Surface-treatment process related sheet resistance variations in graphene-based thin-film electrodes
Graphene-based ultra-thin films have good potential to be used as electrodes in many microelectronic, optoelectronic, energy storage, and sensing applications. Low sheet resistance (RS) of graphene-based thin-film electrodes (TFEs) is one of the key requirements for realizing efficient functional de...
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| 主要な著者: | , , , , , , , |
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| フォーマット: | 論文 |
| 出版事項: |
Elsevier B.V.
2022
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| オンライン･アクセス: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133923825&doi=10.1016%2fj.surfin.2022.102161&partnerID=40&md5=756a2abb63ec9b2113c8dfe8adf7f017 http://eprints.utp.edu.my/33556/ |
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| 要約: | Graphene-based ultra-thin films have good potential to be used as electrodes in many microelectronic, optoelectronic, energy storage, and sensing applications. Low sheet resistance (RS) of graphene-based thin-film electrodes (TFEs) is one of the key requirements for realizing efficient functional devices. RS of graphene is unfortunately affected by some surface treatment processes such as annealing and patterning. In this work, we have investigated comprehensively the effect of aforementioned processes on RS of chemical vapor deposition-grown atomically-thin pristine graphene and its hybrid TFEs. Thermal treatment processes such as rapid thermal annealing and vacuum annealing are examined in order to enhance the interface adhesion of graphene-based TFEs. Whereas, patterning modes such as optical lithography (OL) and laser ablation are studied to improve the patterning accuracy. Variations in RS of TFEs are analyzed before and after the processes. We find that RS of TFEs is improved by 25-30 along with better interface adhesion after thermal treatments, attributing to the improvement in physical/chemical bonding and elimination of surface residues. In patterning part, CO2 laser negligibly affects the RS of TFEs whereas a 2.5-fold rise in RS is found after OL patterning. We believe that these results could be useful in producing reliable graphene-based devices. © 2022 |
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