Accurate prediction of chemical exergy of technical lignins for exergy-based assessment on sustainable utilization processes
文献类型：期刊论文
| 作者 | Huang, Youwang1,2,3; Wang, Haiyong1,2,3; Zhang, Xinghua4 ; Zhang, Qi4; Wang, Chenguang1,2,3; Ma, Longlong4
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| 刊名 | ENERGY
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| 出版日期 | 2022-03-15 |
| 卷号 | 243页码:12 |
| ISSN号 | 0360-5442 |
| 关键词 | Technical lignin Chemical exergy Standard entropy Prediction model Artificial intelligence technique |
| DOI | 10.1016/j.energy.2021.123041 |
| 通讯作者 | Ma, Longlong(mall@ms.giec.ac.cn) |
| 英文摘要 | 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. |
| WOS关键词 | REDUCTIVE CATALYTIC FRACTIONATION ; FAST PYROLYSIS ; BIOMASS PYROLYSIS ; NEURAL-NETWORK ; GASEOUS FUELS ; LIQUID ; CONVERSION ; MODEL ; COMBUSTION ; OXIDATION |
| WOS研究方向 | Thermodynamics ; Energy & Fuels |
| 语种 | 英语 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| WOS记录号 | WOS:000789317300012 |
| 源URL | [http://ir.giec.ac.cn/handle/344007/36361]  |
| 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.Guangdong Key Lab New & Renewable Energy Res & De, Guangzhou 510640, Peoples R China 2.Chinese Acad Sci, Guangzhou Inst Energy Convers, Guangzhou 510640, Peoples R China 3.CAS Key Lab Renewable Energy, Guangzhou 510640, Peoples R China 4.Southeast Univ, Sch Energy & Environm, Key Lab Energy Thermal Convers & Control, Minist Educ, Nanjing 210096, Peoples R China |
| 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. |
入库方式： OAI收割
来源：广州能源研究所
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