Literature DB >> 23869401

Designed CVD growth of graphene via process engineering.

Kai Yan, Lei Fu, Hailin Peng, Zhongfan Liu.   

Abstract

Graphene, the atomic thin carbon film with honeycomb lattice, holds great promise in a wide range of applications, due to its unique band structure and excellent electronic, optical, mechanical, and thermal properties. Scientists are researching this star material because of the development of various emerging preparation techniques, among which chemical vapor deposition (CVD) has received the fastest advances in the past few years. For the CVD growth of graphene, the ultimate goal is to achieve the highest quality in the largest scale and lowest cost with a precise control of layer thickness, stacking order, and crystallinity. To meet this goal, researchers need a comprehensive understanding and effective controlling of the growth process, especially to its elementary steps. In this Account, we focus on our recent progresses toward the controlled surface growth of graphene and its two-dimensional (2D) hybrids via rational designs of CVD elementary processes, namely, process engineering. A typical CVD process consists of four main elementary steps: (A) adsorption and catalytic decomposition of precursor gas, (B) diffusion and dissolution of decomposed carbon species into bulk metal, (C) segregation of dissolved carbon atoms onto the metal surface, and finally, (D) surface nucleation and growth of graphene. Absence or enhancement of each elementary step would lead to significant changes in the whole growth process. Metals with certain carbon solubility, such as nickel and cobalt, involve all four elementary steps in a typical CVD process, thus providing us an ideal system for process engineering. The elementary segregation process can be completely blocked if molybdenum is introduced into the system as an alloy catalyst, yielding perfect monolayer graphene almost independent of growth parameters. On the other hand, the segregation-only process of predissolved solid carbons is also capable of high-quality graphene growth. By using a synergetic Cu-Ni alloy, we are able to further enhance the control to such a segregation technique, especially for the thickness of graphene. By designing a cosegregation process of carbon atoms with other elements, such as nitrogen, doped graphene could be synthesized directly with a tunable doping profile. Copper with negligible carbon solubility provides another platform for process engineering, where both carbon dissolution and segregation steps are negligible in the CVD process. Carbon atoms decomposed from precursors diffuse on the surface and build up the thermodynamically stable honeycomb lattice. As a result, graphene growth on copper is self-limited, and formation of multilayer graphene is generally prohibited. Being able to control this process better, as well as the high quality produced, makes copper-based growth the dominating synthesis procedure in the graphene community. We designed a two-temperature zone system to spatially separate the catalytic decomposition step of carbon precursors and the surface graphitization step for breaking this self-limited growth feature, giving high-quality Bernal stacked bilayer graphene via van der Waals epitaxy. We performed the so-called wrinkle engineering by growing graphene on nanostructured copper foil together with a structure-preserved surface transfer. In such a way, we controlled the wrinkling or folding on graphene and further fabricated graphene nanoribbon arrays by self-masked plasma etching. Moreover, by designing a two-step patching growth process on copper, we succeeded in synthesizing the mosaic graphene, a patchwork of intrinsic and nitrogen-doped graphene connected by single crystalline graphene p-n junctions. By following a general concept of process engineering, our work on the designed CVD growth of graphene and its 2D hybrids provides a unique insight of this research field. It enables the precise growth control of graphene together with the in-depth understanding of CVD growth process, which would further stimulate the pace of graphene applications.

Entities:  

Year:  2013        PMID: 23869401     DOI: 10.1021/ar400057n

Source DB:  PubMed          Journal:  Acc Chem Res        ISSN: 0001-4842            Impact factor:   22.384


  13 in total

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4.  Computational study of graphene growth on copper by first-principles and kinetic Monte Carlo calculations.

Authors:  Simone Taioli
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5.  Rapid epitaxy-free graphene synthesis on silicidated polycrystalline platinum.

Authors:  Vitaliy Babenko; Adrian T Murdock; Antal A Koós; Jude Britton; Alison Crossley; Philip Holdway; Jonathan Moffat; Jian Huang; Jack A Alexander-Webber; Robin J Nicholas; Nicole Grobert
Journal:  Nat Commun       Date:  2015-07-15       Impact factor: 14.919

6.  Graphene-assisted multiple-input high-base optical computing.

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Journal:  Sci Rep       Date:  2016-09-08       Impact factor: 4.379

7.  Growing three-dimensional biomorphic graphene powders using naturally abundant diatomite templates towards high solution processability.

Authors:  Ke Chen; Cong Li; Liurong Shi; Teng Gao; Xiuju Song; Alicja Bachmatiuk; Zhiyu Zou; Bing Deng; Qingqing Ji; Donglin Ma; Hailin Peng; Zuliang Du; Mark Hermann Rümmeli; Yanfeng Zhang; Zhongfan Liu
Journal:  Nat Commun       Date:  2016-11-07       Impact factor: 14.919

8.  In situ catalytic growth of large-area multilayered graphene/MoS2 heterostructures.

Authors:  Wei Fu; Fei-Hu Du; Juan Su; Xin-Hao Li; Xiao Wei; Tian-Nan Ye; Kai-Xue Wang; Jie-Sheng Chen
Journal:  Sci Rep       Date:  2014-04-14       Impact factor: 4.379

9.  Phase Conjugated and Transparent Wavelength Conversions of Nyquist 16-QAM Signals Employing a Single-Layer Graphene Coated Fiber Device.

Authors:  Xiao Hu; Mengqi Zeng; Yun Long; Jun Liu; Yixiao Zhu; Kaiheng Zou; Fan Zhang; Lei Fu; Jian Wang
Journal:  Sci Rep       Date:  2016-03-02       Impact factor: 4.379

10.  One-Minute Room-Temperature Transfer-Free Production of Mono- and Few-Layer Polycrystalline Graphene on Various Substrates.

Authors:  Shenglin Jiang; Yike Zeng; Wenli Zhou; Xiangshui Miao; Yan Yu
Journal:  Sci Rep       Date:  2016-01-14       Impact factor: 4.379

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