# Thermodynamic Model Selector

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

- Skill: `a5c-ai/thermodynamic-model-selector` (Agent Skill)
- Install (CLI): `npx skillmds@latest add a5c-ai/thermodynamic-model-selector`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/thermodynamic-model-selector/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Web & Frontend
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/thermodynamic-model-selector

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# 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

