Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes

doi:10.1016/j.energy.2021.123041

GIEC OpenIR

	Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes
	Huang, Youwang 1,3,4; Wang, Haiyong 1,3,4; Zhang, Xinghua2 ; Zhang, Qi2 ; Wang, Chenguang 1,3,4; Ma, Longlong2
	2022-03-15
发表期刊	ENERGY
ISSN	0360-5442
卷号	243 页码:12
通讯作者	Ma, Longlong(mall@ms.giec.ac.cn)
摘要	The exergy-based assessment on the sustainable utilization processes of technical lignin is important for potential identify and process optimization. In this study, chemical exergy of technical lignin was evaluated for the first time based on the Gibbs free energy relation. The chemical exergy of technical lignin was from 17653.89 to 33337.92 kJ kg(-1).The effects of O/C and H/C ratios on the chemical exergy and standard entropy were investigated by using contour plot analysis. The chemical exergy of technical lignin is more significantly influenced by the O/C ratio, compared with the H/C ratio. Three types of prediction models including artificial neural network model with the input of elemental composition, HHV-based correlation, and element-based correlation were developed. The artificial neural network model has an excellent performance of predicting the chemical exergy of technical lignin, with the prediction relative error of less than +/- 0.15% under the confidential level of 97%. The prediction relative errors of the HHV-based correlation and the element-based correlation are within +/- 1.0% and +/- 2.5%, respectively. This work will provide the basic data for exergy-based assessment on the valorization processes of technical lignin, which is an important aspect of improving the economic level of biorefinery industry. (C) 2021 Elsevier Ltd. All rights reserved.
关键词	Technical lignin Chemical exergy Standard entropy Prediction model Artificial intelligence technique
DOI	10.1016/j.energy.2021.123041
关键词[WOS]	REDUCTIVE CATALYTIC FRACTIONATION ; FAST PYROLYSIS ; BIOMASS PYROLYSIS ; NEURAL-NETWORK ; GASEOUS FUELS ; LIQUID ; CONVERSION ; MODEL ; COMBUSTION ; OXIDATION
收录类别	SCI
语种	英语
WOS研究方向	Thermodynamics ; Energy & Fuels
WOS类目	Thermodynamics ; Energy & Fuels
WOS记录号	WOS:000789317300012
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.giec.ac.cn/handle/344007/36362
专题	中国科学院广州能源研究所
通讯作者	Ma, Longlong
作者单位	1.Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou 510640, Peoples R China 2.Southeast Univ, Sch Energy & Environm, Key Lab Energy Thermal Convers & Control, Minist Educ, Nanjing 210096, Peoples R China 3.CAS Key Lab Renewable Energy, Guangzhou 510640, Peoples R China 4.Guangdong Key Lab New & Renewable Energy Res & De, Guangzhou 510640, Peoples R China
第一作者单位	中国科学院广州能源研究所
推荐引用方式 GB/T 7714	Huang, Youwang,Wang, Haiyong,Zhang, Xinghua,et al. Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes[J]. ENERGY,2022,243:12.
APA	Huang, Youwang,Wang, Haiyong,Zhang, Xinghua,Zhang, Qi,Wang, Chenguang,&Ma, Longlong.(2022).Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes.ENERGY,243,12.
MLA	Huang, Youwang,et al."Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes".ENERGY 243(2022):12.