Thermal degradation of carbohydrates, proteins and lipids in microalgae analyzed by evolutionary computation

被引:114
作者
Chen, Wei-Hsin [1 ,2 ]
Chu, Yen-Shih [1 ]
Liu, Jenn-Long [3 ]
Chang, Jo-Shu [2 ,4 ]
机构
[1] Natl Cheng Kung Univ, Dept Aeronaut & Astronaut, Tainan 701, Taiwan
[2] Natl Cheng Kung Univ, Res Ctr Energy Technol & Strategy, Tainan 701, Taiwan
[3] I Shou Univ, Dept Informat Management, Kaohsiung 840, Taiwan
[4] Natl Cheng Kung Univ, Dept Chem Engn, Tainan 701, Taiwan
关键词
Biomass and microalgae; Thermal degradation temperature; Pyrolysis; Particle swarm optimization (PSO); Evolutionary computation; TGA and kinetics; PARTICLE SWARM OPTIMIZATION; THERMOGRAVIMETRIC ANALYSIS; PYROLYSIS CHARACTERISTICS; BIOMASS PYROLYSIS; KINETIC-PARAMETERS; CO-PYROLYSIS; TORREFACTION; MODEL; TGA; CLASSIFICATION;
D O I
10.1016/j.enconman.2018.01.036
中图分类号
O414.1 [热力学];
学科分类号
摘要
The kinetics of microalgae pyrolysis is investigated to analyze the thermal degradation of carbohydrates, proteins and lipids in different species of microalgae. The pyrolysis processes of microalgae Chlorella vulgaris ESP-31, Nannochioropsis oceanica CY2, and Chlamydomonas sp. JSC4 are examined by thermogravimetric analysis (TGA), and independent parallel reaction (IPR) model is adopted to approach the pyrolysis kinetics. To maximize the fit quality between the established kinetic models and experimental data, particle swarm optimization (PSO), a kind of evolutionary computation, is employed. The thermal degradation characteristics of the three microalgal species are compared with each other. The results suggest that the thermal degradation curves of the three microalgae can be predicted with a fit quality of at least 97.9%. The activation energies of carbohydrates, proteins, and lipids in the microalgae are in the ranges of 53.28-53.30, 142.61-188.35, and 40.21-59.23 kJ mol(-1), respectively, while the thermal degradation of carbohydrates, proteins, and lipids are in temperature ranges of 164-497, 209-309, and 200-635 degrees C, respectively. It is proved in this work that the IPR model and the calculation of the PSO can be used to predict the pyrolysis kinetics of microalgae to a good level of fitness.
引用
收藏
页码:209 / 219
页数:11
相关论文
共 47 条
  • [21] A sectional approach for biomass: Modelling the pyrolysis of cellulose
    Lin, Tunei
    Goos, Elke
    Riedel, Uwe
    [J]. FUEL PROCESSING TECHNOLOGY, 2013, 115 : 246 - 253
  • [22] Evolutionary computation of unconstrained and constrained problems using a novel momentum-type particle swarm optimization
    Liu, Jenn-Long
    Lin, Jiann-Horng
    [J]. ENGINEERING OPTIMIZATION, 2007, 39 (03) : 287 - 305
  • [23] Pyrolysis of three different types of microalgae: Kinetic and evolved gas analysis
    Lopez-Gonzalez, D.
    Fernandez-Lopez, M.
    Valverde, J. L.
    Sanchez-Silva, L.
    [J]. ENERGY, 2014, 73 : 33 - 43
  • [24] Mediterranean agri-food processing wastes pyrolysis after pre-treatment and recovery of precursor materials: A TGA-based kinetic modeling study
    Manara, P.
    Vamvuka, D.
    Sfakiotakis, S.
    Vanderghem, C.
    Richel, A.
    Zabaniotou, A.
    [J]. FOOD RESEARCH INTERNATIONAL, 2015, 73 : 44 - 51
  • [25] Solution of optimal reactive power dispatch of power systems using hybrid particle swarm optimization and imperialist competitive algorithms
    Mehdinejad, Mehdi
    Mohammadi-Ivatloo, Behnam
    Dadashzadeh-Bonab, Reza
    Zare, Kazem
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2016, 83 : 104 - 116
  • [26] Microalgae biofuels as an alternative to fossil fuel for power generation
    Milano, Jassinnee
    Ong, Hwai Chyuan
    Masjuki, H. H.
    Chong, W. T.
    Lam, Man Kee
    Loh, Ping Kwan
    Vellayan, Viknes
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 58 : 180 - 197
  • [27] Improvement of EEG-based motor imagery classification using ring topology-based particle swarm optimization
    Mirvaziri, Hamid
    Mobarakeh, Zabihollah Saberi
    [J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2017, 32 : 69 - 75
  • [28] ATMOSPHERIC PYROLYSIS OF CARBOHYDRATES WITH THERMOGRAVIMETRIC AND MASS-SPECTROMETRIC ANALYSES
    PAVLATH, AE
    GREGORSKI, KS
    [J]. JOURNAL OF ANALYTICAL AND APPLIED PYROLYSIS, 1985, 8 (1-4) : 41 - 48
  • [29] Pyrolysis characteristics and kinetics of microalgae via thermogravimetric analysis (TGA): A state-of-the-art review
    Quang-Vu Bach
    Chen, Wei-Hsin
    [J]. BIORESOURCE TECHNOLOGY, 2017, 246 : 88 - 100
  • [30] Effects of wet torrefaction on reactivity and kinetics of wood under air combustion conditions
    Quang-Vu Bach
    Khanh-Quang Tran
    Skreiberg, Oyvind
    Khalil, Roger A.
    Phan, Anh N.
    [J]. FUEL, 2014, 137 : 375 - 383