Literature DB >> 27580305

Large-Scale Graphene on Hexagonal-BN Hall Elements: Prediction of Sensor Performance without Magnetic Field.

Min-Kyu Joo1,2, Joonggyu Kim2, Ji-Hoon Park1, Van Luan Nguyen1, Ki Kang Kim3, Young Hee Lee1,2, Dongseok Suh2.   

Abstract

A graphene Hall element (GHE) is an optimal system for a magnetic sensor because of its perfect two-dimensional (2-D) structure, high carrier mobility, and widely tunable carrier concentration. Even though several proof-of-concept devices have been proposed, manufacturing them by mechanical exfoliation of 2-D material or electron-beam lithography is of limited feasibility. Here, we demonstrate a high quality GHE array having a graphene on hexagonal-BN (h-BN) heterostructure, fabricated by photolithography and large-area 2-D materials grown by chemical vapor deposition techniques. A superior performance of GHE was achieved with the help of a bottom h-BN layer, and showed a maximum current-normalized sensitivity of 1986 V/AT, a minimum magnetic resolution of 0.5 mG/Hz(0.5) at f = 300 Hz, and an effective dynamic range larger than 74 dB. Furthermore, on the basis of a thorough understanding of the shift of charge neutrality point depending on various parameters, an analytical model that predicts the magnetic sensor operation of a GHE from its transconductance data without magnetic field is proposed, simplifying the evaluation of each GHE design. These results demonstrate the feasibility of this highly performing graphene device using large-scale manufacturing-friendly fabrication methods.

Entities:  

Keywords:  chemical vapor deposition; graphene; graphene Hall element; hexagonal boron nitride; large-area graphene device; magnetic field sensor

Year:  2016        PMID: 27580305     DOI: 10.1021/acsnano.6b04547

Source DB:  PubMed          Journal:  ACS Nano        ISSN: 1936-0851            Impact factor:   15.881


  1 in total

1.  Hall sensors batch-fabricated on all-CVD h-BN/graphene/h-BN heterostructures.

Authors:  André Dankert; Bogdan Karpiak; Saroj P Dash
Journal:  Sci Rep       Date:  2017-11-09       Impact factor: 4.379

  1 in total

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