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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

An interpretable machine-learning-driven tool (HyWEC) for hydrogen wettability estimation: Implications for underground hydrogen storage

2025International Journal of Hydrogen EnergyJournal

10.1016/j.ijhydene.2025.150256 Full text7 citations

Authors

7 authors across 4 institutions in 4 countries.

Joshua N. TurksonFirst authorCorresponding
as printed: Joshua Nsiah Turkson
Muhammad Aslam Md YusofCorresponding
Victor Darkwah-Owusu
Yen Adams Sokama‐Neuyam
- Kwame Nkrumah University of Science and Technology (GH)
as printed: Yen Adams Sokama-Neuyam
Ingebret Fjelde
Fahd Saeed Alakbari
Bennet Nii Tackie-OtooSenior author

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Enhanced Oil Recovery Techniqueslevel 3 · 1.00
CO2 Sequestration and Geologic Interactionslevel 3 · 1.00
Hydraulic Fracturing and Reservoir Analysislevel 3 · 0.99

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 5, 2026
2025 · International Journal of Hydrogen Energy · 7 citations
https://openalex.org/W4412428854

An interpretable machine-learning-driven tool (HyWEC) for hydrogen wettability estimation: Implications for underground hydrogen storage · Sankore