thermodynamic-model-selector

Automated thermodynamic property method selection based on component characteristics and operating conditions

509 stars

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

$curl -o ~/.claude/skills/thermodynamic-model-selector/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/chemical-engineering/skills/thermodynamic-model-selector/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/thermodynamic-model-selector/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How thermodynamic-model-selector Compares

Feature / Agentthermodynamic-model-selectorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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 assessments

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