semiconductor-sim 1.0.5

A simulation library for basic semiconductor devices aimed at undergraduates.

SemiconductorSim

SemiconductorSim is an open-source Python library designed to simulate fundamental semiconductor devices, making complex semiconductor physics accessible to undergraduate students. Accompanied by interactive tutorials and comprehensive examples, this library serves as a valuable educational tool for students, educators, and enthusiasts in the fields of electronics and semiconductor engineering.

🧭 Table of Contents

• Installation
• Features
• Supported Devices
• Quickstart
• Examples & Docs
• Units & Conventions
• Interactive Notebooks
• Development
• Troubleshooting
• Contributing
• License
• Releases

📚 Features

• PN Junction Diode Simulation: IV, SRH recombination, temperature dependence
• LED Simulation: IV with emission, efficiency model, temperature effects
• Solar Cell Simulation: IV under illumination, short/open-circuit conditions
• Tunnel, Varactor, Zener, MOS Capacitor: teaching-focused models and plots
• Interactive Visualizations: Jupyter widgets and Plotly/Matplotlib support
• Documentation: API references, tutorials, and example scripts

🧪 Supported Devices

• PN Junction Diode: Ideal diode with SRH recombination and temperature effects.
• LED: Diode IV with emission intensity; simple efficiency model.
• Solar Cell: IV under illumination; short/open-circuit conditions.
• Tunnel Diode: Simplified IV with correct reverse-bias behavior for teaching.
• Varactor Diode: Junction capacitance vs. reverse bias; IV characteristic.
• Zener Diode: Breakdown behavior with optional ML-predicted Zener voltage.
• MOS Capacitor: C–V and I–V characteristics with depletion width model.

🔧 Installation

Install from PyPI (recommended):

pip install semiconductor-sim

From source (editable):

git clone https://github.com/kennedym-ds/semiconductor_sim.git
cd semiconductor_sim
python -m venv .venv
. .venv/Scripts/activate
pip install -U pip
pip install -r requirements.txt
pip install -e .

🚀 Quickstart

Minimal PN junction example (no plotting required):

import numpy as np
from semiconductor_sim.devices import PNJunctionDiode

diode = PNJunctionDiode(doping_p=1e17, doping_n=1e17, temperature=300)
V = np.array([0.0, 0.2, 0.4])
I, R = diode.iv_characteristic(V, n_conc=1e16, p_conc=1e16)
print("Current:", I)
print("Recombination (SRH):", R)

LED quick preview (two-value return when concentrations omitted):

import numpy as np
from semiconductor_sim.devices import LED

led = LED(doping_p=1e17, doping_n=1e17, temperature=300)
V = np.linspace(0, 2, 5)
current, emission = led.iv_characteristic(V)

📓 Examples & Docs

• Examples: see the examples/ folder for scripts and Jupyter notebooks (interactive versions use ipywidgets/plotly).
• API docs: browse module docstrings and examples until hosted docs are added.

📐 Units & Conventions

• Length: cm; Area: cm²; Volume: cm³; Charge: C; Capacitance: F.
• Doping and carrier concentrations: cm⁻³.
• Temperature: K (default DEFAULT_T = 300 K).
• Constants available via semiconductor_sim.utils.constants: q, k_B, epsilon_0, DEFAULT_T.
• Return shapes: device iv_characteristic methods return arrays aligned to the input voltage_array. Where scalar recombination is computed, it is broadcast to match the voltage vector.

💡 Interactive Notebooks

• Explore interactive notebooks in examples/ with Jupyter and ipywidgets.
• Launch Jupyter:

python -m pip install jupyter ipywidgets
jupyter notebook examples

If running on a headless server/CI, plotting uses Matplotlib’s non-interactive backend automatically inside plotting helpers.

🖼️ Plotting Helper (Headless-Safe)

To keep plots consistent and CI-friendly, device plotting functions call lightweight helpers:

• semiconductor_sim.utils.plotting.use_headless_backend("Agg"): switch to a non-interactive backend before any figures are created.
• semiconductor_sim.utils.plotting.apply_basic_style(): apply minimal, consistent rcParams (grid, sizes, legend).

When writing new scripts that use Matplotlib directly, you can opt-in to the same behavior:

from semiconductor_sim.utils.plotting import (
  use_headless_backend,
  apply_basic_style,
)
use_headless_backend("Agg")
apply_basic_style()

import matplotlib.pyplot as plt
# ... your plotting code ...

Notes:

• Prefer relying on device .plot_* helpers where available.
• Avoid calling plt.switch_backend at runtime; set backend via the helper before any figures are created.

🧑‍💻 Development

Set up a virtual environment and install dev tools:

python -m venv .venv
. .venv/Scripts/activate
pip install -U pip
pip install -r requirements.txt
pip install -e .
pip install ruff mypy pytest pre-commit
pre-commit install

Run checks:

ruff check .
ruff format --check .
mypy .
pytest -q

CI runs Ruff, Mypy, and tests across Python 3.10–3.13 on Linux/Windows/macOS with coverage thresholds. It includes dependency review, pip-audit security checks, and CodeQL scanning. Dependabot keeps GitHub Actions and pip dependencies updated. Publishing to PyPI is automated on tags v*.*.*. See CHANGELOG.md for notable changes.

🩺 Troubleshooting

• "FigureCanvasAgg is non-interactive" warnings: safe to ignore in headless runs.
• Missing ML model for Zener voltage: library falls back to the configured default and prints a notice. You can train your own model and place the zener_voltage_rf_model.pkl under semiconductor_sim/models/ if desired.
• On Windows, ensure you activate the venv before running commands:

. .\.venv\Scripts\Activate.ps1

🤝 Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines. Typical flow:

git checkout -b feature/my-improvement
ruff check . && mypy . && pytest -q

Open a PR; CI runs lint, types, tests, CodeQL, and dependency review.

✅ Quality Checks

Before opening a PR, run the core checks locally:

ruff check .
ruff format --check .
mypy .
pytest -q

See the detailed checklist in the PR template:

• .github/pull_request_template.md

📄 License

This project is licensed under the MIT License — see LICENSE.

🏷️ Releases

• Versioning: semantic (MAJOR.MINOR.PATCH).
• Publishing: push a tag like v0.1.1 to trigger the publish workflow.