| name | kinetic-modeler |
| description | Reaction kinetics modeling skill for parameter estimation, mechanism validation, and rate equation development |
| allowed-tools | ["Read","Write","Glob","Grep","Edit","Bash"] |
| metadata | {"specialization":"chemical-engineering","domain":"science","category":"Reaction Engineering","skill-id":"CE-SK-006"} |
| graph | {"domains":["domain:chemical-engineering"],"skillAreas":["skill-area:mathematical-reasoning","skill-area:physics-simulation","skill-area:statistical-analysis"],"workflows":["workflow:experiment-design"],"roles":["role:research-scientist","role:computational-scientist"]} |
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
