Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration
Effectively storing carbon dioxide (CO 2) in geological formations synergizes with algal-
based removal technology, enhancing carbon capture efficiency, leveraging biological …
based removal technology, enhancing carbon capture efficiency, leveraging biological …
Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration
Z Tariq, M Ali, A Hassanpouryouzband, B Yan… - …, 2023 - research.ed.ac.uk
Effectively storing carbon dioxide (CO 2) in geological formations synergizes with algal-
based removal technology, enhancing carbon capture efficiency, leveraging biological …
based removal technology, enhancing carbon capture efficiency, leveraging biological …
Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration
Z Tariq, M Ali, A Hassanpouryouzband, B Yan, S Sun… - 2023 - repository.kaust.edu.sa
Effectively storing carbon dioxide (CO2) in geological formations synergizes with algal-
based removal technology, enhancing carbon capture efficiency, leveraging biological …
based removal technology, enhancing carbon capture efficiency, leveraging biological …
Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration
Z Tariq, M Ali, A Hassanpouryouzband, B Yan… - …, 2023 - ui.adsabs.harvard.edu
Effectively storing carbon dioxide (CO 2) in geological formations synergizes with algal-
based removal technology, enhancing carbon capture efficiency, leveraging biological …
based removal technology, enhancing carbon capture efficiency, leveraging biological …
Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration.
Z Tariq, M Ali, A Hassanpouryouzband, B Yan… - …, 2023 - europepmc.org
Effectively storing carbon dioxide (CO 2) in geological formations synergizes with algal-
based removal technology, enhancing carbon capture efficiency, leveraging biological …
based removal technology, enhancing carbon capture efficiency, leveraging biological …
Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration
Z Tariq, M Ali, A Hassanpouryouzband… - …, 2023 - pubmed.ncbi.nlm.nih.gov
Effectively storing carbon dioxide (CO 2) in geological formations synergizes with algal-
based removal technology, enhancing carbon capture efficiency, leveraging biological …
based removal technology, enhancing carbon capture efficiency, leveraging biological …
Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration
Z Tariq, M Ali, A Hassanpouryouzband, B Yan, S Sun… - 2023 - repository.kaust.edu.sa
Effectively storing carbon dioxide (CO2) in geological formations synergizes with algal-
based removal technology, enhancing carbon capture efficiency, leveraging biological …
based removal technology, enhancing carbon capture efficiency, leveraging biological …
[引用][C] Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling: Implications for carbon geo-sequestration
Z Tariq, M Ali, A Hassanpouryouzband, B Yan… - …, 2023 - ui.adsabs.harvard.edu
Predicting wettability of mineral/CO2/brine systems via data-driven machine learning modeling:
Implications for carbon geo-sequestration - NASA/ADS Now on home page ads icon ads Enable …
Implications for carbon geo-sequestration - NASA/ADS Now on home page ads icon ads Enable …