ArticlePolymers2025
The Bioenergy Potential of Date Palm Branch/Waste Through Reaction Modeling, Thermokinetic Data, Machine Learning KNN Analysis, and Techno-Economic Assessments (TEA).
Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Backpropagation DNN and Thermokinetic Analysis of the Thermal Devolatilization of Dried PulverizedPolymers · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.