COMSOL Optical / Optoelectronic Simulation

Automate COMSOL Multiphysics simulations through the mph Python interface for user-configured optical, semiconductor, thermal, or coupled multiphysics projects.

This skill is topic-neutral. It does not assume a material stack, device type, measured benchmark, local COMSOL path, or default parameter set.

OpenClaw / ClawHub Quick Start

Install from ClawHub:

openclaw skills install comsol-opto-simulation

After installation, verify the offline helpers before any license-consuming COMSOL run:

python scripts/test_sweep_offline.py
python scripts/discover_comsol_environment.py --pretty

Run python scripts/install_mph.py only when the user approves dependency installation. It installs Python bridge packages into a skill-local vendor/site-packages directory and does not install COMSOL or provide a license.

Scope

Use this skill for:

• optical absorption and field-distribution models
• semiconductor or transport models
• thermal-electrical coupled models
• parameter sweeps and batch studies
• post-processing of simulated device or sample metrics
• convergence diagnostics and solver fallback planning

Do not use this skill to invent missing material parameters, boundary conditions, or validation data. Ask the user to configure those values first.

Required User Configuration

Before running COMSOL automation, collect or confirm:

• COMSOL installation path and available modules
• geometry dimension and domain/layer list
• material parameters and their sources
• optical constants or source/excitation terms
• electrical/thermal/mechanical boundary conditions as relevant
• solver strategy and sweep variables
• output metrics and validation criteria

Use:

• templates/device_stack.json
• templates/config_sweep.json
• templates/config_thermal.json
• templates/official_photogeneration_coupling.json
• references/script-map.md
• references/material-database.md
• references/input-schema.md

as generic templates only.

Workflow

1. Discover local COMSOL:

   python scripts/discover_comsol_environment.py --pretty
   

2. Check official resources and licenses when the user permits a license-consuming check:

   python scripts/probe_application_library_examples.py --pretty
   python scripts/check_comsol_products.py --skip-start --pretty
   

3. Install or verify the workspace-local Python bridge:

   python scripts/install_mph.py
   

4. Create a project-specific config by copying a template and replacing all \x3CUNCONFIGURED> values.
5. Run the appropriate script:

   python scripts/run_optoelectronic_sim.py --config \x3Cproject_config.json>
   python scripts/run_parameter_sweep.py --config \x3Cproject_sweep_config.json>
   

   If unsure which script to use, read references/script-map.md first.
6. Inspect exported plots, CSV files, JSON summaries, and COMSOL model artifacts under output/.
7. Report assumptions, fitted parameters, solver settings, convergence status, and validation gaps.

Prerequisites

• COMSOL Multiphysics compatible with the selected physics
• Required COMSOL modules for the selected model
• Python 3.10+
• Java runtime compatible with COMSOL/mph

Escalation

• If COMSOL is not installed, ask the user to provide the installation path or install COMSOL.
• If a required module is missing, report the missing module and suggest a reduced model if possible.
• If a simulation diverges, reduce step size, simplify physics, inspect material parameters, adjust scaling, and add continuation or fallback strategies.
• If a parameter sweep fails mid-way, use checkpoint/resume behavior where configured.

References

• references/input-schema.md
• references/material-database.md
• references/comsol-api-patterns.md
• references/comsol-docs-java-playbook.md
• references/comsol-official-learning-roadmap.md
• references/comsol-convergence-diagnostics.md
• references/comsol-official-photogeneration-template.md
• references/thermal-coupling-guide.md
• references/parameter-sweep-guide.md