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About ASCICat

Overview

ASCICat (Activity-Stability-Cost Integrated Catalyst Discovery) is a Python framework for multi-objective electrocatalyst screening.

Mission

To provide the computational catalysis community with a standardized, transparent, and reproducible framework for translating DFT/ML catalyst databases into actionable experimental priorities.

Key Features

  • Unified Metric: The ASCI score combines activity, stability, and cost into a single interpretable number
  • Transparent: All scoring functions and weight choices are explicit and documented
  • Reproducible: Same data + same weights = same rankings, always
  • Comprehensive: Built-in sensitivity analysis, visualization, and statistical tools
  • Accessible: Python API, CLI, and GUI interfaces

Development

ASCICat is developed at the Dutch Institute for Fundamental Energy Research (DIFFER).

Author

N. Khossossi Research Scientist DIFFER n.khossossi@differ.nl

Acknowledgments

This work was supported by DIFFER and the Dutch Research Council (NWO).

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