探究Cu/ZnO相互作用对CO2加氢制甲醇反应性能的影响

doi:10.3866/PKU.WHXB202009101

物理化学学报 >> 2021, Vol. 37 >> Issue (5): 2009101.doi: 10.3866/PKU.WHXB202009101

所属专题： CO₂还原

探究Cu/ZnO相互作用对CO₂加氢制甲醇反应性能的影响

李聪明¹^,*(), 陈阔¹, 王晓月¹, 薛楠², 杨恒权²^,*()

¹ 太原理工大学煤科学与技术教育部与山西省重点实验室，太原 030024
² 山西大学化学化工学院，太原 030006

收稿日期:2020-09-30 录用日期:2020-10-30 发布日期:2020-11-06
通讯作者: 李聪明,杨恒权 E-mail:licongming0523@163.com;hqyang@sxu.edu.cn
基金资助:
国家自然科学基金(21676176);山西省重大科技项目(20201102005);煤转化重点实验室基金(J20-21-610);催化国家重点实验室基金(N-15-05)

Understanding the Role of Cu/ZnO Interaction in CO₂ Hydrogenation to Methanol

Congming Li¹^,*(), Kuo Chen¹, Xiaoyue Wang¹, Nan Xue², Hengquan Yang²^,*()

¹ Key Laboratory of Coal Science and Technology, Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, China
² School of Chemistry and Chemical Engineering, Shanxi University, Taiyuan 030006, China

Received:2020-09-30 Accepted:2020-10-30 Published:2020-11-06
Contact: Congming Li,Hengquan Yang E-mail:licongming0523@163.com;hqyang@sxu.edu.cn
About author:Email:hqyang@sxu.edu.cn (H.Y.)
Email: licongming0523@163.com (C.L.)
Supported by:
the National Natural Science Foundation of China(21676176);Major Scientific and Technological Project of Shanxi Province of China(20201102005);the Foundation of State Key Laboratory of Coal Conversion(J20-21-610);the Fund of State Key Laboratory of Catalysis in DICP, China(N-15-05)

摘要/Abstract

摘要：

利用可再生绿氢和二氧化碳生产甲醇是未来解决二氧化碳排放的根本途径之一，而研发高效稳定的甲醇合成催化剂是决定整个合成工艺的关键因素之一。负载型催化剂（金属纳米颗粒负载在载体表面）在甲醇合成反应中占有重要地位，而金属-载体相互作用常被用来稳定金属颗粒，调控催化剂活性、选择性和稳定性。尽管对金属-载体相互作用进行了大量研究，但是关于不同强度金属-载体相互作用对催化剂的结构和性能影响的理解仍然是匮乏的。本工作合成了三种具有不同强度金属-载体相互作用的Cu/ZnO-SiO₂催化剂，探究了其对CO₂加氢制甲醇反应性能的影响。H₂-TPR和XPS表征结果表明，通过改变沉淀顺序可以调变Cu/ZnO-SiO₂催化剂中金属-载体相互作用，FT-IR结果证实了Cu物种均以CuO的形式存在。TEM、XRD和N₂O化学吸附结果表明Cu/ZnO强的相互作用促进了Cu物种的分散，提高了CO₂转化率和催化剂的稳定性。正如预期，Re-CZS催化剂实现了最高的CO₂转化率(12.4%)，而Co-CZS催化剂与Nor-CZS催化剂的CO₂转化率分别为12.1%和9.8%。反应相同时间后，标准化的CO₂转化率降低顺序是：Re-CZS (75%) > Co-CZS (70%) > Nor-CZS (65%)。与Co-CZS和Nor-CZS催化剂不同，Re-CZS催化剂的甲醇选择性随着反应进行逐步增加而后趋于稳定。对该催化剂在反应过程中的结构演变进行表征，结果显示，Re-CZS催化剂Cu/ZnO间强的相互作用引起了催化剂结构重构，促使体相中的ZnO物种向催化剂表面Cu物种迁移，形成了更多的Cu/ZnO界面，有利于甲醇的生成。本工作为合理设计有效催化剂提供一个可行策略。

关键词: Cu/ZnO-SiO₂催化剂, 金属-载体相互作用, CO₂加氢, 甲醇

Abstract:

Using renewable green hydrogen and carbon dioxide (CO₂) to produce methanol is one of the fundamental ways to reduce CO₂ emissions in the future, and research and development related to catalysts for efficient and stable methanol synthesis is one of the key factors in determining the entire synthesis process. Metal nanoparticles stabilized on a support are frequently employed to catalyze the methanol synthesis reaction. Metal-support interactions (MSIs) in these supported catalysts can play a significant role in catalysis. Tuning the MSI is an effective strategy to modulate the activity, selectivity, and stability of heterogeneous catalysts. Numerous studies have been conducted on this topic; however, a systematic understanding of the role of various strengths of MSI is lacking. Herein, three Cu/ZnO-SiO₂ catalysts with different strengths of MSI, namely, normal precipitation Cu/ZnO-SiO₂ (Nor-CZS), co-precipitation Cu/ZnO-SiO₂ (Co-CZS), and reverse precipitation Cu/ZnO-SiO₂ (Re-CZS), were successfully prepared to determine the role of such interactions in the hydrogenation of CO₂ to methanol. The results of temperature-programmed reduction (H₂-TPR) and X-ray photoelectron spectroscopy (XPS) characterization illustrated that the MSI of the catalysts was considerably affected by the precipitation sequence. Fourier transform infrared reflection spectroscopy (FT-IR) results indicated that the Cu species existed as CuO in all cases and that copper phyllosilicate was absent (except for strong Cu-SiO₂ interaction). Transmission electron microscopy (TEM), X-ray diffraction (XRD), and N₂O chemical titration results revealed that strong interactions between the Cu and Zn species would promote the dispersion of Cu species, thereby leading to a higher CO₂ conversion rate and improved catalytic stability. As expected, the Re-CZS catalyst exhibited the highest activity with 12.4% CO₂ conversion, followed by the Co-CZS catalyst (12.1%), and the Nor-CZS catalyst (9.8%). After the same reaction time, the normalized CO₂ conversion of the three catalysts decreased in the following order: Re-CZS (75%) > Co-CZS (70%) > Nor-CZS (65%). Notably, the methanol selectivity of the Re-CZS catalyst was found to level off after a prolonged period, in contrast to that of Co-CZS and Nor-CZS. Investigation of the structural evolution of the catalyst with time on stream revealed that the high methanol selectivity of the catalyst was caused by the reconstruction of the catalyst, which was induced by the strong MSI between the Cu and Zn species, and the migration of ZnO onto Cu species, which caused an enlargement of the Cu/ZnO interface. This work offers an alternative strategy for the rational and optimized design of efficient catalysts.

Key words: Cu/ZnO-SiO₂ catalysts, Metal-support interaction, CO₂ hydrogenation, Methanol

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李聪明, 陈阔, 王晓月, 薛楠, 杨恒权. 探究Cu/ZnO相互作用对CO₂加氢制甲醇反应性能的影响[J]. 物理化学学报, 2021, 37(5), 2009101. doi: 10.3866/PKU.WHXB202009101

Congming Li, Kuo Chen, Xiaoyue Wang, Nan Xue, Hengquan Yang. Understanding the Role of Cu/ZnO Interaction in CO₂ Hydrogenation to Methanol[J]. Acta Phys. -Chim. Sin. 2021, 37(5), 2009101. doi: 10.3866/PKU.WHXB202009101

链接本文: https://www.whxb.pku.edu.cn/CN/10.3866/PKU.WHXB202009101

https://www.whxb.pku.edu.cn/CN/Y2021/V37/I5/2009101

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参考文献 46

1	García-Trenco A. ; Regoutz A. ; White E. R. ; Payne D. J. ; Shaffer M. S. P. ; Williams C. K. Appl. Catal. B 2018, 220, 9. doi: 10.1016/j.apcatb.2017.07.069
2	Reichenbach T. ; Walter M. ; Moseler M. ; Hammer B. ; Bruix A. J. Phys. Chem. C 2019, 123, 30903. doi: 10.1021/acs.jpcc.9b07715
3	Li M. M. -J. ; Tsang S. C. E. Catal. Sci. Technol. 2018, 8, 3450. doi: 10.1039/C8CY00304A
4	Grabow L. C. ; Mavrikakis M. ACS Catal. 2011, 1, 365. doi: 10.1021/cs200055d
5	Zhong J. ; Yang X. ; Wu Z. ; Liang B. ; Huang Y. ; Zhang T. Chem. Soc. Rev. 2020, 49, 1385. doi: 10.1039/c9cs00614a
6	van Deelen T. W. ; Hernández Mejía C. ; de Jong K. P. Nat. Catal. 2019, 2, 955. doi: 10.1038/s41929-019-0364-x
7	Yoshihara J. ; Parker S. C. ; Schafer A. ; Campbell C. T. Catal. Lett. 1995, 31, 313. doi: 10.1007/BF00808595
8	Yoshihara J. ; Campbell C. T. J. Catal. 1996, 161, 776. doi: 10.1006/jcat.1996.0240
9	Fujitani T. ; Matsuda T. ; Kushida Y. ; Ogihara S. ; Uchijima T. ; Nakamura J. Catal. Lett. 1997, 49, 175. doi: 10.1023/A:1019069708459
10	Choia Y. ; Futagamia K. ; Fujitani T. ; Nakamuraa J. Appl. Catal. A 2001, 208, 163. doi: 10.1016/S0926-860X(00)00712-2
11	Kuld S. ; Thorhauge M. ; Falsig H. ; Elkjær C. F. ; Helveg S. ; Chorkendorff I. ; Sehested J. Science 2016, 352, 969. doi: 10.1126/science.aaf0718
12	Xie C. ; Niu Z. ; Kim D. ; Li M. ; Yang P. Chem. Rev. 2020, 120, 1184. doi: 10.1021/acs.chemrev.9b00220
13	Kattel S. ; Ramírez P. J. ; Chen J. G. ; Rodriguez J. A. ; Liu P. Science 2017, 355, 1296. doi: 10.1126/science.aal3573
14	Liao F. ; Huang Y. ; Ge J. ; Zheng W. ; Tedsree K. ; Collier P. ; Hong X. ; Tsang S. C. Angew. Chem. Int. Ed. 2011, 50, 2162. doi: 10.1002/anie.201007108
15	Heenemann M. ; Millet M. -M. ; Girgsdies F. ; Eichelbaum M. ; Risse T. ; Schlögl R. ; Jones T. ; Frei E. ACS Catal. 2020, 10, 5672. doi: 10.1021/acscatal.0c024000574
16	Lunkenbein T. ; Schumann J. ; Behrens M. ; Schlogl R. ; Willinger M. G. Angew. Chem. Int. Ed. 2015, 54, 4544. doi: 10.1002/anie.201411581
17	Martin O. ; Mondelli C. ; Curulla-Ferré D. ; Drouilly C. ; Hauert R. ; Pérez-Ramírez J. ACS Catal. 2015, 5, 5607. doi: 10.1021/acscatal.5b00877
18	Sun Y. ; Huang C. ; Chen L. ; Zhang Y. ; Fu M. ; Wu J. ; Ye D. J. CO₂ Util 2020, 37, 55. doi: 10.1016/j.jcou.2019.11.029
19	Chen K. ; Yu J. ; Liu B. ; Si C. ; Ban H. ; Cai W. ; Li C. ; Li Z. ; Fujimoto K. J. Catal. 2019, 372, 163. doi: 10.1016/j.jcat.2019.02.035
20	Xin Q. ; Papavasiliou A. ; Boukos N. ; Glisenti A. ; Li J. P. H. ; Yang Y. ; Philippopoulos C. J. ; Poulakis E. ; Katsaros F.K. ; Meynen V. ; et al Appl. Catal. B 2018, 223, 103. doi: 10.1016/j.apcatb.2017.03.071
21	Yin A. ; Guo X. ; Dai W. L. ; Fan K. J. Phys. Chem. C 2009, 113, 11003. doi: 10.1021/jp902688b
22	Batista J. ; Pintar A. ; Mandrino D. ; Jenko M. ; Martin V. Appl. Catal. A 2001, 206, 113. doi: 10.1016/S0926-860X(00)00589-5
23	Zhao Y. ; Zhang Y. ; Wang Y. ; Zhang J. ; Xu Y. ; Wang S. ; Ma X. Appl. Catal. A 2017, 539, 59. doi: 10.1016/j.apcata.2017.04.001
24	Tian J. ; Chen W. ; Wu P. ; Zhu Z. ; Li X. Catal. Sci. Technol. 2018, 8, 2624. doi: 10.1039/c8cy00023a
25	Chen L. ; Guo P. ; Qiao M. ; Yan S. ; Li H. ; Shen W. ; Xu H. ; Fan K. J. Catal. 2008, 257, 172. doi: 10.1016/j.jcat.2008.04.021
26	Wang Y. ; Shen Y. ; Zhao Y. ; Lv J. ; Wang S. ; Ma X. ACS Catal. 2015, 5, 6200. doi: 10.1021/acscatal.5b01678
27	Yue H. ; Zhao Y. ; Zhao S. ; Wang B. ; Ma X. ; Gong J. Nat. Commun. 2013, 4, 2339. doi: 10.1038/ncomms3339
28	Xu X. ; Cao X. ; Zhao L. ; Wang H. ; Yu H. ; Gao B. Environ. Sci. Pollut. Res. Int. 2013, 20, 358. doi: 10.1007/s11356-012-0873-5
29	Constantinou D. A. ; Fierro J. L. G. ; Efstathiou A. M. Appl. Catal. B 2010, 95, 255. doi: 10.1016/j.apcatb.2010.01.003
30	Ai P. ; Tan M. ; Reubroycharoen P. ; Wang Y. ; Feng X. ; Liu G. ; Yang G. ; Tsubaki N. Catal. Sci. Technol. 2018, 8, 6441. doi: 10.1039/C8CY02093K
31	Witoon T. ; Permsirivanich T. ; Donphai W. ; Jaree A. ; Chareonpanich M. Fuel Process. Technol. 2013, 116, 72. doi: 10.1016/j.fuproc.2013.04.024
32	d'Alnoncourt R. N. ; Xia X. ; Strunk J. ; Loffler E. ; Hinrichsen O. ; Muhler M. Phys. Chem. Chem. Phys. 2006, 8, 1525. doi: 10.1039/B515487A
33	Karelovic A. ; Ruiz P. Catal. Sci. Technol. 2015, 5, 869. doi: 10.1039/C4CY00848K
34	van den Berg R. ; Prieto G. ; Korpershoek G. ; van der Wal L. I. ; van Bunningen A. J. ; Lægsgaard-Jørgensen S. ; de Jongh P. E. ; de Jong K. P. Nat. Commun. 2016, 7, 13057. doi: 10.1038/ncomms13057
35	Liu C. ; Yang B. ; Tyo E. ; Seifert S. ; DeBartolo J. ; von Issendorff B. ; Zapol P. ; Vajda S. ; Curtiss L. A. J. Am. Chem. Soc. 2015, 137, 8676. doi: 10.1021/jacs.5b03668
36	Numpilai T. ; Wattanakit C. ; Chareonpanich M. ; Limtrakul J. ; Witoon T. Energy Convers. Manage. 2019, 180, 511. doi: 10.1016/j.enconman.2018.11.011
37	Fujitani T. ; Nakamura J. Catal. Lett. 1998, 56, 119. doi: 10.1023/A:1019000927366
38	van den Berg R. ; Parmentier T. E. ; Elkjær C. F. ; Gommes C. J. ; Sehested J. ; Helveg S. ; de Jongh P. E. ; de Jong K. P. ACS Catal. 2015, 5, 4439. doi: 10.1021/acscatal.5b00833
39	Tisseraud C. ; Comminges C. ; Belin T. ; Ahouari H. ; Soualah A. ; Pouilloux Y. ; Le Valant A. J. Catal. 2016, 343, 106. doi: 10.1016/j.jcat.2015.12.005
40	Gao P. ; Xie R. ; Wang H. ; Zhong L. ; Xia L. ; Zhang Z. ; Wei W. ; Sun Y. H. J. CO₂ Util. 2015, 11, 41. doi: 10.1016/j.jcou.2014.12.008
41	Gao P. ; Li F. ; Zhan H. ; Zhao N. ; Xiao F. ; Wei W. ; Zhong L. ; Wang H. ; Sun Y. J. Catal. 2013, 298, 51. doi: 10.1016/j.jcat.2012.10.030
42	Hu B. ; Yin Y. ; Liu G. ; Chen S. ; Hong X. ; Tsang S. C. E. J. Catal. 2018, 359, 17. doi: 10.1016/j.jcat.2017.12.029
43	Hansen P. L. ; Wagner J. B. ; Helveg S. ; Rostrup-Nielsen J. R. ; Clausen B. S. ; Topsoe H. Science 2002, 295, 2053. doi: 10.1126/science.1069325
44	Behrens M. ; Studt F. ; Kasatkin I. ; Kuehl S. ; Haevecker M. ; Abild-Pedersen F. ; Zander S. ; Girgsdies F. ; Kurr P. ; Kniep B.-L. ; et al Science 2012, 336, 893. doi: 10.1126/science.1219831
45	Zhan H. ; Li F. ; Gao P. ; Zhao N. ; Xiao F. ; Wei W. ; Zhong L. ; Sun Y. J. Power Sources 2014, 251, 113. doi: 10.1016/j.jpowsour.2013.11.037
46	Natesakhawat S. ; Ohodnicki P. R. ; Howard B. H. ; Lekse J. W. ; Baltrus J. P. ; Matranga C. Top. Catal. 2013, 56, 1752. doi: 10.1007/s11244-013-0111-5

Sample	H₂ Consumption ^a	Cu dispersion ^b	S_Cu ^b	d_Cu ^b	d_CuO ^c	d_CuO ^d
Sample	(mmol·g^-1)	(%)	(m²·g^-1)	(nm)	(nm)	(nm)
Nor-CZS	1.46	12.2	82.9	8.5	7.8	9.6
Co-CZS	1.57	16.1	109.1	6.5	9.1	10.1
Re-CZS	1.64	18.5	125.3	5.6	n.d.	8.2

Sample	Cu 2p_3/2 Peak 1		Cu 2p_3/2 Peak 2
Sample	Position/eV	Relative intensity/%	Position/eV	Relative intensity/%
Nor-CZS	935.3	40	933.7	60
Co-CZS	935.1	73	933.5	27
Re-CZS	935.6	78	933.3	22

Sample	S_BET ^a/(m²·g^-1)	S_Micro ^b/(m²·g^-1)	V_total ^c/(m³·g^-1)	D_ave^d/nm
SiO₂	322.2	11.2	1.25	13.3
Nor-CZS	238.6	4.4	0.97	12.2
Co-CZS	253.5	n.d.	1.11	13.1
Re-CZS	269.9	n.d.	1.16	13.2

	Nor-CZS	Co-CZS	Re-CZS
CO₂ conversion (%)	9.8	12.1	12.4
MeOH selectivity (%)	37.0	35.0	30.1
TOF (s^-1)	8.5 × 10^-3	8.0 × 10^-3	7.1 × 10^-3
P_MeOH (mmol·min^-1·g^-1)	23.3 × 10^-3	27.2 × 10^-3	23.9 × 10^-3

Sample	Relative content (%)			Number of basic sites (μmol·g^-1)
Sample	Peak 1	Peak 2	Peak 3	Peak 1	Peak 2	Peak 3
Re-CZS-0	15.84	70.84	13.71	27.09	121.14	23.44
Re-CZS-8	14.57	58.68	26.75	28.12	113.25	51.63
Re-CZS-40	13.51	50.02	36.47	22.70	84.03	61.27

探究Cu/ZnO相互作用对CO₂加氢制甲醇反应性能的影响

Understanding the Role of Cu/ZnO Interaction in CO₂ Hydrogenation to Methanol

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