Authors: Zaid Abdulhamid Alhulaybi Albin Zaid | Abdulrazak Jinadu Otaru
Source: Industrial Crops and Products (article, 2025-07-15)
Field: Materials Science — Materials Chemistry

Experimental measurements, convolutional deep neural networks, and thermo-kinetic analyses of the thermal decomposition of Phoenix dactylifera L./polylactic acid composites The study provides a thorough evaluation of the thermal decomposition of Phoenix dactylifera L. (PDL), polylactic acid (PLA), and their bio-composite (PDL/PLA), employing machine learning convolutional deep neural networks (CDNN) and analyzing the kinetics and thermodynamics of the process. The experimental measurement data used in this study were obtained from thermogravimetric analysis (TGA) of the samples at heating rates of 10, 20, and 40 °C·min⁻¹ , with degradation temperatures ranging from 25 to 600 °C. The experimentally measured data indicated that sample weight loss shifted to higher temperatures with increased heating rates and higher proportions of PLA plastic content. The application of the machine learning CDNN technique for analysing this process resulted in learning algorithms and arbitrary constants that effectively captured the thermal decomposition behaviour of the materials, achieving an accuracy of R² ∼ 0.99. A CDNN framework comprising eight hidden neurons was identified as the most effective architecture, significantly reducing the overall cost function during training from 47.37 to 0.48 and determining sample composition as the most influential operating parameter driving the thermal degradation process. The kinetic parameters of the process were estimated using the regular integral isoconversional kinetic methods, specifically the Flynn-Wall-Ozawa (FWO) and Kissinger-Akahira-Sunose (KAS) model-free kinetic approaches. The overall activation energies for the process, as estimated using the FWO and KAS kinetic methods, are 124.31 kJ·mol⁻¹ and 120.54 kJ·mol⁻¹ , respectively. Furthermore, the estimated values of activation enthalpy (105.62 – 135.97 kJ·mol⁻¹), Gibbs free energy of the activated complex (164.66 – 194.79 kJ·mol⁻¹), and entropy of activation (-0.13 to −0.09 kJ·mol⁻¹·K⁻¹) indicate that the formation of activated complexes from the reactants is characterized as endothermic, non-spontaneous, and associated with less disorder. This study aims to provide valuable insights to energy experts, environmental engineers, plastic manufacturers, and policymakers regarding the efficient utilization of Phoenix dactylifera L. to facilitate energy reduction in the thermal degradation of plastics. • A study on the thermal decomposition of Phoenix dactylifera L. and polylactic acid biocomposites. • The increasing proportion of PLA plastic content in the biocomposites resulted in an enhancement of thermal stability. • The application of convolutional DNN yielded predictions that remained within the boundaries of experimental variability. • The estimated activation energies FWO and KAS kinetic models are 124.31 kJ·mol⁻¹ and 120.54 kJ·mol⁻¹ , respectively. Polylactic acid ; Phoenix dactylifera ; Phoenix ; Thermal decomposition ; Composite material ; Decomposition ; Convolutional neural network ; Kinetic energy ; Materials science ; Pyrolysis ; Chemistry ; Computer science ; Palm ; Polymer ; Artificial intelligence ; Physics ; Organic chemistry Thermal and Kinetic Analysis ; Natural Fiber Reinforced Composites ; Thermochemical Biomass Conversion Processes