应用分布式活化能模型预测木质纤维素生物质水热炭化动力学

Suprio Kamal, Md. Shahriar Hossain, Ishmamul Hoque Sadab, Kazi Bayzid Kabir, Kawnish Kirtania
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引用次数: 0

摘要

水热碳化(HTC)已被确定为从高水分有机样品(如生物质)生产生物燃料的最有前途的技术之一。然而,在这一过程的动力学建模方面观察到的进展有限。由于该过程中涉及的非等温和等温后续步骤的性质,现有的动力学模型涉及机械和实验缺陷。为了解决这些局限性,应用分布式活化能模型(DAEM)预测木质纤维素生物质的HTC动力学。DAEM考虑了反应器的非等温温度分布,以解释在加热的瞬态步骤期间发生的相当大的脱挥发分。制作了一个微动力学反应器,以便于动力学实验来估计DAEM参数——平均活化能、标准偏差和指数前因子。基于木质纤维素生物质在190°C和210°C的最终HTC温度下的实验,发现这些参数分别为96.03 kJ mol−1、3 kJ mol–1和5×108 s−1。此外,使用190°C和210°C下的估计参数,这些参数用于准确预测230°C下HTC动力学。所获得的结果将为木质纤维素生物质HTC的反应器设计和大规模模拟提供有价值的输入。
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Application of distributed activation energy model to predict hydrothermal carbonization kinetics of lignocellulosic biomass

Hydrothermal carbonization (HTC) has been established as one of the most promising techniques for producing biofuels from high moisture containing organic samples such as, biomass. However, limited progress is observed in terms of the kinetic modeling of this process. Existing kinetic models involve mechanistic and experimental shortcomings due to the nature of the non-isothermal and isothermal subsequent steps involved in the process. To address these limitations, a distributed activation energy model (DAEM) was applied to predict HTC kinetics of lignocellulosic biomass. The DAEM considered the non-isothermal temperature profile of the reactor to account for the considerable devolatilization taking place during the transient step of heating. A micro-kinetic reactor was fabricated to facilitate kinetic experiments to estimate the DAEM parameters- mean activation energy, standard deviation, and pre-exponential factor. These parameters were found to be 96.03 kJ mol−1, 3 kJ mol−1, and 5 × 108 s  1 respectively, based on experiments at final HTC temperatures of 190 °C and 210 °C for lignocellulosic biomass. Furthermore, the parameters were used to accurately predict HTC kinetics at 230 °C using the estimated parameters at 190 °C and 210 °C. The obtained results would be valuable inputs for reactor design and large-scale simulations for HTC of lignocellulosic biomass.

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