NLL-Assisted Multilayer Graphene Patterning

Date

2018-02-01

Author

Kovalska, Evgeniya
Pavlov, Ihor
Deminskyi, Petro
Baldycheva, Anna
Ilday, F. Omer
Kocabas, Coskun

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The range of applications of diverse graphene-based devices could be limited by insufficient surface reactivity, unsatisfied shaping, or null energy gap of graphene. Engineering the graphene structure by laser techniques can adjust the transport properties and the surface area of graphene, providing devices of different nature with a higher capacitance. Additionally, the created periodic potential and appearance of the active external/inner/edge surface centers determine the multifunctionality of the graphene surface and corresponding devices. Here, we report on the first implementation of nonlinear laser lithography (NLL) for multilayer graphene (MLG) structuring, which offers a low-cost, single-step, and high-speed nanofabrication process. The NLL relies on the employment of a high repetition rate femtosecond Yb fiber laser that provides generation of highly reproducible, robust, uniform, and periodic nanostructures over a large surface area (1 cm(2)/15 s). NLL allows one to obtain clearly predesigned patterned graphene structures without fabrication tolerances, which are caused by contacting mask contamination, polymer residuals, and direct laser exposure of the graphene layers. We represent regularly patterned MLG (p-MLG) obtained by the chemical vapor deposition method on an NLL-structured Ni foil. We also demonstrate tuning of chemical (wettability) and electro-optical (transmittance and sheet resistance) properties of p-MLG by laser power adjustments. In conclusion, we show the great promise of fabricated devices, namely, supercapacitors, and Li-ion batteries by using NLL-assisted graphene patterning. Our approach demonstrates a new avenue to pattern graphene for multifunctional device engineering in optics, photonics, and bioelectronics.

Subject Keywords

Two dimensional materials, Optical properties, Power, Batteries, Lasers

URI

https://hdl.handle.net/11511/52583

Journal

ACS OMEGA

DOI

https://doi.org/10.1021/acsomega.7b01853

Collections

Department of Physics, Article

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Citation Formats

E. Kovalska, I. Pavlov, P. Deminskyi, A. Baldycheva, F. O. Ilday, and C. Kocabas, “NLL-Assisted Multilayer Graphene Patterning,” ACS OMEGA, pp. 1546–1554, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52583.