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Theoretical Background

The scientific foundation of the ASCI framework.

The Catalyst Selection Problem

Computational catalysis databases contain thousands of DFT-calculated catalyst properties. The challenge is translating this data into actionable experimental priorities.

Traditional approaches:

  1. Single-objective ranking - Sort by one metric (e.g., activity)
  2. Manual multi-criteria - Ad-hoc weighting, poorly documented
  3. Pareto analysis - Non-dominated set, no ranking

ASCICat provides:

  • Unified, interpretable metric
  • Transparent, reproducible rankings
  • Built-in sensitivity analysis

Three-Pillar Framework

Activity (Thermodynamic)

Based on the Sabatier principle and volcano relationships:

\[S_a(\Delta E) = \max\left(0, 1 - \frac{|\Delta E - \Delta E_{opt}|}{\sigma_a}\right)\]

Physical basis:

  • DFT binding energies correlate with activation barriers
  • Optimal binding balances adsorption and desorption
  • Volcano plots validated experimentally

Stability (Thermodynamic)

Based on surface thermodynamics:

\[S_s(\gamma) = \frac{\gamma_{max} - \gamma}{\gamma_{max} - \gamma_{min}}\]

Physical basis:

  • Lower surface energy → stronger surface bonding
  • Correlates with dissolution resistance
  • Validated for metal dissolution in electrochemistry

Cost (Economic)

Based on material economics:

\[S_c(C) = \frac{\log C_{max} - \log C}{\log C_{max} - \log C_{min}}\]

Physical basis:

  • Raw material cost as proxy for catalyst cost
  • Logarithmic scaling handles 5+ orders of magnitude
  • Economic viability critical for deployment

Integration: The ASCI Score

Weighted linear combination:

\[\phi_{ASCI} = w_a \cdot S_a + w_s \cdot S_s + w_c \cdot S_c\]

Properties:

  • Bounded: \(\phi \in [0, 1]\)
  • Interpretable: Higher = better
  • Customizable: Weights reflect priorities
  • Constraint: \(w_a + w_s + w_c = 1\)

Assumptions

  1. DFT accuracy - Binding energies are meaningful
  2. Descriptor validity - Chosen descriptors capture key properties
  3. Linear aggregation - Trade-offs are linear
  4. Independence - Scores are approximately independent

Limitations

  • Kinetic barriers not directly captured
  • Support effects not included
  • Electrolyte effects not modeled
  • Deactivation mechanisms not predicted

Validation

ASCICat rankings are validated by:

  1. Pareto consistency - Top ASCI catalysts are mostly Pareto-optimal
  2. Known benchmarks - Pt-group metals rank highly for HER
  3. Sensitivity robustness - Rankings stable across weight ranges