中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Volume change of CO2 + long-chain liquid n-alkane (with n ≥ 14) mixtures under geological storage conditions: An observed abrupt change near the critical point of CO2

文献类型:期刊论文

作者Bei, Ke3,4,5; Wang, Youyan3,5; Yang, Dan3,5; Shao, Qizhi3,5; Zheng, Xiangyong3,5; Zhao, Min3,5; Chou, I. -Ming2; Kikuchi, Jun4; Pan, Zhiyan1
刊名JOURNAL OF MOLECULAR LIQUIDS
出版日期2024-11-01
卷号413页码:8
关键词Volume expansion High pressure optical cell Machine learning Raman spectroscopy Supercritical fluid CO2 + long-chain alkane
ISSN号0167-7322
DOI10.1016/j.molliq.2024.125827
英文摘要This study used a high pressure optical cell (HPOC) combined with a heating/cooling stage, a pressure device, and a laser Raman spectrometer to investigate the volume expansion (VE) of CO2 + tetradecane and CO2 + hexadecane mixtures under geological storage conditions. Abrupt changes in VE were observed near the CO2 critical point (CP), which is assumed to be ubiquitous in CO2 + long-chain alkane mixtures with >= 14 carbon alkanes. This is due to the critical anomaly of the thermodynamic behavior of the mixture near the CP of CO2, which inhibits the VE of CO2 + long-chain alkanes at lower temperatures. In addition, four machine learning (ML) algorithms, including backpropagation neural network (BPNN), K-nearest neighbors (KNN), random forest (RF), and support vector regression (SVR), were applied to predict the volume expansion factor (VEF). The BPNN model provided much higher robustness and accuracy with correlation coefficient (R-2) >0.98 and mean square error (MSE) <0.03, which indicates a strong agreement between the predicted result and matching experimental data. We concluded that a predictive framework built using ML could provide rapid predictions of the volume change curve or curved surface of CO2 + organic mixtures under various temperature and pressure conditions.
WOS关键词SITU RAMAN-SPECTROSCOPY ; PHASE-EQUILIBRIA ; DISSOLUTION MECHANISM ; DISPERSION PROPERTY ; AQUEOUS-SOLUTIONS ; IMPROVED MODEL ; EXPANSION ; SOLUBILITY ; PREDICTION ; WATER
资助项目Zhejiang Provincial Natural Science Foundation of China[LQ22D030001] ; National Key Research and Development Program of China[2019YFE0117200] ; National Natural Science Foundation of China[42130109] ; JSPS Postdoctoral Fellowship for Research in Japan[P22718] ; Japan Society for the Promotion of Science
WOS研究方向Chemistry ; Physics
语种英语
WOS记录号WOS:001310893000001
出版者ELSEVIER
资助机构Zhejiang Provincial Natural Science Foundation of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; JSPS Postdoctoral Fellowship for Research in Japan ; Japan Society for the Promotion of Science
源URL[http://ir.idsse.ac.cn/handle/183446/11374]  
专题深海科学研究部_深海极端环境模拟研究实验室
通讯作者Kikuchi, Jun; Pan, Zhiyan
作者单位1.Zhejiang Univ Technol, Dept Environm Engn, Hangzhou 310032, Peoples R China
2.Chinese Acad Sci, Inst Deep Sea Sci & Engn, CAS Key Lab Expt Study Deep Sea Extreme Condit, Sanya 572000, Peoples R China
3.Natl & Local Joint Engn Res Ctr Ecol Treatment Tec, Wenzhou 325035, Zhejiang, Peoples R China
4.RIKEN, Ctr Sustainable Resource Sci, 1-7-22 Tsurumi Ku, Yokohama 2300045, Japan
5.Wenzhou Univ, Coll Life & Environm Sci, Wenzhou 325035, Peoples R China
推荐引用方式
GB/T 7714
Bei, Ke,Wang, Youyan,Yang, Dan,et al. Volume change of CO2 + long-chain liquid n-alkane (with n ≥ 14) mixtures under geological storage conditions: An observed abrupt change near the critical point of CO2[J]. JOURNAL OF MOLECULAR LIQUIDS,2024,413:8.
APA Bei, Ke.,Wang, Youyan.,Yang, Dan.,Shao, Qizhi.,Zheng, Xiangyong.,...&Pan, Zhiyan.(2024).Volume change of CO2 + long-chain liquid n-alkane (with n ≥ 14) mixtures under geological storage conditions: An observed abrupt change near the critical point of CO2.JOURNAL OF MOLECULAR LIQUIDS,413,8.
MLA Bei, Ke,et al."Volume change of CO2 + long-chain liquid n-alkane (with n ≥ 14) mixtures under geological storage conditions: An observed abrupt change near the critical point of CO2".JOURNAL OF MOLECULAR LIQUIDS 413(2024):8.

入库方式: OAI收割

来源:深海科学与工程研究所

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