NanoNet

Official Resources

• GitHub: https://github.com/freude/NanoNet
• Documentation: Available in repository
• License: BSD License

Overview

NanoNet is a tight-binding package designed for electronic structure calculations of nanostructures including nanowires, quantum dots, and heterostructures. It provides tools for building atomistic models and computing electronic properties using the tight-binding method with focus on semiconductor nanostructures.

Scientific domain: Nanostructure electronic structure, tight-binding, quantum transport Target user community: Researchers studying semiconductor nanostructures and quantum devices

Theoretical Background

NanoNet implements:

• Tight-binding Hamiltonian for sp³d⁵s* orbitals
• Strain effects via valence force field
• NEGF for quantum transport
• Spin-orbit coupling

Capabilities (CRITICAL)

• Nanostructures: Nanowires, quantum dots, superlattices
• Heterostructures: Interface and junction modeling
• Band Structure: Electronic bands with strain effects
• Transport: NEGF quantum transport calculations
• Strain: Valence force field relaxation
• Spin-Orbit: SOC implementation

Key Strengths

Nanostructure Focus:

• Optimized for nanoscale systems
• Efficient for large atomistic models
• Realistic semiconductor parameters

Heterostructure Support:

• Interface band alignment
• Core-shell structures
• Superlattice modeling

Transport Calculations:

• NEGF implementation
• Transmission functions
• I-V characteristics

Inputs & Outputs

• Input formats:

  • Structure definitions
  • Material parameters
  • Device geometry

• Output data types:

  • Band structures
  • DOS
  • Transmission spectra
  • Current-voltage curves

Installation

pip install nanonet

Usage Examples

from nanonet import tb

# Create nanowire
wire = tb.Nanowire(material='Si', diameter=3.0, length=10.0)

# Calculate band structure
bands = wire.compute_bands(kpoints=100)

# Transport calculation
transmission = wire.compute_transmission(energy_range=[-1, 1])

Performance Characteristics

• Speed: Optimized for nanostructures
• Memory: Efficient sparse matrices
• Scalability: Handles thousands of atoms

Limitations & Known Constraints

• Semiconductor focus: Primarily for III-V and group IV
• Parameter dependent: Requires TB parameters
• Large systems: Memory limits for very large structures

Comparison with Other Tools

• vs sisl: NanoNet specialized for nanostructures
• vs Kwant: Different focus, both for transport
• Unique strength: Semiconductor nanostructure focus, strain

Application Areas

• Semiconductor nanowires
• Quantum dots
• Core-shell nanostructures
• Nanoscale transistors
• Thermoelectric devices

Verification & Sources

Primary sources:

1. GitHub: https://github.com/freude/NanoNet

Confidence: VERIFIED

Verification status: ✅ VERIFIED

• Source code: OPEN (GitHub, BSD)
• Developer: freude