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kinetic-modeler

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Reaction kinetics modeling skill for parameter estimation, mechanism validation, and rate equation development

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How to use this skill

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Source SKILL.md: https://github.com/a5c-ai/babysitter/blob/HEAD/library/specializations/domains/science/chemical-engineering/skills/kinetic-modeler/SKILL.md

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Kinetic Modeler Skill

Purpose

The Kinetic Modeler Skill develops and validates reaction kinetics models, performing parameter estimation from experimental data and supporting reactor design.

Capabilities

  • Rate equation formulation (power law, LHHW, Eley-Rideal)
  • Parameter estimation via nonlinear regression
  • Arrhenius parameter calculation
  • Activation energy determination
  • Model discrimination (AIC, BIC criteria)
  • Confidence interval estimation
  • Reaction mechanism validation
  • Kinetic data analysis

Usage Guidelines

When to Use

  • Developing kinetic models
  • Estimating rate parameters
  • Validating reaction mechanisms
  • Supporting reactor design

Prerequisites

  • Experimental data available
  • Proposed mechanism identified
  • Operating conditions characterized
  • Thermodynamic constraints known

Best Practices

  • Use statistically valid data
  • Test multiple model forms
  • Validate with independent data
  • Report parameter uncertainties

Process Integration

This skill integrates with:

  • Kinetic Model Development
  • Reactor Design and Selection
  • Catalyst Evaluation and Optimization

Configuration

kinetic-modeler:
  model-types:
    - power-law
    - langmuir-hinshelwood
    - eley-rideal
    - mechanistic
  estimation-methods:
    - least-squares
    - maximum-likelihood
    - bayesian

Output Artifacts

  • Kinetic models
  • Parameter estimates
  • Confidence intervals
  • Model validation reports
  • Mechanism analysis