical design and experimental study of pyridine-incorporated polymeric carbon nitride with an optimal structure for boosting photocatalytic CO₂ reduction

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