AI-driven perovskite solar cell optimization platform with OpenAI Agents SDK
Project description
OpenRXN Perovskite Optimizer
Python Version License Code Style: Black Agents: OpenAI SDK
Author: Nik Jois (nikjois@llamasearch.ai)
Welcome to the OpenRXN Perovskite Optimizer. This platform provides AI-driven materials discovery and optimization for perovskite solar cells using a multi-agent architecture.
Key Features
- Multi-Agent Architecture: Coordinated AI agents for discovery, synthesis, and optimization.
- Machine Learning: Advanced property prediction and materials design.
- Experimental Integration: Automated synthesis protocols and characterization.
- Web Interface: Interactive dashboard and comprehensive REST API.
- High Performance: GPU acceleration and distributed computing support.
- Scientific Rigor: Comprehensive testing and experimental validation.
Quick Start
Install the package and start optimizing perovskite materials:
# Install with automatic setup
curl -sSL https://raw.githubusercontent.com/openrxn/openrxn-perovskite-optimizer/main/scripts/install.sh | bash
# Or install manually
git clone https://github.com/openrxn/openrxn-perovskite-optimizer
cd openrxn-perovskite-optimizer
uv venv --python 3.11
source .venv/bin/activate
uv pip install -e ".[all]"
Discover new materials:
# Discover materials based on MAPbI3
perovskite-optimizer discover materials --composition MAPbI3 --target-efficiency 25.0
# Generate synthesis protocols
perovskite-optimizer synthesize protocol --composition "MA0.8FA0.2PbI3"
# Optimize compositions
perovskite-optimizer optimize composition --base "MAPbI3" --objectives efficiency stability cost
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