thermodynamic-model-selector
Automated thermodynamic property method selection based on component characteristics and operating conditions
Best use case
thermodynamic-model-selector is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Automated thermodynamic property method selection based on component characteristics and operating conditions
Teams using thermodynamic-model-selector should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/thermodynamic-model-selector/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How thermodynamic-model-selector Compares
| Feature / Agent | thermodynamic-model-selector | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Automated thermodynamic property method selection based on component characteristics and operating conditions
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Thermodynamic Model Selector Skill
## Purpose
The Thermodynamic Model Selector Skill guides selection of appropriate thermodynamic property methods based on component characteristics, operating conditions, and accuracy requirements.
## Capabilities
- Component analysis (polarity, association, electrolytes)
- Operating condition assessment
- Property method recommendation
- Binary interaction parameter fitting
- VLE/LLE data regression
- Model validation against experimental data
- Uncertainty quantification
## Usage Guidelines
### When to Use
- Selecting property methods for simulation
- Fitting interaction parameters
- Validating thermodynamic models
- Assessing model uncertainty
### Prerequisites
- Component list defined
- Operating ranges specified
- Experimental data available
- Accuracy requirements known
### Best Practices
- Consider all phase equilibria
- Validate with experimental data
- Document model selection rationale
- Assess sensitivity to parameters
## Process Integration
This skill integrates with:
- Process Simulation Model Development
- Distillation Column Design
- Crystallization Process Design
## Configuration
```yaml
thermodynamic-model-selector:
model-categories:
- equation-of-state
- activity-coefficient
- specialized
data-sources:
- DECHEMA
- NIST
- DIPPR
```
## Output Artifacts
- Model selection reports
- Parameter fitting results
- Validation comparisons
- Uncertainty assessmentsRelated Skills
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