用热重分析和人工神经网络研究脱油麻花饼与废LDPE共热解行为

IF 5.8 2区生物学 Q1 AGRICULTURAL ENGINEERING

Biomass & Bioenergy Pub Date : 2025-04-13 DOI:10.1016/j.biombioe.2025.107870

Kaumik Gandhi , Yash Jaiswal , Bhupendra Suryawanshi , Kantilal Chouhan , Hemant Kumar , Ajay Sharma

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引用次数: 0

摘要

生物质-塑料废物混合物的热解为可持续能源回收提供了一条有希望的途径，但潜在的动力学相互作用在很大程度上仍未被探索。采用热重分析（TGA）、无模型动力学建模和人工神经网络（ANN）预测方法研究了脱油麻花饼（DOMC）和废低密度聚乙烯（LDPE）的共热解行为。采用Flynn-Wall-Ozawa （FWO）、Kissinger-Akahira-Sunose （KAS）、Starink、Tang和Boswell方法进行的动力学分析显示，与DOMC混合后，LDPE的活化能（Ea）降低，表明协同效应提高了分解效率。人工神经网络模型显示出很高的预测精度（R2 ~ 1），有效地捕获了不同加热速率（5、10和20°C/min）下的热解行为。研究结果强调了共热解在减少塑料废物降解中的能量障碍方面的潜力，并强调了基于人工智能的预测建模在热解优化中的适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Co-pyrolysis behaviour of de-oiled mahua cake and waste LDPE using thermogravimetric analysis and artificial neural network

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Co-pyrolysis behaviour of de-oiled mahua cake and waste LDPE using thermogravimetric analysis and artificial neural network

Pyrolysis of biomass-plastic waste mixtures offers a promising pathway for sustainable energy recovery, yet the underlying kinetic interactions remain largely unexplored. This study investigates the co-pyrolysis behavior of de-oiled mahua cake (DOMC) and waste low-density polyethylene (LDPE) using thermogravimetric analysis (TGA), model-free kinetic modeling, and artificial neural network (ANN) prediction. Kinetic analysis using Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), Starink, Tang, and Boswell methods revealed a reduction in activation energy (E_a) for LDPE when mixed with DOMC, suggesting a synergistic effect that enhances decomposition efficiency. The ANN model demonstrated high predictive accuracy (R² ∼1), effectively capturing pyrolysis behavior across different heating rates (5, 10, and 20 °C/min). The findings highlight the potential of co-pyrolysis for reducing energy barriers in plastic waste degradation and underscore the applicability of AI-based predictive modeling for pyrolysis optimization.

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来源期刊

Biomass & Bioenergy 工程技术-能源与燃料

CiteScore

11.50

自引率

3.30%

发文量

258

审稿时长

60 days

期刊介绍： Biomass & Bioenergy is an international journal publishing original research papers and short communications, review articles and case studies on biological resources, chemical and biological processes, and biomass products for new renewable sources of energy and materials. The scope of the journal extends to the environmental, management and economic aspects of biomass and bioenergy. Key areas covered by the journal: • Biomass: sources, energy crop production processes, genetic improvements, composition. Please note that research on these biomass subjects must be linked directly to bioenergy generation. • Biological Residues: residues/rests from agricultural production, forestry and plantations (palm, sugar etc), processing industries, and municipal sources (MSW). Papers on the use of biomass residues through innovative processes/technological novelty and/or consideration of feedstock/system sustainability (or unsustainability) are welcomed. However waste treatment processes and pollution control or mitigation which are only tangentially related to bioenergy are not in the scope of the journal, as they are more suited to publications in the environmental arena. Papers that describe conventional waste streams (ie well described in existing literature) that do not empirically address ''new'' added value from the process are not suitable for submission to the journal. • Bioenergy Processes: fermentations, thermochemical conversions, liquid and gaseous fuels, and petrochemical substitutes • Bioenergy Utilization: direct combustion, gasification, electricity production, chemical processes, and by-product remediation • Biomass and the Environment: carbon cycle, the net energy efficiency of bioenergy systems, assessment of sustainability, and biodiversity issues.