Effects of phospholipids on pyrolysis and oxidation characteristics of Jatropha biodiesel: TG-FTIR-MS experiment and ReaxFF-MD simulation

被引:0
|
作者
Zhou, Li [1 ,2 ,3 ]
Li, Fashe [1 ,2 ,3 ]
Wang, Wenchao [1 ,2 ,3 ]
Zhang, Huicong [1 ,2 ,3 ]
Duan, Yaozong [1 ,2 ,3 ]
Wang, Hua [1 ,2 ,3 ]
机构
[1] Kunming Univ Sci & Technol, Yunnan Prov Key Lab Clean Energy & Energy Storage, Kunming 650093, Yunnan, Peoples R China
[2] Kunming Univ Sci & Technol, State Key Lab Complex Nonferrous Met Resources Cle, Kunming 650093, Yunnan, Peoples R China
[3] Kunming Univ Sci & Technol, Fac Met & Energy Engn, Kunming 650093, Yunnan, Peoples R China
关键词
Biodiesel; Phospholipid; Pyrolysis; Oxidation; Gaseous product; REACTIVE FORCE-FIELD; CURCAS; OIL; PERFORMANCE; PARAMETERS; COMBUSTION;
D O I
10.1016/j.fuel.2024.133816
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Phospholipids, as key trace constituents of biodiesel, can have complex effects on the performance of biodiesel. Exploring the mechanism of their influence on the pyrolysis and oxidation characteristics of biodiesel is crucial for controlling the generation and emission of pollutants. To this end, this study employed TG-FTIR-MS experimental technology and the ReaxFF-MD simulation method to investigate the effects of phosphatidylethanolamine (PE) on the activation energy (Ea), gaseous product generation, and mechanism of Jatropha biodiesel pyrolysis and oxidation reactions. The results indicated that the addition of 400 ppm PE can reduce the pyrolysis Ea of Jatropha biodiesel from 87.25 kJ/mol to 80.67 kJ/mol, consistent with simulated Ea of 93.35 kJ/mol and 81.81 kJ/mol, respectively. This notably promoted the initial oxidation stage of the Jatropha biodiesel reaction, facilitating the generation of oxidation products such as CO and C2H4. In the pyrolysis reaction, PE promoted C2H4 formation, primarily through reactions involving hydrocarbon small free radicals. In the oxidation reaction, the addition of PE increased the number and variety of active free radicals in the system, with the formation reactions of H2O and CH2O involving phosphorus-containing oxygen groups. Furthermore, a small amount of nitrogenous free radicals participates in the formation reactions of C2H4 and CO.
引用
收藏
页数:15
相关论文
共 20 条
  • [11] Insight into the pyrolysis of 3,7-dinitro-1,3,5,7-tetraazabicyclo [3,3,1] nonan (DPT) based on ReaxFF MD simulations and TG-FTIR-MS techniques
    Duan, Xiaoli
    Jin, Guoliang
    Zhang, Luyao
    Xu, Zishuai
    Zhang, Ruxin
    Wang, Jianlong
    FUEL, 2023, 331
  • [12] Pyrolysis kinetics and characteristics of waste tyres: Products distribution and optimization via TG-FTIR-MS and rapid infrared heating techniques
    Zeng, Yongfu
    Liu, Zuohua
    Yu, Jianglong
    Hu, Erfeng
    Jia, Xin
    Tian, Yishui
    Wang, Chao
    CHEMICAL ENGINEERING JOURNAL, 2024, 482
  • [13] Insight into gaseous product distribution of cross-linked polyethylene pyrolysis using ReaxFF MD simulation and TG-MS
    Kong, Jiamin
    Zhou, Kai
    Ren, Xiancheng
    Chen, Yidong
    Li, Yuan
    Meng, Pengfei
    JOURNAL OF ANALYTICAL AND APPLIED PYROLYSIS, 2023, 169
  • [14] Co-pyrolysis of sewage sludge and rice husk by TG-FTIR-MS: Pyrolysis behavior, kinetics, and condensable/non-condensable gases characteristics
    Wang, Chengxin
    Bi, Haobo
    Lin, Qizhao
    Jiang, Xuedan
    Jiang, Chunlong
    RENEWABLE ENERGY, 2020, 160 (1048-1066) : 1048 - 1066
  • [15] Synergistic effects of wood fiber and polylactic acid during co-pyrolysis using TG-FTIR-MS and Py-GC/MS
    Sun, Ce
    Li, Changxin
    Tan, Haiyan
    Zhang, Yanhua
    ENERGY CONVERSION AND MANAGEMENT, 2019, 202
  • [16] The effect of biomass addition on pyrolysis characteristics and gas emission of coal gangue by multi-component reaction model and TG-FTIR-MS
    Bi, Haobo
    Ni, Zhanshi
    Tian, Junjian
    Wang, Chengxin
    Jiang, Chunlong
    Zhou, Wenliang
    Bao, Lin
    Sun, Hao
    Lin, Qizhao
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 798
  • [17] Co-pyrolysis of coal slime and cattle manure by TG-FTIR-MS and artificial neural network modeling: Pyrolysis behavior, kinetics, gas emission characteristics
    Jiang, Chunlong
    Zhou, Wenliang
    Bi, Haobo
    Ni, Zhanshi
    Sun, Hao
    Lin, Qizhao
    ENERGY, 2022, 247
  • [18] TG-FTIR-MS study of synergistic effects during co-pyrolysis of corn stalk and high-density polyethylene (HDPE)
    Kai, Xingping
    Yang, Tianhua
    Shen, Shengqiang
    Li, Rundong
    ENERGY CONVERSION AND MANAGEMENT, 2019, 181 : 202 - 213
  • [19] Enhanced energy efficiency and fast co-pyrolysis characteristics of biogas residues and long-flame coal using infrared heating and TG-FTIR-MS
    Zeng, Yongfu
    Liu, Zuohua
    Yu, Jianglong
    Hu, Erfeng
    Li, Shuai
    Jia, Xin
    Tian, Yishui
    Wang, Chao
    PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2024, 189 : 414 - 424
  • [20] Kinetic characteristics and reactive behaviors of HSW vitrinite coal pyrolysis: A comprehensive analysis based on TG-MS experiments, kinetics models and ReaxFF MD simulations
    Bai, Hongcun
    Mao, Ning
    Wang, Ruihan
    Li, Zhuangmei
    Zhu, Meilin
    Wang, Qiang
    ENERGY REPORTS, 2021, 7 : 1416 - 1435