Tight-binding description of graphene–BCN–graphene layered semiconductors

Ebrahimi, Mahsa; Horri, Ashkan; Sanaeepur, Majid; Tavakoli, Mohammad Bagher

doi:10.1007/s10825-019-01442-z

Cited by 8 publications

(11 citation statements)

References 32 publications

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“…A bias voltage ( V DS ) of 0.6 V is applied between the drain and source contacts. For a fair comparison with previous studies, − a 1 nm layer of silicon dioxide is considered as a gate oxide. A thicker SiO 2 layer reduces the control of the gate over the channel and decreases the switching ratio.…”

Section: Resultsmentioning

confidence: 99%

“…In this presented paper, by using lattice-matched BC 2 N instead of graphene as the source and drain regions, and using BN as a tunneling barrier, a lower barrier height is constructed that enhances the switching ratio and subthreshold swing. Besides lateral heterostructure devices, vertical tunneling transistors based on graphene-BCN heterostructures have been proposed. , Although it is easier to fabricate vertical heterostructures than lateral ones, it has some specific disadvantages. Indeed, in the vertical heterostructures, the overlap between gate and source (or drain) regions screens the field induced by the gate.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, in the vertical heterostructures, the overlap between gate and source (or drain) regions screens the field induced by the gate. This screening strongly degrades the I ON / I OFF ratio and subthreshold swing. , In the lateral heterostructures, screening of the gate happens in a small region where the gate overlaps with the source (or drain) region, which is an intrinsic advantage. In this paper, for the first time, we suggest a double gate tunneling FET, based on a hexagonal BC 2 N-BN-BC 2 N heterostructure as a channel.…”

Section: Introductionmentioning

confidence: 99%

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Lateral BN-BCN Heterostructure Tunneling Transistor with Large Current Modulation

Horri

Faez

2022

ACS Appl. Electron. Mater.

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This paper, for the first time, presents a lateral tunneling transistor based on a two-dimensional boron nitride (BN) and hexagonal boron-carbon-nitrogen (hBCN) heterostructure. The device operation is analyzed based on a nonequilibrium Greens Function (NEGF) method and an atomistic tight-binding (TB) model. The TB hopping parameters are achieved by fitting the bandstructure to density functional theory (DFT) results. This model has been used to calculate the electrical characteristics of the device, such as I ON /I OFF ratio, subthreshold swing, and intrinsic gate-delay time. The results indicate a switching ratio of over eight orders of magnitude, much higher than the previous two-dimensional lateral or vertical tunneling transistor. Also, the device exhibits a low subthreshold swing of 42.17 mV/decade. The results show that the BN and BC 2 N conduction band edge (CBE) and valence band edge (VBE) play important roles in the electrical behavior of the device.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Lateral BN-BCN Heterostructure Tunneling Transistor with Large Current Modulation

Horri

Faez

2022

ACS Appl. Electron. Mater.

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“…pybinding tools are incorporated in python libraries [16]. Quantum tunneling in tunneling MOSFETs and study of sensors based on bottom up approaches have used tight binding models [17]. Also the tight-binding calculations have been used to analyse the transport features and to understand the origin of the various modes of transport in graphene nanoribbons using full-scale quantumtransport simulations [18]- [21].…”

Section: Introduction-graphene Modeling and Applicationsmentioning

confidence: 99%

A Novel Graphene Modelling: Bottom up Approach - Band Gap Studies to Transport in Python

Bhardwaj

2021

Preprint

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In this work we develop a computational, quantum level monolayer graphene nanoribbon (GNR) MOSFET of channel length of 10 and 20 nm, with a width of 2 nm and contacts of 2nm width is attached. To develop the MOSFET channel, a bottom up approach is adopted by developing the material model. First the material models of graphene nanoribbon is developed using pybinding module tool in python. The material models of monolayer, bilayer graphene nanoribbon are built on the principles of tight binding module. The methodology developed is based on the Hamiltonian matrix formulation that has been used to determine the E-k plots and LDOS plots of graphene monolayer, bilayer graphene nano ribbon. The GNR MOSFET that is structurally built in python is used to simulate graphene as a switch. Its band gap characteristics is presented as its performance as a switch and is verified with relevant work. Then GNR MOSFET is modelled using quantum principles of NEGF and greens function to determine the transmission characteristics and the I-V characteristics for channel lengths of 10 nm and 20 nm.

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“…Novel electronic devices have been realized by heterostructures based on vertical stacking or lateral stitching of 2D materials with different elec-tronic properties [6]. Lateral graphene/hexagonal boron nitride (Gr/hBN) heterostructures, due to very low lattice mismatch between graphene and hBN, are most suitable as platforms for fully two-dimensional nanoelectronic devices [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Effect of substitutional defects on resonant tunneling diodes based on armchair graphene and boron nitride nanoribbons lateral heterojunctions

Sanaeepur¹

2020

Beilstein J. Nanotechnol.

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A nanometer-scaled resonant tunneling diode based on lateral heterojunctions of armchair graphene and boron nitride nanoribbons, exhibiting negative differential resistance is proposed. Low-bandgap armchair graphene nanoribbons and high-bandgap armchair boron nitride nanoribbons are used to design the well and the barrier region, respectively. The effect of all possible substitutional defects (including BC, NC, CB, and CN) at the interface of graphene and boron nitride nanoribbons on the negative differential resistance behavior of the proposed resonant tunneling diode is investigated. Transport simulations are carried out in the framework of tight-binding Hamiltonians and non-equilibrium Green’s functions. The results show that a single substitutional defect at the interface of armchair graphene and boron nitride nanoribbons can dramatically affect the negative differential resistance behavior depending on its type and location in the structure.

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Tight-binding description of graphene–BCN–graphene layered semiconductors

Cited by 8 publications

References 32 publications

Lateral BN-BCN Heterostructure Tunneling Transistor with Large Current Modulation

Lateral BN-BCN Heterostructure Tunneling Transistor with Large Current Modulation

A Novel Graphene Modelling: Bottom up Approach - Band Gap Studies to Transport in Python

Effect of substitutional defects on resonant tunneling diodes based on armchair graphene and boron nitride nanoribbons lateral heterojunctions

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