The Bioenergy Potential of Date Palm Branch/Waste Through Reaction Modeling, Thermokinetic Data, Machine Learning KNN Analysis, and Techno-Economic Assessments (TEA)

This research assesses the bioenergy potential of date palm branch (DPB) waste, aligning with Saudi Arabia's Vision 2030 energy and environmental goals. The study uses reaction modeling, thermokinetics, a k-nearest neighbors (KNN) machine learning approach, and techno-economic assessments. Experimental characterizations employing FTIR, SEM, and both proximate and ultimate analysis of pulverized DPB biomass reveal its lignocellulosic nature and compositional characteristics. Thermogravimetric analysis (TGA) of the material, tested between 25 and 1000 °C at heating rates of 7.5 to 60 °C per minute, revealed that the main thermal breakdown occurred from 200 to 530 °C, and was caused by the decomposition of hemicellulose and cellulose. Criado master plot analysis of the material's thermal decomposition indicated the R3 contracting cylinder model was the most suitable reaction mechanism. The Jander [D3] and Ginstling-Brounshtein [D4] diffusion models were also good fits. The kinetic analysis showed that various model-free approaches, including FWO, KAS, STK, and FR, yielded comparable activation energy values for the hemicellulose and cellulose components, with the results clustering between approximately 98.43 and 109.30 kJ/mol. The application of the KNN machine learning technique in this study yielded accurate predictions (R2~0.975) of the TGA traces following rigorous modeling that involved hyperparameter optimization and testing of the trained model on 20% unseen data. Through a global sensitivity analysis, the degradation temperature for DPB's thermal devolatilization was identified as the key parameter controlling the pyrolysis process. The techno-economic assessments of the pyrolysis operation indicate that it is a viable, financially rewarding, and environmentally friendly process, offering valuable insights for policymakers, environmental engineers, and energy professionals toward promoting sustainable waste management and a circular economy.

Authors

Institutions

Publication Details

Journal
Polymers
Published
2025-11-29
DOI
https://doi.org/10.3390/polym17233182
Citations
2
Primary Topic
Thermochemical Biomass Conversion Processes
Type
article
Field-Weighted Citation Impact
1.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Bioenergy Potential of Date Palm Branch/Waste Through Reaction Modeling, Thermokinetic Data, Machine Learning KNN Analysis, and Techno-Economic Assessments (TEA)

Abdulrazak Jinadu Otaru, Abdullah A. AlShuaibi, Zaid Abdulhamid Alhulaybi Albin Zaid, Saud Mahmood Alholiby Albin Zaid et al.
2 citations
Polymers
Thermochemical Biomass Conversion Processes
1.35
article

The Bioenergy Potential of Date Palm Branch/Waste Through Reaction Modeling, Thermokinetic Data, Machine Learning KNN Analysis, and Techno-Economic Assessments (TEA)

Abdulrazak Jinadu Otaru, Abdullah A. AlShuaibi, Zaid Abdulhamid Alhulaybi Albin Zaid, Saud Mahmood Alholiby Albin Zaid, Mubarak Mohammed Alkhaldi
article en
2 citations

Abstract

This research assesses the bioenergy potential of date palm branch (DPB) waste, aligning with Saudi Arabia's Vision 2030 energy and environmental goals. The study uses reaction modeling, thermokinetics, a k-nearest neighbors (KNN) machine learning approach, and techno-economic assessments. Experimental characterizations employing FTIR, SEM, and both proximate and ultimate analysis of pulverized DPB biomass reveal its lignocellulosic nature and compositional characteristics. Thermogravimetric analysis (TGA) of the material, tested between 25 and 1000 °C at heating rates of 7.5 to 60 °C per minute, revealed that the main thermal breakdown occurred from 200 to 530 °C, and was caused by the decomposition of hemicellulose and cellulose. Criado master plot analysis of the material's thermal decomposition indicated the R3 contracting cylinder model was the most suitable reaction mechanism. The Jander [D3] and Ginstling-Brounshtein [D4] diffusion models were also good fits. The kinetic analysis showed that various model-free approaches, including FWO, KAS, STK, and FR, yielded comparable activation energy values for the hemicellulose and cellulose components, with the results clustering between approximately 98.43 and 109.30 kJ/mol. The application of the KNN machine learning technique in this study yielded accurate predictions (R2~0.975) of the TGA traces following rigorous modeling that involved hyperparameter optimization and testing of the trained model on 20% unseen data. Through a global sensitivity analysis, the degradation temperature for DPB's thermal devolatilization was identified as the key parameter controlling the pyrolysis process. The techno-economic assessments of the pyrolysis operation indicate that it is a viable, financially rewarding, and environmentally friendly process, offering valuable insights for policymakers, environmental engineers, and energy professionals toward promoting sustainable waste management and a circular economy.

PolymersVol. 17(23)
Cornell University (US), King Faisal University (SA)
Openalex Percentile: Top 17%
Thermochemical Biomass Conversion Processes
1.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.