NLL-Assisted Multilayer Graphene Patterning

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buir.contributor.authorİlday, Fatih Ömer
dc.citation.epage1554en_US
dc.citation.issueNumber2en_US
dc.citation.spage1546en_US
dc.citation.volumeNumber3en_US
dc.contributor.authorKovalska, E.en_US
dc.contributor.authorPavlov, I.en_US
dc.contributor.authorDeminskyi, P.en_US
dc.contributor.authorBaldycheva, A.en_US
dc.contributor.authorİlday, Fatih Ömeren_US
dc.contributor.authorKocabas, C.en_US
dc.date.accessioned2019-02-21T16:02:24Z
dc.date.available2019-02-21T16:02:24Z
dc.date.issued2018en_US
dc.departmentDepartment of Physicsen_US
dc.description.abstractThe 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 cm2/15 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.
dc.description.provenanceMade available in DSpace on 2019-02-21T16:02:24Z (GMT). No. of bitstreams: 1 Bilkent-research-paper.pdf: 222869 bytes, checksum: 842af2b9bd649e7f548593affdbafbb3 (MD5) Previous issue date: 2018en
dc.description.sponsorshipThis research was partially supported by the European Research Council (ERC) Consolidator grants ERC-682723 SmartGraphene and ERC-617521 NLL; the European Union funding: Marie Curie Fellowship visiting grant; and the Engineering and Physical Sciences Research Council (EPSRC) of the United Kingdom via grant no. EP/ N035569/1. We thank our colleagues Dr. Nurbek Kakenov, Dr. Osman Balci, and Dr. Nassima Afshar Imani from Bilkent University who provided insight and expertise that greatly assisted the research. We thank Dr. Omer Salihoglu (TUBITAK, Marmara Research Center) for the assistance with capacity and life-cycle battery measurements, and Murat Güre and Ergun Karaman (physicists and engineers of Bilkent University) for catalyst preparation and technical support. E.K. would also like to show her gratitude to all co-authors for sharing their pearls of wisdom and comments during the preparation of manuscript that greatly improved its quality.
dc.identifier.doi10.1021/acsomega.7b01853
dc.identifier.issn2470-1343
dc.identifier.urihttp://hdl.handle.net/11693/50000
dc.language.isoEnglish
dc.publisherAmerican Chemical Society
dc.relation.isversionofhttps://doi.org/10.1021/acsomega.7b01853
dc.relation.projectBilkent Üniversitesi - European Research Council, ERC: ERC-617521 - European Research Council, ERC: ERC-682723 SmartGraphene - Engineering and Physical Sciences Research Council, EPSRC: EP/ N035569/1 - Engineering and Physical Sciences Research Council, EPSRC
dc.rightsinfo:eu-repo/semantics/openAccess
dc.source.titleACS Omegaen_US
dc.titleNLL-Assisted Multilayer Graphene Patterningen_US
dc.typeArticleen_US

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