Forerunner 5 (AIchemy) Documentation¶

Welcome to the comprehensive documentation for fr5 (Forerunner 5), the AIchemy project's Python toolkit for chemical informatics and optimization!

🔬 What is fr5?¶

fr5 is a Python package with set of tools for reaction optimization and exploration of search space that enables finding new chemical species and reaction conditions that lead to the best reaction outcomes. It provides powerful tools for:

🧪 Molecular Descriptors: Generate comprehensive descriptors for ionic liquids (ILs) and Metal-Organic Frameworks (MOFs)
📊 Property Prediction: Machine learning models for predicting chemical properties (viscosity, density, CO₂ solubility/uptake)
⚗️ Reaction Analysis: Predict reaction outcomes including conversion and selectivity
🎯 Bayesian Optimization: Advanced optimization algorithms for experimental design
📈 Visualization: Built-in plotting and analysis tools

🚀 Quick Start¶

import fr5

# Example: Predict ionic liquid viscosity
from fr5.property_prediction_il import predict_viscosity

# Your IL composition data
il_data = {
    'cation': 'EMIM',
    'anion': 'BF4',
    'temperature': 298.15
}

# Get viscosity prediction
result = predict_viscosity(il_data)
print(f"Predicted viscosity: {result['viscosity']:.2f} mPa·s")

📦 Package Structure¶

The fr5 package is organized into several main modules:

Module	Description
`fr5.descriptors`	Molecular descriptor generation for ILs and MOFs
`fr5.property_prediction_il`	Ionic liquid property prediction models
`fr5.property_prediction_mof`	MOF property prediction models
`fr5.bayes_opt`	Bayesian optimization for experimental design
`fr5.reaction_analysis`	Reaction outcome prediction
`fr5.shared`	Shared utilities and helper functions

📚 Documentation Sections¶

Installation: Setup and installation guide
Overview: Detailed introduction to fr5 capabilities
IL Property Prediction: Ionic liquid property models
MOF Property Prediction: MOF property models
Bayesian Optimization: Experimental design and optimization
API Reference: Complete code documentation

💡 Need Help?¶

Browse the API Reference for detailed function documentation
Visit our GitHub repository for source code and issues

Developed as part of the AIchemy project at Imperial College London.