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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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