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How do I optimize solar cell materials with MatCraft?

Material Domains
solar
perovskite
photovoltaic

MatCraft supports optimization of both perovskite and silicon solar cells. The solar cell domain plugin provides physics models for predicting power conversion efficiency and stability from material parameters.

Perovskite Solar Cells

Perovskite absorbers have the general formula ABX3, where A, B, and X site compositions dramatically affect performance:

yaml
name: "perovskite-absorber"
domain: solar_cell

components:
  - name: ma_fraction
    type: continuous
    bounds: [0.0, 1.0]
    description: "Methylammonium (MA) fraction on A-site"
  - name: fa_fraction
    type: continuous
    bounds: [0.0, 1.0]
    description: "Formamidinium (FA) fraction on A-site"
  - name: cs_fraction
    type: continuous
    bounds: [0.0, 0.2]
    description: "Cesium fraction on A-site"
  - name: pb_fraction
    type: continuous
    bounds: [0.5, 1.0]
    description: "Lead fraction on B-site"
  - name: sn_fraction
    type: continuous
    bounds: [0.0, 0.5]
    description: "Tin fraction on B-site"
  - name: iodide_fraction
    type: continuous
    bounds: [0.5, 1.0]
    description: "Iodide fraction on X-site"
  - name: bromide_fraction
    type: continuous
    bounds: [0.0, 0.5]
  - name: absorber_thickness
    type: continuous
    bounds: [200, 800]
    unit: "nm"

constraints:
  - type: sum_equals
    components: [ma_fraction, fa_fraction, cs_fraction]
    value: 1.0
  - type: sum_equals
    components: [pb_fraction, sn_fraction]
    value: 1.0
  - type: sum_equals
    components: [iodide_fraction, bromide_fraction]
    value: 1.0

objectives:
  - name: pce
    direction: maximize
    unit: "%"
    description: "Power conversion efficiency"
  - name: stability_t80
    direction: maximize
    unit: "hours"
    description: "Time to 80% of initial efficiency under 1-sun illumination"
  - name: bandgap
    direction: minimize
    description: "Deviation from Shockley-Queisser optimal bandgap (1.34 eV)"

Built-In Physics

The solar cell plugin includes:

  • Bandgap estimation: Vegard's law interpolation from end-member bandgaps, accounting for bowing parameters for mixed compositions.
  • Shockley-Queisser limit: Theoretical maximum efficiency as a function of bandgap.
  • Stability heuristic: Empirical model based on Goldschmidt tolerance factor and octahedral factor — compositions with tolerance factors closer to 1.0 are predicted to be more stable.
  • Absorption coefficient model: Estimates absorption edge and Urbach energy from composition.

Typical Campaign

A perovskite optimization campaign with 8 parameters typically converges in 15-20 iterations. The Pareto front between efficiency and stability reveals the fundamental trade-off: Sn-rich compositions can achieve high efficiency but suffer from rapid oxidation, while Cs-containing compositions are more stable but have wider bandgaps.

Silicon Solar Cells

For silicon cells, the domain covers doping profiles, surface texturing parameters, anti-reflection coating thickness, and metallization geometry. The physics model uses a simplified PC1D-style simulation for rapid efficiency estimation.

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