Official Resources
- Homepage: http://vides.nanotcad.com/
- Repository: https://github.com/vides-hub/vides
- License: BSD License
Overview
NanoTCAD ViDES (Vintage Integrated Development Environment for Simulations) is an open-source software package for the simulation of nanoscale electronic devices. It is particularly renowned for its ability to simulate 2D material-based devices (graphene, MoS2) using the Non-Equilibrium Green's Function (NEGF) formalism self-consistently coupled with a 2D/3D Poisson solver. The code is wrapped in Python, providing a flexible scripting environment for investigating novel transistor architectures.
Scientific domain: Nanoelectronics, CNTs, Graphene, TMDs
Target user community: Device engineers and physicists developing post-silicon logic
Theoretical Methods
- NEGF Formalism: Standard coherent transport formalism for calculating density and current.
- Poisson Solver: Finite difference solver for the electrostatic potential in 2D/3D geometries.
- Self-Consistency: Newton-Raphson or Gummel iteration to solve the coupled Schrödinger-Poisson system.
- Hamiltonians:
- Tight-Binding models (Nearest neighbor, etc.).
- Massless Dirac Fermions (Continuous models).
- Maximally Localized Wannier Functions (integration).
Capabilities
- Simulations:
- Graphene Nanoribbon FETs (GNR-FETs).
- Carbon Nanotube FETs (CNT-FETs).
- TMD Transistors (MoS2, WSe2).
- Heterojunctions and tunneling barriers.
- Observables:
- Transfer characteristics ($I_d-V_g$).
- Output characteristics ($I_d-V_d$).
- Local Density of States (LDOS).
- Potential profiles and subband structures.
Key Strengths
- Python Interface: The
pyViDES module allows users to construct simulations using standard Python syntax, making it highly accessible and easy to integrate with plotting libraries.
- 2D Focus: Specialized routines and material parameters for graphene and transition metal dichalcogenides.
- Drift-Diffusion: Also includes a semi-classical drift-diffusion module for comparing ballistic vs classical limits.
Inputs & Outputs
- Inputs: Python scripts defining the device geometry, materials, and bias loop.
- Outputs:
- Text files (currents).
- Grid data (potential, charge) for visualization.
Interfaces & Ecosystem
- Wannier90: Can import Wannier Hamiltonians for atomistic accuracy.
- Python: Full integration with NumPy/SciPy/Matplotlib.
Performance Characteristics
- Computational Cost: NEGF inversion is $O(N_y^3)$ (width). Efficient for narrow ribbons/nanotubes; slower for wide devices.
- Parallelism: MPI parallelization over energy points.
Comparison with Other Codes
- vs. Kwant: Kwant generally lacks the built-in self-consistent Poisson solver required for realistic transistor characteristics (I-V curves); ViDES provides this "TCAD" functionality out-of-the-box.
- vs. NEMO5: NEMO5 is a heavier, industrial-scale code; ViDES is lighter and better suited for rapid academic prototyping of 2D devices.
Community and Support
- Development: University of Pisa (Gianluca Fiori, Giuseppe Iannaccone).
- Source: GitHub and website.
Verification & Sources
- Website: http://vides.nanotcad.com/
- Primary Publication: G. Fiori and G. Iannaccone, IEEE Electron Device Lett. (2007).
- Verification status: ✅ VERIFIED
- Well-established in the 2D device community.