journal article·2022-12-23

Ab Initio Study of Metal Oxo-Trimer Nanoporous MOF Building Units for the Catalytic Conversion of CO2 to Methanol

Pengbo Lyu, Guillaume Maurin

ACS Applied Nano Materials· Volume 5· Issue 12
Publisher page

Abstract

Seeking catalysts with low overpotential is crucial to achieve efficient (photo)electrochemical CO2 reduction. Metal–organic frameworks (MOFs) with coordinatively unsaturated sites (CUSs) are promising candidates for this purpose. Density functional theory calculations explored the reaction mechanisms and activities for a series of metal oxo-trimer nodes within MOFs for catalytic CO2 reduction to methanol. We first demonstrate that all investigated systems fulfill the thermodynamic requirement for CO2 reduction regardless of the pH value. Then, we investigate the minimum energy pathway for CO2 reduction over a Fe-only system with experimentally proved activity as a benchmark. In comparison with Fe (II), Co(II) and Ni(II) lead to equivalent or even better catalytic activity with Ni(II) the most active metal, whereas Cu(I), Zn(II), Cd(II), Ti(III), Y(III) and Ce(III) show poor performance. Finally, we found that the stability of the intermediate species *COOH is a reliable descriptor to rank the catalytic activity of these oxo-trimers, and the origin is analyzed. Our computational efforts not only deliver a fundamental understanding of CO2 reduction process over CUSs in MOFs but also provide theoretical guidance for rational design of highly active catalysts for (photo)electrochemical CO2 reduction based on MOFs containing metal oxo-trimer nodes.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Metal-Organic Frameworks: Synthesis and Applications · Advanced Photocatalysis Techniques · CO2 Reduction Techniques and Catalysts

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Hunan Provincial Key Laboratory of Thin Film Materials and Devices, School of Materials Science and Engineering, Xiangtan University, Xiangtan 411105, China

ICGM, Université Montpellier, CNRS, ENSCM, Montpellier 34293, France

Funding

Hunan Province

References (71)

Show source-provided references
1. 10.1007/s11356-019-07158-810.1007/s11356-019-07158-8 ↗
2. 10.1021/jacs.0c0235610.1021/jacs.0c02356 ↗
3. 10.1002/cssc.20110022010.1002/cssc.201100220 ↗
4. 10.1021/jacs.9b0490710.1021/jacs.9b04907 ↗
5. 10.1021/acsenergylett.8b0087810.1021/acsenergylett.8b00878 ↗
6. 10.1002/anie.20181150610.1002/anie.201811506 ↗
7. 10.1021/acs.accounts.1c0061610.1021/acs.accounts.1c00616 ↗
8. 10.1021/acs.accounts.1c0064310.1021/acs.accounts.1c00643 ↗
9. 10.1021/jacs.9b0706710.1021/jacs.9b07067 ↗
10. 10.1016/j.jcat.2021.11.02310.1016/j.jcat.2021.11.023 ↗
11. 10.1016/j.ccr.2021.21434010.1016/j.ccr.2021.214340 ↗
12. 10.1021/acs.chemrev.8b0048110.1021/acs.chemrev.8b00481 ↗
13. 10.1002/anie.20190424610.1002/anie.201904246 ↗
14. 10.1002/solr.20170012610.1002/solr.201700126 ↗
15. 10.1039/c7cs90049j10.1039/c7cs90049j ↗
16. 10.1002/anie.20220619310.1002/anie.202206193 ↗
17. 10.1021/acscatal.2c0208810.1021/acscatal.2c02088 ↗
18. 10.1002/advs.20210336110.1002/advs.202103361 ↗
19. 10.1039/d1ta10440c10.1039/d1ta10440c ↗
20. 10.1016/j.ccr.2017.09.00110.1016/j.ccr.2017.09.001 ↗
21. 10.1002/celc.20180152010.1002/celc.201801520 ↗
22. 10.1021/acsami.1c2012810.1021/acsami.1c20128 ↗
23. 10.1039/c9cs00609e10.1039/c9cs00609e ↗
24. 10.1021/jacs.8b0640710.1021/jacs.8b06407 ↗
25. 10.1039/b807080f10.1039/b807080f ↗
26. 10.1021/acs.chemrev.9b0022310.1021/acs.chemrev.9b00223 ↗
27. 10.1021/acs.chemrev.9b0068510.1021/acs.chemrev.9b00685 ↗
28. 10.1016/j.ccr.2020.21331910.1016/j.ccr.2020.213319 ↗
29. 10.1016/j.micromeso.2019.05.04010.1016/j.micromeso.2019.05.040 ↗
30. 10.3389/fenrg.2014.0006310.3389/fenrg.2014.00063 ↗
31. 10.1021/cs501169t10.1021/cs501169t ↗
32. 10.1021/cs300587410.1021/cs3005874 ↗
33. 10.1016/j.enchem.2020.10003310.1016/j.enchem.2020.100033 ↗
34. 10.1002/anie.20045425010.1002/anie.200454250 ↗
35. 10.1002/anie.20046059210.1002/anie.200460592 ↗
36. 10.1126/science.111627510.1126/science.1116275 ↗
37. 10.1038/ncomms672310.1038/ncomms6723 ↗
38. 10.1016/j.jcat.2009.08.00110.1016/j.jcat.2009.08.001 ↗
39. 10.1021/acscatal.0c0039910.1021/acscatal.0c00399 ↗
40. 10.1021/acscatal.5b0194910.1021/acscatal.5b01949 ↗
41. 10.1039/c4ra07028c10.1039/c4ra07028c ↗
42. Vimont, A.; Cortes, P. H.; Hwang, Y. K.; Férey, G.; Daturi, M.; Chang, J.S.; Serre, C.; Yoon, J. W. Use of a porous crystalline hybrid solid as a nitrogen oxide reduction catalyst and devices. WO2010136677A1, December 2, 2010.
43. 10.1007/s10562-016-1840-410.1007/s10562-016-1840-4 ↗
44. 10.1016/j.micromeso.2010.12.01610.1016/j.micromeso.2010.12.016 ↗
45. 10.1021/cg401205810.1021/cg4012058 ↗
46. 10.1039/b512169h10.1039/b512169h ↗
47. 10.1021/cm901983a10.1021/cm901983a ↗
48. 10.1002/cplu.20160045610.1002/cplu.201600456 ↗
49. 10.1016/j.micromeso.2011.12.00110.1016/j.micromeso.2011.12.001 ↗
50. 10.1039/c2cy00376g10.1039/c2cy00376g ↗
51. 10.1039/d0nj00257g10.1039/d0nj00257g ↗
52. 10.1021/cm103644b10.1021/cm103644b ↗
53. 10.1021/ja906198y10.1021/ja906198y ↗
54. 10.1002/ejic.20120010610.1002/ejic.201200106 ↗
55. 10.1021/acscatal.0c0221910.1021/acscatal.0c02219 ↗
56. 10.1021/acsami.0c0624110.1021/acsami.0c06241 ↗
57. 10.1021/acscatal.9b0393210.1021/acscatal.9b03932 ↗
58. 10.1021/acscatal.8b0481310.1021/acscatal.8b04813 ↗
59. 10.1021/acscatal.9b0212610.1021/acscatal.9b02126 ↗
60. 10.1016/j.apcatb.2020.11917310.1016/j.apcatb.2020.119173 ↗
61. 10.1021/jp047349j10.1021/jp047349j ↗
62. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; Li, X.; Caricato, M.; Marenich, A. V.; Bloino, J.; Janesko, B. G.; Gomperts, R.; Mennucci, B.; Hratchian, H. P.; Ortiz, J. V.; Izmaylov, A. F.; Sonnenberg, J. L.; Williams; Ding, F.; Lipparini, F.; Egidi, F.; Goings, J.; Peng, B.; Petrone, A.; Henderson, T.; Ranasinghe, D.; Zakrzewski, V. G.; Gao, J.; Rega, N.; Zheng, G.; Liang, W.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Throssell, K.; Montgomery, J. A.; Peralta, J. E.; Ogliaro, F.; Bearpark, M. J.; Heyd, J. J.; Brothers, E. N.; Kudin, K. N.; Staroverov, V. N.; Keith, T. A.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A. P.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Millam, J. M.; Klene, M.; Adamo, C.; Cammi, R.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Farkas, O.; Foresman, J. B.; Fox, D. J. Gaussian 09, Reviion D.01; Gaussian, Inc.: Wallingford, CT, 2016.
63. 10.1063/1.46714610.1063/1.467146 ↗
64. 10.1063/1.44897510.1063/1.448975 ↗
65. 10.1063/1.338234410.1063/1.3382344 ↗
66. 10.1021/cs400541910.1021/cs4005419 ↗
67. 10.1021/acssuschemeng.9b0269910.1021/acssuschemeng.9b02699 ↗
68. 10.1021/acscatal.6b0208910.1021/acscatal.6b02089 ↗
69. 10.1021/cm401661x10.1021/cm401661x ↗
70. 10.1039/c9nr09529b10.1039/c9nr09529b ↗
71. 10.1002/jcc.2288510.1002/jcc.22885 ↗