Advanced generalized machine learning models for predicting hydrogen–brine interfacial tension in underground hydrogen storage systems
Abstract The global transition to clean energy has highlighted hydrogen (H2) as a sustainable fuel, with underground hydrogen storage (UHS) in geological formations emerging as a key solution. Accurately predicting fluid interactions, particularly interfacial tension (IFT), is critical for ensuring...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-02304-4 |
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