Getting Started¶
Welcome to ASCICat! This guide will help you get up and running with multi-objective catalyst screening.
What is ASCICat?¶
ASCICat (Activity-Stability-Cost Integrated Catalyst Discovery) is a Python framework that enables researchers to:
- Rank catalysts based on multiple performance criteria simultaneously
- Generate high-quality figures for scientific analysis
- Perform sensitivity analysis to understand how weight choices affect rankings
- Compare results reproducibly across different studies
The ASCI Score¶
The core of ASCICat is the unified ASCI metric:
\[\phi_{ASCI} = w_a \cdot S_a + w_s \cdot S_s + w_c \cdot S_c\]
| Component | Description | Range |
|---|---|---|
| \(S_a\) | Activity score (Sabatier principle) | [0, 1] |
| \(S_s\) | Stability score (surface energy) | [0, 1] |
| \(S_c\) | Cost score (economic viability) | [0, 1] |
| \(w_a, w_s, w_c\) | Customizable weights | Sum to 1 |
Equal Weights by Default
ASCICat uses equal weights (0.33, 0.33, 0.34) by default for unbiased exploratory screening. You can customize these based on your application requirements.
Quick Links¶
-
Installation
Install ASCICat via pip or from source
-
Quick Start
Run your first ASCI calculation in 5 minutes
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First Analysis
Complete walkthrough of an HER screening analysis
System Requirements¶
| Requirement | Minimum | Recommended |
|---|---|---|
| Python | 3.8+ | 3.10+ |
| RAM | 4 GB | 8 GB+ |
| Storage | 100 MB | 500 MB |
Supported Platforms¶
- Linux (Ubuntu, CentOS, Fedora)
- macOS (10.14+)
- Windows (10/11)
Next Steps¶
- Install ASCICat - Set up the package
- Quick Start - Run your first analysis
- Explore Tutorials - Learn advanced features