nano-negf 0.1.1

1D NEGF-Poisson nanowire solver package

Nano NEGF

A Python framework for the self-consistent solution of 1D Non-Equilibrium Green's Function (NEGF) and Poisson equations for nanowire structures.

Features

• 1D Poisson solver with Neumann Boundary Conditions.

• Calculation of electron density and tunneling current using the NEGF formalism (Recursive Green's Function algorithm).

• Self-consistent loop for the convergence of electrostatic potential and charge density.

• Adjustable physical parameters including effective mass ($m^*$), relative permittivity ($\epsilon_r$), Fermi levels of the leads ($\mu_L$ and $\mu_R$), and temperature ($T$).

• Built-in visualization for energy band diagrams and carrier density profiles.

Dependencies

This package requires Python 3.11 or newer and the following libraries:

• numpy

• matplotlib

Installation

To install the package, navigate to the root directory of the project (where pyproject.toml is located) in your terminal and run:

pip  install  -e  .

Note: The -e (editable) flag allows you to modify the source code without needing to reinstall the package.

Project Structure

nano_negf/

├── pyproject.toml # Package build configuration

├── nano_negf/ # Main source code

│ ├── __init__.py

│ ├── constants.py # Physical constants

│ ├── physics.py # Physics utilities (energy grids, Fermi functions, self-energy)

│ ├── poisson.py # Matrix-based Poisson solver

│ ├── negf.py # RGF algorithm, density, and current calculations

│ └── solver.py # Main SelfConsistentSolver class

└── example.py # Example usage script

Quick Start (Usage)

Once installed, you can import and use the SelfConsistentSolver in your scripts or go to the example file and run the code. Here is a basic example:

from nano_negf import SelfConsistentSolver

  

# 1. Initialize the solver with desired parameters

sim = SelfConsistentSolver(

N=100, # Number of grid points

dx=1e-9, # Grid spacing (m)

m_eff_ratio=0.25, # Electron effective mass ratio

mu_L=0.1, # Left lead chemical potential (eV)

mu_R=0.0, # Right lead chemical potential (eV)

Nd=1e24 # Doping density (1/m^3)

)

  

# 2. Run the self-consistent loop

sim.run(max_iter=800, mix=0.1, tol=1e-4)

  

# 3. Plot the results (Band diagram and Carrier density)

sim.plot_results()

License

Copyright (c) 2026 Mohammad Saeed Foroughi