Thermal pyrolysis of wasted high-density plastic into valuable fuels using statistically derived kinetic rate constants

Hammad Hussain , Sonia Arshed , Shahbaz Nasir Khan , Sameera Haq Nawaz , Muhammad Yasin Naz , Rao Adeel Un Nabi
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Abstract

Experimentally, empirical rate constants are used to extract liquid fuels and gases from the thermal decomposition of high-density plastics (HDPs). However, this approach is costly, time-consuming, and not commercially viable for producing a sustainable volume of liquid fuel. The prediction of rate constants is, therefore, imperative to boost the efficiency of the scaled destruction of plastic waste into fuels and other valuable products. We used the Box-Behnken technique in response surface methodology (RSM) to forecast temperature-dependent rate constants for thermal destruction of HDP. Most appropriate combinations of activation energies (Ea), exponential factors (Ao) and rate constants (k) were predicted statistically for better insight into HDP reaction mechanism for commercial scale production of oils and gases. The predicted parameters were used in a 2nd order ordinary differential solver to simulate the amount of oil and gases. The thermal treatment of HDP under optimized conditions resulted in 99 % oil production after 240 min of reaction. The formation of heavy wax was observed at the start of the reaction, and it changed to oil, light wax, and gases after 1 hour of processing. After 2 h, light wax production declined and oil production increased over time.
利用统计导出的动力学速率常数将废弃高密度塑料热裂解成有价值的燃料
实验中,利用经验速率常数从高密度塑料(HDPs)的热分解中提取液体燃料和气体。然而,这种方法成本高,耗时长,而且在商业上不可行,无法生产出可持续数量的液体燃料。因此,速率常数的预测对于提高塑料垃圾转化为燃料和其他有价值产品的效率至关重要。我们使用响应面法(RSM)中的Box-Behnken技术来预测HDP热破坏的温度相关速率常数。对活化能(Ea)、指数因子(Ao)和速率常数(k)的最合适组合进行了统计预测,以便更好地了解HDP反应机理,用于商业规模的油气生产。将预测参数应用于二阶常微分求解器中,对油气量进行了数值模拟。在优化条件下对HDP进行热处理,反应240 min后原油采收率达到99%。在反应开始时观察到重蜡的形成,经过1小时的处理后变为油、轻蜡和气体。2 h后,随着时间的推移,轻蜡产量下降,原油产量增加。
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