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Direct Large-Area Growth of Graphene on Silicon for Potential Ultra-Low-Friction Applications and Silicon-Based Technologies

Tseng, Wei-Shiuan and Chen, Yen-Chun and Hsu, Chen-Chih and Lu, Chen-Hsuan and Wu, Chih-I and Yeh, Nai-Chang (2020) Direct Large-Area Growth of Graphene on Silicon for Potential Ultra-Low-Friction Applications and Silicon-Based Technologies. Nanotechnology, 31 (33). Art. No. 335602. ISSN 0957-4484. https://resolver.caltech.edu/CaltechAUTHORS:20200506-092128313

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Abstract

Deposition of layers of graphene on silicon has the potential for a wide range of optoelectronic and mechanical applications. However, direct growth of graphene on silicon has been difficult due to the inert, oxidized silicon surfaces. Transferring graphene from metallic growth substrates to silicon is not a good solution either, because most transfer methods involve multiple steps that often lead to polymer residues or degradation of sample quality. Here we report a single-step method for large-area direct growth of continuous horizontal graphene sheets and vertical graphene nano-walls on silicon substrates by plasma-enhanced chemical vapor deposition (PECVD) without active heating. Comprehensive studies utilizing Raman spectroscopy, x-ray/ultraviolet photoelectron spectroscopy (XPS/UPS), atomic force microscopy (AFM), scanning electron microscopy (SEM) and optical transmission are carried out to characterize the quality and properties of these samples. Data gathered by the residual gas analyzer (RGA) during the growth process further provide information about the synthesis mechanism. Additionally, ultra-low friction (with a frictional coefficient ~0.015) on multilayer graphene-covered silicon surface is achieved, which is approaching the superlubricity limit (for frictional coefficients <0.01). Our growth method therefore opens up a new pathway towards scalable and direct integration of graphene into silicon technology for potential applications ranging from structural superlubricity to nanoelectronics, optoelectronics, and even the next-generation lithium-ion batteries.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1088/1361-6528/ab9045DOIArticle
ORCID:
AuthorORCID
Wu, Chih-I0000-0002-0404-6781
Yeh, Nai-Chang0000-0002-1826-419X
Additional Information:© 2020 IOP Publishing Ltd. Received 14 February 2020; Accepted 5 May 2020; Accepted Manuscript online 5 May 2020; Published 4 June 2020. This work at Caltech was jointly supported by the National Science Foundation under the Institute for Quantum Information and Matter (IQIM), Award #1733907, and the Army Research Office under the Multi-University Research Initiative (MURI) program, Award #W911NF-16-1-0472. W -S T and C -I Wu gratefully acknowledge the support from the Dragon-Gate Program (MoST 107-2911-I-002-576) under the Ministry of Science and Technology (MoST) in Taiwan for supporting their visit to Caltech and the collaborative research. Y -C C acknowledges the support from the Dragon-Gate Program (MoST 106-2911-I-007-520) under MoST in Taiwan for supporting his visit to Caltech. The authors thank Professor George Rossman for the use of his Raman spectrometer, and acknowledge the use of the XPS/UPS, AFM facilities at the Beckman Institute and the use of the SEM system at the Kavli Nanoscience Institute. We also thank Professor Quanshui Zheng at Tsinghua University in China for helpful discussions on topics of structural superlubricity and for providing the DLC substrates.
Group:Institute for Quantum Information and Matter, Kavli Nanoscience Institute
Funders:
Funding AgencyGrant Number
NSFPHY-1733907
Army Research Office (ARO)W911NF-16-1-0472
Ministry of Science and Technology (Taipei)107-2911-I-002-576
Ministry of Science and Technology (Taipei)106-2911-I-007-520
Subject Keywords:graphene-on-silicon, PECVD, AFM, superlubricity, XPS/UPS, RGA
Issue or Number:33
Record Number:CaltechAUTHORS:20200506-092128313
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200506-092128313
Official Citation:Wei-Shiuan Tseng et al 2020 Nanotechnology 31 335602
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103023
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:06 May 2020 16:43
Last Modified:08 Jun 2020 22:34

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