kinetic-modeler

# 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 ```yaml 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