Nitrogen heterocycles in bio-oil produced from hydrothermal liquefaction of biomass: A review

被引:34
作者
Leng, Lijian [1 ]
Zhou, Junhui [1 ]
Li, Tanghao [1 ]
Vlaskin, Mikhail [3 ]
Zhan, Hao [1 ]
Peng, Haoyi [1 ]
Huang, Huajun [2 ]
Li, Hailong [1 ]
机构
[1] Cent South Univ, Sch Energy Sci & Engn, Changsha 410083, Peoples R China
[2] Jiangxi Agr Univ, Sch Land Resources & Environm, Nanchang 330045, Jiangxi, Peoples R China
[3] Russian Acad Sci, Joint Inst High Temp, Moscow 125412, Russia
基金
中国国家自然科学基金;
关键词
Nitrogen heterocyclic compounds; Hydro -thermal liquefaction; Protein -rich biomass; Maillard reaction; Bio-oil; Aqueous phase; WATER TREATMENT SYSTEM; CULTURE ALGAL BIOMASS; SEWAGE-SLUDGE; THERMOCHEMICAL LIQUEFACTION; LIGNOCELLULOSIC BIOMASS; AMINO-ACIDS; MICROALGAE; MODEL; CONVERSION; PYROLYSIS;
D O I
10.1016/j.fuel.2022.126995
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
Hydrothermal liquefaction (HTL) of nitrogen-rich biomass (N-B) is a promising valorization technology. How-ever, nitrogen heterocycles (N-H, mainly 5-/6-membered) was produced considerably in bio-oil during HTL of N-B, impeding the application of bio-oil as a fuel due to NOx emission, and the use of bio-oil containing N-H as chemical precursors is not yet satisfactory due to relative low content and selectivity. This study aims to overview the effects of biomass and HTL processing parameters on N-H distribution and transformation mechanisms of N-H during HTL of N-B. It was found that factors influencing the formation of N-H are mainly biomass composition (particularly the compositions of amino acids and monosaccharides), HTL process parameters such as temperature, and extraction conditions such as solvents and procedures. Maillard reaction between amino acids and monosaccharides as well as the chain scission, dimerization, and cyclization of amino acids are the major paths to form N-H. Strategies in engineering biomass feedstock, HTL process, and bio-oil extraction procedure, in addition to optimizing N-H analysis and N-H classification, were proposed to promote the development of this area. Amongst, the use of machine learning-aided prediction, optimization, and regulation of N-H formation reactions is promising.
引用
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页数:14
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