NanoNets

NanoNets is a Python package for simulating single-electron transport in complex nanoparticle networks.
It provides tools for generating and analyzing nanoparticle device topologies, computing network electrostatics, and running efficient kinetic Monte Carlo (KMC) simulations of single-electron tunneling.
Designed for both fundamental research and device engineering.

Features

• Flexible Topology: Create regular lattice or random planar nanoparticle networks with customizable geometry and connectivity.
• Physical Electrostatics: Automatically computes full capacitance matrices and induced charges using physical NP parameters.
• Kinetic Monte Carlo: High-performance, Numba-optimized KMC engine for simulating electron tunneling, network currents, and time-resolved device response.
• Constant and Floating Electrodes: Simulate both voltage-biased and floating (open circuit) contacts.
• Heterogeneous Devices: Supports multiple nanoparticle types, resistive disorder, and tunable electrode configurations.
• Extensible & Modular: Clear class structure enables easy modification and integration with other scientific Python tools.
• Batch and Time-Dependent Simulation: Supports stationary (fixed voltage) and dynamic (time-varying voltage) simulation modes.
• Rich Output: Exports observables, charge/potential landscapes, network currents, and more, directly to CSV for analysis.

Class Overview

Quickstart Example

```from nanonets import Simulation import numpy as np

Define your network topology and parameters

topologyparameter = { 'Nx': 5, 'Ny': 5, # 5x5 lattice 'epos': [[0,0], [4,4]], # Electrodes at two corners 'electrode_type': ['constant', 'constant'] # Both are not floating }

Initialize simulation

sim = Simulation(topology_parameter)

Run a stationary simulation (fixed voltages)

Nvolt = 100 # Number of voltages voltages = np.zeros((Nvolt,3)) # 3 Columns (Two E + Gate) voltages[:,0] = np.linspace(-0.1, 0.1, Nvolt) # Voltage Sweep at E1 sim.runconstvoltages(voltages, targetelectrode=1)

Access results

currents = sim.getobservablestorage() potentials = sim.getpotentialstorage() ```

Citing

If you use NanoNets for published work, please cite:

@article{mensing2024kinetic,
  title={A kinetic Monte Carlo approach for Boolean logic functionality in gold nanoparticle networks},
  author={Mensing, Jonas and van der Wiel, Wilfred G and Heuer, Andreas},
  journal={Frontiers in Nanotechnology},
  volume={6},
  pages={1364985},
  year={2024},
  publisher={Frontiers Media SA}}