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Microfluidic investigation on CO2 self-storage behavior in submarine sediment using artificial intelligence image recognition

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成果类型:
期刊论文
作者:
Zhong, Jinrong*;Luo, Zuozhi;Zhu, Yaxuan;Sun, Yifei;Sun, Changyu;...
通讯作者:
Zhong, Jinrong;Zhang, YF
作者机构:
[Zhu, Yaxuan; Zhang, Yue-Fei; Zhong, Jinrong; Luo, Zuozhi] Changsha Univ Sci & Technol, Sch Chem & Pharmaceut Engn, Hunan Prov Key Lab Mat Protect Elect Power & Trans, Changsha 410114, Peoples R China.
[Sun, Yifei; Sun, Changyu; Chen, Guangjin] China Univ Petr, Coll Chem Engn & Environm, Beijing 102249, Peoples R China.
[Yin, Zhenyuan] Tsinghua Univ, Inst Ocean Engn, Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China.
[Huang, Zhuo] Peoples Bank China, Shaanxi Prov Branch, Xian 710075, Peoples R China.
通讯机构:
[Zhong, JR; Zhang, YF ] C
Changsha Univ Sci & Technol, Sch Chem & Pharmaceut Engn, Hunan Prov Key Lab Mat Protect Elect Power & Trans, Changsha 410114, Peoples R China.
语种:
英文
关键词:
Microfluidic chip;AI-Based image recognition;Hydrate cap;Seal capacity optimization;CO2 marine geological storage
期刊:
Energy
ISSN:
0360-5442
年:
2025
卷:
337
页码:
138587
基金类别:
CRediT authorship contribution statement Jinrong Zhong: Writing – review & editing, Supervision, Software, acquisition, Formal analysis, Data curation, Conceptualization. Zuozhi Luo: Writing – original draft, Software, Investigation. Yaxuan Zhu: Software, Resources, Investigation. Yifei Sun: Methodology, Conceptualization. Changyu Sun: Methodology, Conceptualization. Zhenyuan Yin: Validation. Zhuo Huang: Software, Resources. Yue-Fei Zhang: Supervision, Resources. Guangjin Chen: Supervision, Methodology, Conceptualization.
机构署名:
本校为第一且通讯机构
院系归属:
化学与生物工程学院
摘要:
Current research on CO 2 storage technologies predominantly focused on core-scale experiments, which overlooked the effect of intricate pore structure and multiphase fluid behaviors at the pore scale. This study investigated CO 2 self-storage behavior using an integrated microfluidics platform combined with CCD imaging and in situ Raman spectroscopy. An artificial intelligence image recognition model was developed and trained on over 1000 annotated images to enhance image analysis. Experiments were conducted in both homogeneous and heterogeneou...

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