## 4 Conclusions  
ANN models, which offer valuable insights into the kinetics of complex, nonlinear systems, were found to yield predicted kinetic parameters that closely align with experimentally determined values, indicating strong predictive performance when properly optimized and well trained. Notably, the models accurately captured trends in activation energy, pre-exponential factors, the kinetic compensation effect, and thermodynamic parameters--including enthalpy, entropy, and Gibbs free energy. Furthermore, the Friedman, FWO, KAS, and Starink models displayed similar activation energy trends across conversion degrees, reinforcing the notion that the carbonization of chitosan and chitin follows a consistent kinetic pathway that is effectively mirrored by ANN predictions. Chitosan's average activation energy ranged from 128.1 to 152.2 kJ/mol, while chitin's was higher (157.3 to 160.0 kJ/mol) due to stronger intermolecular interactions from higher acetylation. In the final stage, chitosan's activation energy decreased due to char formation and polymer breakdown, whereas chitin's increased due to cross-linking and char stabilization. Fluctuations in activation energy suggest a complex, temperature-dependent degradation process for both materials. Experimental \(\Delta\)H values for chitosan (155.2 kJ/mol) and chitin (154.6 kJ/mol) confirmed the endothermic nature of carbonization, with ANN predictions closely aligned but slightly lower. chitin exhibited higher \(\Delta\)G (183.7 kJ/mol) than chitosan (168.2 kJ/mol), indicating greater thermal stability due to its crystallinity and strong hydrogen bonding. Both materials showed negative \(\Delta\)S, with chitin's more negative value (\(-42.9\) J/mol\(\cdot\)K vs. \(-22.7\) J/mol\(\cdot\)K) suggesting greater structural reorganization. ANN predictions accurately captured average thermodynamic trends but showed minor deviations in instantaneous values. Morpho-structural analysis of carbonaceous products at different carbonization temperatures revealed that surface morphology, degree of disorder, and surface functionality of the resulting chars were significantly influenced by both the precursor material and the carbonization temperature. The results of this study confirm that the integrated experimental methodology--combining thermo-kinetic analysis, thermodynamics and ANN modeling--is effective in providing valuable insights into the kinetic modeling of complex nonlinear systems. Consequently, the predictive capabilities of the ANN approach in both kinetics and thermodynamics contribute to a deeper understanding of the carbonization processes of chitin and chitosan. This improved understanding facilitates precise control over product characteristics, supports efficient scale-up and process optimization, and enhances resource utilization, ultimately enabling more cost-effective processing. The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/app15116141/s1](https://www.mdpi.com/article/10.3390/app15116141/s1)]([https://www.mdpi.com/article/10.3390/app15116141/s1](https://www.mdpi.com/article/10.3390/app15116141/s1)), Figure S1: SEM-EDX analyses of chitosan and chitin chars obtained at different temperature levels. **Author Contributions**: Conceptualization, M.A.T. and G.O. ; data curation, M.A.T. and G.O. ; methodology, M.A.T. and G.O. ; software, M.A.T. ; writing-- original draft, M.A.T. and G.O. ; writing--review and editing, M.A.T. and G.O. All authors have read and agreed to the published version of the manuscript. **Funding**: Bilecik Seyh Edebali University Scientific Research Projects (No: 2022-02.BSEC.03-02). **Institutional Review Board Statement**: Not applicable. **Informed Consent Statement**: Not applicable. **Data Availability Statement**: Part of the data are contained within the article and Supplementary Materials. Further inquiries can be directed to the corresponding author.