Back to Prompt Library
planning

Model Pore Network & Ion Transport

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: AI-Driven Supercapacitor Design via Pore Network & Electrolyte Optimization

Format
Code-aware
Lines
1
Sections
1
Linked challenge
AI-Driven Supercapacitor Design via Pore Network & Electrolyte Optimization

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines
1 sections
No variables
0 checklist items
Develop a `PoreNetworkSimulator` class that takes idealized pore network parameters (e.g., porosity, average pore diameter, a tortuosity factor) and electrolyte properties (e.g., ionic conductivity, viscosity). Implement a simplified model (e.g., based on Bruggeman's correlation or a similar effective medium theory) to calculate the effective ion diffusion coefficient and estimate a proxy for charging time. Document the assumptions and limitations of your simulation model.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Preserve the role framing, objective, and reporting structure so comparison runs stay coherent.

Tune next

Swap in your own domain constraints, anomaly thresholds, and examples before you branch variants.

Verify after

Check whether the prompt asks for the right evidence, confidence signal, and escalation path.