Pyrolysis of agricultural biomass is a promising technique for producing renewable energy and effectively managing solid waste. In this study, groundnut shell (GNS) was processed at 500 °C in an inert gas atmosphere with a gas flow rate and a heating rate of 10 mL/min and 10 °C/min, respectively, in a custom-designed fluidized bed pyrolytic-reactor. Under optimal operating conditions, the GNS-derived pyrolytic-oil yield was 62.8 wt.%, with the corresponding biochar (19.5 wt.%) and biogas yields (17.7 wt.%). The GC-MS analysis of the GNS-based bio-oil confirmed the presence of (trifluoromethyl)pyridin-2-amine (18.814%), 2-Fluoroformyl-3,3,4,4-tetrafluoro-1,2-oxazetidine (16.23%), 5,7-dimethyl-1H-Indazole (11.613%), N-methyl-N-nitropropan-2-amine (6.5%) and butyl piperidino sulfone (5.668%) as major components, which are used as building blocks in the biofuel, pharmaceutical, and food industries. Furthermore, a 2 × 5 × 1 artificial neural network (ANN) architecture was developed to predict the decomposition behavior of GNS at heating rates of 5, 10, and 20 °C/min, while the thermodynamic and kinetic parameters were estimated using a non-isothermal model-free method. The Popescu method predicted activation energy (E_a) of GNS biomass ranging from 111 kJ/mol to 260 kJ/mol, with changes in enthalpy (ΔH), Gibbs-free energy (ΔG), and entropy (ΔS) ranging from 106 to 254 kJ/mol, 162–241 kJ/mol, and −0.0937 to 0.0598 kJ/mol/K, respectively. The extraction of high-quality precursors from GNS pyrolysis was demonstrated in this study, as well as the usefulness of the ANN technique for thermogravimetric analysis of biomass.

农业生物质的热解是一种用于生产可再生能源和有效管理固体废物的有前途的技术。在这项研究中，花生壳 (GNS) 在 500 °C 的惰性气体气氛中进行处理，气体流速和加热速率分别为 10 mL/min 和 10 °C/min，在定制设计的流化床中热解反应器。在最佳操作条件下，GNS 衍生的热解油产量为 62.8 wt.%，相应的 biochar (19.5 wt.%) 和沼气产量 (17.7 wt.%)。基于 GNS 的生物油的 GC-MS 分析证实存在（三氟甲基）吡啶-2-胺（18.814%）、2-氟甲酰基-3,3,4,4-四氟-1,2-氧氮杂环丁烷（ 16.23%)、5,7-二甲基-1H-吲唑(11.613%)、N-甲基-N-硝基丙-2-胺(6.5%)和丁基哌啶基砜(5.668%)为主要成分，它们被用作生物燃料、制药和食品行业的积木。此外，还开发了一个 2 × 5 × 1 人工神经网络 (ANN) 架构来预测 GNS 在 5、10 和 20 °C/min 的加热速率下的分解行为，同时使用非-等温无模型方法。Popescu 方法预测活化能 (E_a ) GNS 生物量范围为 111 kJ/mol 至 260 kJ/mol，焓 (ΔH)、吉布斯自由能 (ΔG) 和熵 (ΔS) 的变化范围为 106 至 254 kJ/mol，162-241分别为 kJ/mol 和 -0.0937 至 0.0598 kJ/mol/K。本研究证明了从 GNS 热解中提取高质量前体，以及 ANN 技术在生物质热重分析中的有用性。