Thermal Decomposition of Date Seed/Polypropylene Homopolymer: Machine Learning CDNN, Kinetics, and Thermodynamics.

ABSTRACT: The buildup of abandoned plastics in the environment and the need to optimize agricultural waste utilization have garnered scrutiny from environmental organizations and policymakers globally. This study presents an assessment of the thermal decomposition of date seeds (DS), polypropylene homopolymer (PP), and their composites (DS/PP) through experimental measurements, machine learning convolutional deep neural networks (CDNN), and kinetic and thermodynamic analyses. The experimental measurements involved the pyrolysis and co-pyrolysis of these materials in a nitrogen-filled thermogravimetric analyzer (TGA), investigating degradation temperatures between 25 and 600 °C with heating rates of 10, 20, and 40 °C.min^-1. These measurements revealed a two-stage process for the bio-compos

SUBMITTER: Albin Zaid ZAA 

PROVIDER: S-EPMC11820839 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature