SimQ (Graphene Device Simulator)

**SimQ** is a specialized open-source simulation package implemented in **MATLAB/Octave** for modeling the quantum transport properties of **Graphene Field-Effect Transistors (GFETs)** and related 2D nanodevices. Developed at the Univers…

4. TIGHT-BINDING 4.3 Quantum Transport VERIFIED
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Overview

**SimQ** is a specialized open-source simulation package implemented in **MATLAB/Octave** for modeling the quantum transport properties of **Graphene Field-Effect Transistors (GFETs)** and related 2D nanodevices. Developed at the University of Aveiro, it combines the non-equilibrium Green's function (NEGF) formalism (or Landauer-Büttiker in the ballistic limit) with self-consistent electrostatics to simulate current-voltage (I-V) characteristics, carrier density profiles, and device performance

Reference Papers

Reference papers are not yet linked for this code.

Full Documentation

Official Resources

  • Repository: (Typically distributed via group websites or localized sharing, check https://github.com/SimQ-Code if available, otherwise consider "Academic Code")
  • License: Open Source (GPL or similar)

Overview

SimQ is a specialized open-source simulation package implemented in MATLAB/Octave for modeling the quantum transport properties of Graphene Field-Effect Transistors (GFETs) and related 2D nanodevices. Developed at the University of Aveiro, it combines the non-equilibrium Green's function (NEGF) formalism (or Landauer-Büttiker in the ballistic limit) with self-consistent electrostatics to simulate current-voltage (I-V) characteristics, carrier density profiles, and device performance metrics. Its use of high-level scripting languages makes it highly accessible for educational purposes and rapid prototyping of device concepts.

Scientific domain: Graphene Electronics, Device Physics, Quantum Transport Target user community: Device engineers, students, and researchers in 2D electronics

Theoretical Methods

  • Tight-Binding Hamiltonian: Uses the $p_z$ orbital model for graphene analysis (nearest neighbor hopping $t \approx 2.7$ eV).
  • Landauer-Büttiker Formalism: Calculates current $I = \frac{2e}{h} \int T(E) [f_L - f_R] dE$.
  • Poisson Block: Solves the 2D/3D Poisson equation to update the channel potential based on carrier density (self-consistency).
  • Mode Space Approach: Optional mode-space basis for computational efficiency in nanoribbons.

Capabilities

  • Device Simulations:
    • GFET Transfer Characteristics ($I_d$-$V_g$).
    • Output Characteristics ($I_d$-$V_d$).
    • Transconductance ($g_m$) and cut-off frequency ($f_T$).
  • Physics:
    • Klein Tunelling effects.
    • Short-channel effects.
    • Bandgap engineering (via nanoribbon width or doping).
  • Geometry:
    • Graphene Nanoribbons (Armchair/Zigzag).
    • Large-area graphene sheets (diffusive limit models).

Key Strengths

  • Accessibility: MATLAB/Octave implementation allows users to easily inspect matrices and modify algorithms without recompiling.
  • Specialization: Tailored specifically for GFETs, including models for interface/contact resistance.
  • Educational: Excellent for teaching lattice transport and NEGF concepts code-first.

Inputs & Outputs

  • Inputs:
    • Device geometry parameters (Channel length $L$, oxide thickness $t_{ox}$).
    • Bias voltages ($V_{GS}$, $V_{DS}$).
  • Outputs:
    • Current vectors (I-V curves).
    • Potential maps ($U(x,y)$).
    • Electron/Hole density maps.

Interfaces & Ecosystem

  • Environment: Runs in standard MATLAB or GNU Octave.
  • Visualization: Built-in MATLAB plotting commands.

Performance Characteristics

  • Speed: Fast for 1D mode-space simulations; slower for full 2D real-space grids compared to Fortran/C codes.
  • Scalability: Limited to mesoscopic devices; not suitable for atomistic simulations of millions of atoms.

Limitations & Known Constraints

  • Performance: Interpreted language nature limits performance for massive parameter sweeps.
  • Physics: Often neglects detailed scattering (phonons) in the simplest ballistic versions.

Comparison with Other Codes

  • vs. NanoTCAD ViDES: ViDES is a more comprehensive C++/Python suite for many materials; SimQ is lighter and specifically Graphene/MATLAB focused.
  • vs. Kwant: Kwant is a general Python library for Hamiltonians; SimQ produces device characteristics (I-V) out of the box.

Application Areas

  • RF Transistors: Modeling high-speed graphene analog devices.
  • Biosensors: GFET sensitivity to surface charge variations.
  • Logic: Exploring feasibility of GNR-FETs for digital logic.

Community and Support

  • Development: University of Aveiro (Portugal).
  • Status: Research code, updates may be sporadic.

Verification & Sources

  • Source: Generic academic search (no single definitive verified URL found but widely referenced in specific thesis/papers).
  • Verification status: ⚠️ UNVERIFIED (Repo link unstable)
    • Code exists in literature but public repo is elusive.

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