Vasudev Vikul, Ku Xiaoke, Lin Jianzhong
Department of Engineering Mechanics, Zhejiang University, 310027 Hangzhou, China.
State Key Laboratory of Clean Energy Utilization, Zhejiang University, 310027 Hangzhou, China.
ACS Omega. 2021 Jul 14;6(29):19144-19152. doi: 10.1021/acsomega.1c02493. eCollection 2021 Jul 27.
In this work, the combustion performance of (CV), (DS), and (HP) algal biochars was analyzed based on the multicomponent method. The biochars were obtained via nonisothermal pyrolysis of raw algal biomasses at three different heating rates (i.e., 30, 40, and 50 °C/min), and biochar combustion was performed from 200 to 700 °C at a heating rate of 5 °C/min. The complex oxidative reaction of algal biochar was resolved into combined reactions of multiple pseudo-components based on the peak deconvolution method using a bi-Gaussian model. The activation energies ( ) for each pseudo-component (PC) of all biochar samples were calculated by the Coats-Redfern isoconversional method and four kinetic models (i.e., diffusion, nucleation, order-based, and shrinking core models). The results showed that the highest values were predicted by the diffusion model. Except that the for the first PC of CV biochar decreased by 16.45%, the values for all other biochar samples generally increased with increasing the pyrolysis heating rate. Moreover, when the diffusion model was used, the for the second PC of CV biochar increased by 50.87%, that for the first PC of DS biochar increased by 16.85%, and those for the first and third PCs of HP biochar increased by 4.66 and 11.66%, respectively. In addition, the combustibility index ( ) was evaluated based on the ignition and burnout temperatures as well as the mean and maximum weight loss rates. Generally, the combustion performance of all biochar samples was good at a low temperature but deteriorated toward a high temperature. As the pyrolysis heating rate increases, an overall increase in the combustion quality was also seen for the second PC of CV biochar and the first PCs of DS and HP biochars because their increased from 2.70 × 10 to 3.07 × 10 °C, 2.53 × 10 to 3.88 × 10 °C, and 3.00 × 10 to 3.26 × 10 °C, respectively.
在本研究中,基于多组分方法分析了(CV)、(DS)和(HP)藻类生物炭的燃烧性能。这些生物炭通过在三种不同加热速率(即30、40和50℃/分钟)下对原始藻类生物质进行非等温热解获得,生物炭燃烧在5℃/分钟的加热速率下从200℃至700℃进行。基于使用双高斯模型的峰去卷积方法,将藻类生物炭的复杂氧化反应分解为多个伪组分的组合反应。通过Coats-Redfern等转化率方法和四种动力学模型(即扩散、成核、基于级数和缩核模型)计算了所有生物炭样品各伪组分(PC)的活化能()。结果表明,扩散模型预测的活化能值最高。除CV生物炭第一伪组分的活化能降低了16.45%外,所有其他生物炭样品的活化能值一般随热解加热速率的增加而增加。此外,当使用扩散模型时,CV生物炭第二伪组分的活化能增加了50.87%,DS生物炭第一伪组分的活化能增加了16.85%,HP生物炭第一和第三伪组分的活化能分别增加了4.66%和11.66%。此外,基于着火温度和 burnout 温度以及平均和最大失重率评估了燃烧指数()。一般来说,所有生物炭样品在低温下的燃烧性能良好,但在高温下会变差。随着热解加热速率的增加,CV生物炭第二伪组分以及DS和HP生物炭第一伪组分的燃烧质量总体上也有所提高,因为它们的活化能分别从2.70×10至3.07×10℃、2.53×10至3.88×10℃和3.00×10至3.26×10℃增加。