营养物
生物量(生态学)
生物燃料
热解
藻类生质燃料
产量(工程)
生物能源
制浆造纸工业
藻类
化学
植物
生物柴油
食品科学
农学
生物
生物技术
材料科学
有机化学
工程类
冶金
催化作用
作者
Sherif Ishola Mustapha,Usman Aliyu Mohammed,Ismail Rawat,Faizal Bux,Yusuf Makarfi Isa
出处
期刊:Fuel
[Elsevier]
日期:2023-01-01
卷期号:332: 126299-126299
被引量:5
标识
DOI:10.1016/j.fuel.2022.126299
摘要
Nutrient alteration as a tool for enhancement of yields and quality of bio-oils produced from thermal conversion of microalgae has not received sufficient attention. To better understand the effect of nutrient stressing on the process, pyrolysis experiments were conducted on unstressed S. obliquus microalgae (N3), nutrient-stressed S. obliquus microalgae (N1) and its residual algae after lipid extraction (R-N1) at different temperatures (400 °C to 700 °C) and the results compared. The biomass characterization results indicated that nutrient stressed conditions altered the microalgae biomass composition and the empirical formula for N1, R-N1, and N3 microalgae biomass were CH2.00N0.07O0.71, CH2.36N0.08O0.75, and CH2.35N0.14O0.71, respectively. The maximum yield of bio-oil for N1 (46.37 wt%) and R-N1 (34.85 wt%) was obtained at 500 °C, while the highest yield of bio-oil for N3 (41.94 wt%) was obtained at 600 °C. Also, the proportion of nitrogen compounds in N3 bio-oil (47.4 %) was significantly higher than that obtained in the nutrient-stressed microalgae biomass (N1) bio-oil (5.92 %) at a pyrolysis temperature of 500 °C. Thus, the nutrient-stressed approach is considered promising to produce good-quality pyrolytic bio-oil from microalgae biomass. A predictive model was developed based on an artificial neural network (ANN) and can serve as a framework for bio-oil yield prediction.
科研通智能强力驱动
Strongly Powered by AbleSci AI