Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Quality Assessment of Graphene for Biosensors Application

Version 1 : Received: 27 May 2023 / Approved: 30 May 2023 / Online: 30 May 2023 (03:57:20 CEST)

A peer-reviewed article of this Preprint also exists.

Shmidt, N.M.; Shabunina, E.I.; Gushchina, E.V.; Petrov, V.N.; Eliseyev, I.A.; Lebedev, S.P.; Priobrazhenskii, S.I.; Tanklevskaya, E.M.; Puzyk, M.V.; Roenkov, A.D.; Usikov, A.S.; Lebedev, A.A. Quality Assessment of Processed Graphene Chips for Biosensor Application. Materials 2023, 16, 5628. Shmidt, N.M.; Shabunina, E.I.; Gushchina, E.V.; Petrov, V.N.; Eliseyev, I.A.; Lebedev, S.P.; Priobrazhenskii, S.I.; Tanklevskaya, E.M.; Puzyk, M.V.; Roenkov, A.D.; Usikov, A.S.; Lebedev, A.A. Quality Assessment of Processed Graphene Chips for Biosensor Application. Materials 2023, 16, 5628.

Abstract

Graphene quality for use in biosensors was assessed in fabricated chips by a set of methods that includes atomic force microscopy (AFM), Raman spectroscopy, and low-frequency noise. It is shown that local areas of residues on the graphene surface, which arisen due to the interaction of graphene with a photoresist at the initial stage of chips development, leads to a spread of chips resistance (R) within 1-10 kΩ and to an increase in the root mean square (RMS) roughness up to 10 times that can significantly impair reproducibility of graphene parameters in biosensors chips. It was observed that the control of the photoresist residues after photolithography (PLG) by AFM and subsequent additional cleaning allow reducing the spread of R values in chips to 1–1.6 kΩ and obtaining RMS roughness similar to the roughness in pristine graphene before PLG. Monitoring of the spectral density of low-frequency voltage fluctuation (SU), which provides integral information about the defect system and quality of the material, makes it possible to identify chips with low graphene quality and with inhomogeneously distributed compressive stresses areas by the type of frequency dependence SU (f).

Keywords

graphene chip; surface topography; photoresist residues; low-frequency noise

Subject

Biology and Life Sciences, Biophysics

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