journal article·2018-02-27

Controlling Fundamental Fluctuations for Reproducible Growth of Large Single-Crystal Graphene

Wei Guo, Bin Wu, Shuai Wang, Yunqi Liu

ACS Nano· Volume 12· Issue 2
Publisher page

Abstract

The controlled growth of graphene by the chemical vapor deposition method is vital for its various applications; however, the reproducibility remains a great challenge. Here, using single-crystal graphene growth on a Cu surface as a model system, we demonstrate that a trace amount of H 2 O and O 2 impurity gases in the reaction chamber is key for the large fluctuation of graphene growth. By precisely controlling their parts per million level concentrations, centimeter-sized single-crystal graphene is obtained in a reliable manner with a maximum growth rate up to 190 μm min –1 . The roles of oxidants are elucidated as an effective modulator for both graphene nucleation density and growth rate. This control is more fundamental for reliable growth of graphene beyond previous findings and is expected to be useful for the growth of various 2D materials that are also sensitive to trace oxidant impurities.
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Research context

OpenAlex topics: Graphene research and applications · Graphene and Nanomaterials Applications · ZnO doping and properties

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

Affiliations

Beijing National Laboratory for Molecular Sciences, Key Laboratory of Organic Solids, Institute of Chemistry, Chinese Academy of Science, Beijing 100190, P.R. China

Key Laboratory of Material Chemistry for Energy Conversion and Storage, Ministry of Education, School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, Wuhan 430074, P.R. China

Funding

Ministry of Science and Technology of the People's Republic of China · National Natural Science Foundation of China · Chinese Academy of Sciences · Beijing Municipal Commission of Science and Technology

References (31)

Show source-provided references
1. 10.1002/adma.20150476010.1002/adma.201504760 ↗
2. 10.1002/advs.20170008710.1002/advs.201700087 ↗
3. 10.1038/nnano.2010.13210.1038/nnano.2010.132 ↗
4. 10.1021/ar400304310.1021/ar4003043 ↗
5. 10.1002/adma.20140454110.1002/adma.201404541 ↗
6. 10.1021/nl502445j10.1021/nl502445j ↗
7. 10.1126/science.125226810.1126/science.1252268 ↗
8. 10.1002/adma.20160176010.1002/adma.201601760 ↗
9. 10.1002/adma.20160357910.1002/adma.201603579 ↗
10. Xu X. · Science Bulletin · 2017 · 62 · 107410.1016/j.scib.2017.07.005 ↗
11. 10.1038/nmat447710.1038/nmat4477 ↗
12. 10.1126/science.124387910.1126/science.1243879 ↗
13. 10.1021/acsnano.6b0004110.1021/acsnano.6b00041 ↗
14. 10.1002/adma.20150370510.1002/adma.201503705 ↗
15. 10.1002/adma.20160040310.1002/adma.201600403 ↗
16. 10.1073/pnas.131280211010.1073/pnas.1312802110 ↗
17. 10.1002/adma.20150147310.1002/adma.201501473 ↗
18. 10.1016/j.jcat.2011.05.02710.1016/j.jcat.2011.05.027 ↗
19. 10.1038/nnano.2015.32210.1038/nnano.2015.322 ↗
20. 10.1038/nnano.2016.13210.1038/nnano.2016.132 ↗
21. 10.1038/nmat476010.1038/nmat4760 ↗
22. 10.1021/jacs.6b0533310.1021/jacs.6b05333 ↗
23. 10.1016/j.jcat.2006.07.03410.1016/j.jcat.2006.07.034 ↗
24. 10.1021/jz101150w10.1021/jz101150w ↗
25. 10.1016/j.susc.2010.05.02610.1016/j.susc.2010.05.026 ↗
26. 10.1038/srep0248410.1038/srep02484 ↗
27. 10.1038/nchem.68610.1038/nchem.686 ↗
28. 10.1021/jz400400u10.1021/jz400400u ↗
29. 10.1021/jp507021510.1021/jp5070215 ↗
30. 10.1021/ja402224h10.1021/ja402224h ↗
31. 10.1021/acsnano.5b0182710.1021/acsnano.5b01827 ↗