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Cited by 820

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Toward Clean and Crackless Transfer of Graphene

Liang, Xuelei, Sperling, Brent A., Calizo, Irene, Cheng, Guangjun, Hacker, Christina Ann, Zhang, Qin, Obeng, Yaw, Yan, Kai, Peng, Hailin, Li, Qiliang, Zhu, Xiaoxiao, Yuan, Hui, Hight Walker, Angela R., Liu, Zhongfan, Peng, Lian-mao, Richter, Curt A.·2011·ACS Nano

Abstract

We present the results of a thorough study of wet chemical methods for transferring chemical vapor deposition grown graphene from the metal growth substrate to a device-compatible substrate. On the basis of these results, we have developed a "modified RCA clean" transfer method that has much better control of both contamination and crack formation and does not degrade the quality of the transferred graphene. Using this transfer method, high device yields, up to 97%, with a narrow device performance metrics distribution were achieved. This demonstration addresses an important step toward large-scale graphene-based electronic device applications.

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Metadata

Authors
Liang, X., Sperling, B. A., Calizo, I., Cheng, G., Hacker, C. A., Zhang, Q., Obeng, Y., Yan, K., Peng, H., Li, Q., Zhu, X., Yuan, H., Hight Walker, A. R., Liu, Z., Peng, L.-M., & Richter, C. A.
Venue
ACS Nano
Published
2011-10-19
Volume
5
Issue
11
Pages
9144-9153
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W1967897514
Cited by
820
References
2
FWCI
20.45
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Toward Clean and Crackless Transfer of Graphene. https://app.cochat.ai/papers/10.1021/nn203377t
The paper
Liang, X., Sperling, B. A., Calizo, I., Cheng, G., Hacker, C. A., Zhang, Q., Obeng, Y., Yan, K., Peng, H., Li, Q., Zhu, X., Yuan, H., Hight Walker, A. R., Liu, Z., Peng, L.-M., & Richter, C. A. (2011). Toward Clean and Crackless Transfer of Graphene. ACS Nano. https://doi.org/10.1021/nn203377t

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.