mat-pourbaix-diagram

Pourbaix Diagram

Goal

To calculate thermodynamically consistent Pourbaix (pH-voltage) diagrams for assessing the aqueous electrochemical stability of materials. This skill uses Machine Learning Interatomic Potentials (MLIPs) for solid phase energies combined with Materials Project data for aqueous species, following the rigorous methodology of Persson et al. (2012)¹.

Applications:

• Alkaline-stable solid-state electrolytes (Li-air batteries)
• Corrosion-resistant materials
• Aqueous battery electrodes
• Electrochemical stability screening

Features

• Automated Referenced: Fetches elemental energies from elemental-energies skill to fill missing terminal entries (e.g., if you relaxed LiCoO2 but forgot Li metal, it will be auto-loaded).
• H2O Reference: Checks resources/h2o_energies.json values matching the MLIP checkpoint. If found, uses this pre-calculated energy. If not found, falls back to look for H2O relaxation in the --relaxed_solids directory.
• MP2020 Compatibility: Automatically detects if compatibility corrections are needed via gga-ggau-mixed-mlips.yaml.

Background

Pourbaix Diagrams

A Pourbaix diagram shows the thermodynamically stable phases as a function of pH and electrochemical potential (voltage vs. SHE). The diagram maps stability domains for solids and dissolved ions in aqueous environments.

Critical: Thermodynamic Consistency

The Challenge: Mixing computational (MLIP/DFT) solid energies with experimental aqueous ion data creates energy scale mismatch.

The Solution (Persson et al. 2012)¹: Water correction that aligns MLIP water formation energy with experimental Gibbs free energy. We use a robust cycle that fixes the hydrogen reference to the Standard Hydrogen Electrode (SHE) scale.

3. Automated Referencing

The script calculate_pourbaix.py automatically:

1. Fetches per-atom elemental energies from the elemental-energies skill.
2. Applies thermodynamic corrections for H₂ gas ($S^\circ$, $\Delta H$) to deriving $\mu_H$.
3. Uses a locally relaxed H₂O structure to derive $\mu_O$, ensuring correct water formation energy.
   • H2O Reference: Checks resources/h2o_energies.json values matching the MLIP checkpoint. If found, uses this pre-calculated energy. If not found, falls back to look for H2O relaxation in the --relaxed_solids directory.