journal article·2023-10-02

A Bilayered Carbon with High Sunlight-Absorption Coefficient Designed by Flat-Band-Guided Strategy

Rui Xu, Hang Zhai, Di Wang, Xianqi Song, Dan Zhou, Quan Li

ACS Materials Letters· Volume 5· Issue 10
Publisher page

Abstract

The electronic band structure of a material determines its photovoltaic performance. In this work, we developed a methodology to explore desired semiconducting materials with a specialized designed fitness function for characterizing flat electronic bands via the generalization of our in-house-developed CALYPSO method. An intriguing bilayered carbon with sp 3 - and sp 2 - hybridized bonds, related to a bilayered reconstruction of (111) diamond or twisted graphene, was proposed and termed as two-dimensional diaphite. Two-dimensional diaphite has a direct electronic bandgap of 1.20 eV, with a high density of states near the band edges caused by the nearby flat bands, affording an extremely high sunlight-absorption coefficient. The type-II van der Waals heterojunctions composed of 2D diaphite and InSe monolayers yielded extraordinary performance for solar-to-electricity conversion with a theoretical power conversion efficiency of up to a record-breaking value of 24.1%, making it a potential candidate for high-efficiency and ultrathin photovoltaic devices. Our results show that the approach proposed herein is a feasible way of searching for functional semiconducting materials with specialized characteristic energy-band structures.
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Research context

OpenAlex topics: 2D Materials and Applications · Graphene research and applications · MXene and MAX Phase Materials

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

Affiliations

Key Laboratory of Material Simulation Methods & Software of Ministry of Education and State Key Lab of Superhard Materials, College of Physics, Jilin University, Changchun 130012, China

Jilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy Materials, Jilin University, Changchun 130012, China

International Center of Future Science, Jilin University, Changchun 130012, China

School of Physics, Changchun University of Science and Technology, Changchun 130022, China

Funding

National Key Research and Development Program of China · Program for Jilin University Science and Technology Innovative Research Team · National Natural Science Foundation of China

References (62)

Show source-provided references
1. 10.1038/s41586-022-04604-510.1038/s41586-022-04604-5 ↗
2. 10.1038/s41586-021-03957-710.1038/s41586-021-03957-7 ↗
3. 10.1126/science.aax329410.1126/science.aax3294 ↗
4. 10.1038/s41563-021-01097-x10.1038/s41563-021-01097-x ↗
5. 10.1038/s41560-020-0598-510.1038/s41560-020-0598-5 ↗
6. 10.1021/jacs.1c0751810.1021/jacs.1c07518 ↗
7. 10.1021/acsmaterialslett.1c0068410.1021/acsmaterialslett.1c00684 ↗
8. 10.1021/acsmaterialslett.3c0030010.1021/acsmaterialslett.3c00300 ↗
9. 10.1021/acsmaterialslett.2c0100110.1021/acsmaterialslett.2c01001 ↗
10. 10.1063/1.173603410.1063/1.1736034 ↗
11. 10.1103/PhysRevLett.108.06870110.1103/PhysRevLett.108.068701 ↗
12. 10.1016/j.solmat.2011.12.01610.1016/j.solmat.2011.12.016 ↗
13. 10.1103/PhysRevLett.55.141810.1103/PhysRevLett.55.1418 ↗
14. 10.1021/acsmaterialslett.2c0025410.1021/acsmaterialslett.2c00254 ↗
15. 10.1016/j.mtphys.2023.10114410.1016/j.mtphys.2023.101144 ↗
16. 10.1021/jacs.1c0303910.1021/jacs.1c03039 ↗
17. 10.1021/jacs.9b1161410.1021/jacs.9b11614 ↗
18. 10.1038/nphoton.2014.27110.1038/nphoton.2014.271 ↗
19. 10.1021/jacs.0c0701310.1021/jacs.0c07013 ↗
20. 10.1021/jacs.2c0753510.1021/jacs.2c07535 ↗
21. 10.1021/jacs.1c0368710.1021/jacs.1c03687 ↗
22. 10.1021/jacs.1c0267510.1021/jacs.1c02675 ↗
23. 10.1021/acsmaterialslett.3c0002710.1021/acsmaterialslett.3c00027 ↗
24. 10.1021/acsmaterialslett.1c0032710.1021/acsmaterialslett.1c00327 ↗
25. 10.1021/acsami.8b0945410.1021/acsami.8b09454 ↗
26. 10.1016/j.mseb.2005.02.04610.1016/j.mseb.2005.02.046 ↗
27. 10.1063/1.346080910.1063/1.3460809 ↗
28. 10.1038/nmat288510.1038/nmat2885 ↗
29. 10.1038/ncomms466610.1038/ncomms4666 ↗
30. 10.1103/PhysRevB.99.04140510.1103/PhysRevB.99.041405 ↗
31. 10.1103/PhysRevB.100.11542510.1103/PhysRevB.100.115425 ↗
32. 10.1038/s41524-020-0300-210.1038/s41524-020-0300-2 ↗
33. 10.1021/ja503579210.1021/ja5035792 ↗
34. 10.1038/s41578-019-0101-810.1038/s41578-019-0101-8 ↗
35. 10.1021/acs.jpclett.6b0024810.1021/acs.jpclett.6b00248 ↗
36. 10.1039/C7TA02109G10.1039/C7TA02109G ↗
37. Kennedy, J.; Eberhart, R. Particle Swarm Optimization. InProceedings of International Conference on Neural Networks (ICNN’95), Perth, Australia, 1995; IEEE, 1995; pp 1942–1948.10.1109/ICNN.1995.488968 ↗
38. 10.1016/j.cpc.2012.05.00810.1016/j.cpc.2012.05.008 ↗
39. 10.1016/j.scib.2019.02.00910.1016/j.scib.2019.02.009 ↗
40. 10.1103/PhysRevLett.77.386510.1103/PhysRevLett.77.3865 ↗
41. 10.1103/PhysRevB.54.1116910.1103/PhysRevB.54.11169 ↗
42. 10.1103/PhysRevA.38.309810.1103/PhysRevA.38.3098 ↗
43. 10.1103/RevModPhys.74.60110.1103/RevModPhys.74.601 ↗
44. 10.1103/PhysRevB.62.492710.1103/PhysRevB.62.4927 ↗
45. 10.1016/j.scriptamat.2015.07.02110.1016/j.scriptamat.2015.07.021 ↗
46. 10.1126/science.110289610.1126/science.1102896 ↗
47. 10.1103/PhysRevB.58.1100910.1103/PhysRevB.58.11009 ↗
48. 10.1021/acs.jpcc.8b1220510.1021/acs.jpcc.8b12205 ↗
49. 10.1016/j.carbon.2017.03.06710.1016/j.carbon.2017.03.067 ↗
50. 10.1039/C4CP02161D10.1039/C4CP02161D ↗
51. 10.1016/j.carbon.2018.11.06210.1016/j.carbon.2018.11.062 ↗
52. 10.1016/j.commatsci.2019.05.02410.1016/j.commatsci.2019.05.024 ↗
53. 10.1038/s41524-019-0211-210.1038/s41524-019-0211-2 ↗
54. 10.1063/1.33111310.1063/1.331113 ↗
55. 10.1063/1.503432010.1063/1.5034320 ↗
56. 10.1039/C9TA00280D10.1039/C9TA00280D ↗
57. 10.1103/PhysRev.127.76810.1103/PhysRev.127.768 ↗
58. 10.1016/j.nanoen.2018.06.07910.1016/j.nanoen.2018.06.079 ↗
59. 10.1002/adma.20050171710.1002/adma.200501717 ↗
60. 10.1021/acs.jpcc.5b0295010.1021/acs.jpcc.5b02950 ↗
61. 10.1021/cm401661x10.1021/cm401661x ↗
62. 10.1021/jp405808a10.1021/jp405808a ↗