Summary of the Webinar
How to Choose the Most Suitable Kinetic Model in Kinetics Neo

Core Workflow and Data Requirements

Kinetic analysis requires multiple measurements (minimum 3 heating rates) with identical initial and final values. The workflow involves: 

1. importing measured data 
2. baseline correction 
3. calculating degree of conversion (α, normalized 0-1) 
4. building kinetic models 
5. validation 
6. prediction/simulation for process optimization.​

The fundamental kinetic equation is:

dα/dt = A × exp(-E/RT) × f(α),

where A is the pre-exponential factor, E is activation energy, and f(α) represents the reaction model. The Kinetics Neo software supports both Arrhenius (standard exponential temperature dependence) and non-Arrhenius approaches (for crystallization with diffusion and nucleation terms).

Model-Free vs. Model-Based Approaches

Model-Free (Isoconversional) Methods

Model-free methods analyze points at the same conversion value across different heating rates, assuming reaction rate at fixed α depends only on temperature. They include:

• Single-point analysis: Uses only maximum points (e.g., Kissinger) or only points with given degree of conversion (e.g. ASTM 1641); provides single activation energy value
• Multi-point analysis (Friedman, Ozawa, Numerical): Analyzes all data points; provides E(α) function

Key limitation: These methods provide only one activation energy value at each point. For overlapping or competing reactions, they cannot separate individual step energies—only an averaged intermediate value.

Model-free methods are only applicable when:

• single-step reactions with constant activation energy (±5-10% variation),
• same final effect across all curves,
• no overlapping mechanisms.

Model-Based (Model-Fitting) Methods

Model-based approaches fit multiple kinetic equations simultaneously to the entire dataset. Each reaction step has constant activation energy, pre-exponential factor, and specific reaction model f(α). The total measured signal equals the sum of individual steps.

Advantages

• Handles parallel, consecutive, and competing reactions
• Works with highly overlapping steps
• Supports various Reaction typesReaction type is the elementary mechanism of one individual reaction step in multi-step chemical reaction. Reaction type f(Cr, Cp) describes dependence of the reaction rate for individual reaction step on the concentrations of reactant Cr and product Cp for this step.reaction types (n-th order, autocatalytic, nucleation, diffusion)
• Enables both Arrhenius and non-Arrhenius temperature dependencies
• Allows predictions beyond experimental conditions

Decision Framework: When to Use Each Method

The webinar provides a critical checklist—if any answer is "yes," then model-free is inapplicable and model-based must be used:

1. Is the reaction incompletely measured? (Unknown final value, no α=1 across all curves)
2. Does peak area/mass loss vary >20% with heating rate? Indicates competing steps
3. Are there peaks in opposite directions? (Endothermic/exothermic mix causing negative α)
4. Does mechanism change at different α values across curves?
5. Is this a mixture with parallel independent reactions?
6. Is diffusion control present? (E.g., epoxy curing with vitrification/glass transition during reaction)
7. Is this crystallization?
   • Isothermal near melting point → Model-free acceptable (Arrhenius)
   • Cooling between Tg and Tm → Model-based required (non-Arrhenius, Hoffman-Lauritzen)
8. Are intermediate reactants important? (E.g., optimizing A→B→C to maximize B concentration)

Selecting Reaction Types

Reaction type selection depends on process characteristics and curve shape analysis via Friedman plots (comparing experimental curve slopes to isoconversional line slopes at reaction start):

Process-Specific Recommendations

• Decomposition/Degradation/Pyrolysis: n-th order (n = 0.5–2), phase boundary (n = 0.3–0.7)
• Curing: Start with n-th order + 1st-order autocatalysis; add complexity only if simple models fail
• Crystallization:
  • Isothermal: Avrami-Erofeev (An)
  • Cooling/non-Arrhenius: Crystallization According to NakamuraCrystallization according to Nakamura is the crystal growth model for non-isothermal crystallization kinetics during cooling.Nakamura or Spherulitic (Spherulitic preferred—better fit according to software testing)

Building Multi-Step Models

For complex reactions, determine:

Number of Steps: Must correspond to physical peaks/shoulders in data (avoid overfitting—don't create 20-step models for 2 observed peaks)

Step Structure:

• Single component è Consecutive reactions (A→B→C)
• Mixture of independent components è Parallel/independent steps
• Competing pathways è Competing structure (A→B, B→C or B→D)

Validation Technique

Compare dynamic vs. isothermal measurements. If activation energies maintain the same order, reactions are consecutive. If order reverses (e.g., 50 kJ/mol then 100 kJ/mol in dynamic becomes 100 kJ/mol then 50 kJ/mol in isothermal), reactions are parallel.

The Kinetics Neo software enables visual model construction—users can add/delete/replace steps as consecutive, competing, or independent without writing equations. F-test statistical comparison helps select the minimal model that adequately describes the data.

Representative Examples from Pre-Installed Kinetics Neo Samples

The webinar demonstrated several real-world cases which are included in samples delivered together with Kinetics Neo software:

• Calcium carbonate decomposition (TG): Single-step model-free analysis
• Epoxy curing (DSC/DEA): Autocatalytic with diffusion control after vitrification; requires model-based approach to account for glass transition during reaction
• Alpha-glucose decomposition (TG): Competing pathways (A→B, B→C/D) due to heating-rate-dependent final mass loss
• Lanthanum hydroxide decomposition: Two-step; model-free integral methods fail on final portions due to cumulative integration effects
• PET crystallization (cooling): Non-Arrhenius model between glass transition and melting temperature
• Multi-peak DSC with opposite directions: Consecutive endothermic-exothermic steps

Critical Warnings for Industrial Applications

The presenter emphasized that improper use of model-free methods for complex systems is "very dangerous" for industrial applications and safety calculations, as predictions outside experimental conditions become unreliable. Model-based approaches provide the necessary rigor for:

• Process optimization (e.g., maximizing intermediate concentrations in A→B→C reactions)
• Safety condition calculations
• Temperature control strategies
• Material behavior simulation

Kinetics Neo Software Capabilities

The software implements all ICTAC (International Confederation for Thermal Analysis and Calorimetry) committee recommendations:

• Data handling: All thermal techniques; automatic α calculation; ability to assume final values for incomplete reactions
• Analysis engines: Complete model-free suite (all ICTAC methods) plus advanced model-based with visual builder
• Advanced features:
  • Non-Arrhenius approaches for crystallization
  • Diffusion control and vitrification modeling
  • F-test model comparison
  • Numerical optimization method (enhanced Friedman with better R²)
• Output: E(α) curves, fitted curves, individual step contributions, concentration vs. temperature/time profiles
• Predictions: Isothermal/dynamic simulations and process optimization tools
• Resources: User guides, step-by-step training examples, webinar library, 30-day trial version

Practical Implementation Recommendations

1. Pre-analysis check: Verify ≥3 curves with same initial/final values; plot DTG/derivative curves to count peaks/shoulders
2. Initial screening: Run model-free (Friedman/Numerical) first—if E is constant (±5-10%) with good fit, single-step suffices
3. Multi-step modeling:
   • Number of steps = number of observable peaks/shoulders
   • Test component structure via isothermal/dynamic comparison
   • Start with simplest reaction type, add complexity only if needed
4. Validation: Check R² values, physical reasonability of parameters (constant E per step), and prediction accuracy
5. Avoid: Over-parameterization, using model-free for predictions in complex systems, ignoring glass transition in curing reactions

The webinar concludes that while model-free methods offer quick insights for simple systems, model-based approaches provide the reliability essential for industrial process optimization and safety-critical applications. The Kinetics Neo software simplifies complex modeling through its visual interface while maintaining scientific rigor through ICTAC-compliant methodologies.