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CarrierCapture.py

Modern Python package for computing carrier capture rates and non-radiative recombination in semiconductors using multiphonon theory.

Tests Python Version License: MIT Code style: black

✨ Features

🧮 Complete Multiphonon Theory Implementation

  • 1D Schrödinger equation solver (ARPACK-based)
  • Harmonic, Morse, and spline potential fitting
  • Configuration coordinate diagrams
  • Capture coefficient calculations

⚡ High-Performance Computing

  • Parallel parameter scanning with joblib
  • Optimized with NumPy/SciPy (within 10-20% of Julia speed)
  • Support for HDF5 and NPZ result storage

🎨 Rich Visualization

  • Publication-quality plots with Plotly
  • Interactive Dash dashboard (web-based)
  • Real-time parameter exploration
  • Arrhenius plots, CC diagrams, 2D heatmaps

🔗 Integration with doped

  • Direct compatibility with doped defect calculation workflows
  • Load configuration coordinate data from doped outputs
  • Automated mass-weighted displacement calculations
  • Seamless end-to-end: DFT → defect analysis → capture rates

🚀 Quick Start

Installation

pip install carriercapture

For development or from source:

git clone https://github.com/WMD-group/CarrierCapture.py.git
cd CarrierCapture.py
pip install -e ".[dev]"

Python API

import numpy as np
from carriercapture.core.potential import Potential
from carriercapture.core.config_coord import ConfigCoordinate

# Create harmonic potentials
pot_initial = Potential.from_harmonic(hw=0.008, Q0=0.0, E0=0.5)
pot_final = Potential.from_harmonic(hw=0.008, Q0=10.5, E0=0.0)

# Solve Schrödinger equation
pot_initial.solve(nev=180)
pot_final.solve(nev=60)

# Calculate capture coefficient
cc = ConfigCoordinate(pot_i=pot_initial, pot_f=pot_final, W=0.068)
cc.calculate_overlap(Q0=5.0)
cc.calculate_capture_coefficient(
    volume=1e-21,
    temperature=np.linspace(100, 500, 50)
)

print(f"Capture coefficient at 300K: {cc.capture_coefficient[20]:.3e} cm³/s")

Command-Line Interface

# Fit potential from DFT data
carriercapture fit data/excited.dat -f spline -o 4 -s 0.001 -O excited.json

# Solve Schrödinger equation
carriercapture solve excited.json -n 180 -O excited_solved.json

# Calculate capture coefficient
carriercapture capture config.yaml -V 1e-21 --temp-range 100 500 50

# High-throughput parameter scan
carriercapture scan --dQ-min 0 --dQ-max 25 --dQ-points 25 \
                    --dE-min 0 --dE-max 2.5 --dE-points 10 \
                    -j -1 -o scan_results.npz

# Launch interactive dashboard
carriercapture viz --port 8050

📚 Documentation Sections

Getting Started

New to CarrierCapture? Start here!

User Guide

Learn how to use CarrierCapture effectively.

API Reference

Complete API documentation.

  • Core - Potential, ConfigCoordinate, Schrödinger solver
  • Analysis - Parameter scanning
  • I/O - File I/O and doped interface
  • Visualization - Plotting functions
  • CLI - Command-line interface

🔬 Scientific Background

CarrierCapture implements the static coupling approximation for non-radiative carrier capture via multiphonon emission (Huang-Rhys theory).

Key Equation

The capture coefficient is calculated as:

\[C(T) = \frac{V \cdot 2\pi}{\hbar} \cdot g \cdot W^2 \cdot \sum_{i,j} p_i |\langle\chi_i|Q-Q_0|\chi_j\rangle|^2 \delta(\varepsilon_i - \varepsilon_j)\]

Where:

  • \(V\): supercell volume
  • \(g\): degeneracy factor
  • \(W\): electron-phonon coupling matrix element
  • \(p_i\): thermal occupation of initial state \(i\)
  • \(\chi_i, \chi_j\): vibrational wavefunctions
  • \(\delta\): energy-conserving delta function (Gaussian broadened)

References

  1. Alkauskas et al. (2014) - Phys. Rev. B 90, 075202
  2. Huang & Rhys (1950) - Proc. R. Soc. Lond. A 204, 406

🎯 Project Status

Component Status
Core Engine ✅ Complete
CLI ✅ Complete
Visualization ✅ Complete
Parameter Scanning ✅ Complete
doped Integration ✅ Complete
Documentation ✅ Complete
Test Coverage ✅ 88 tests
PyPI Release 🔄 Planned

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments