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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.

Predicting fouling resistance in spiral-wound ultrafiltration membranes: a machine learning approach for high-recovery wastewater treatment

2026Chemical Engineering CommunicationsJournal

10.1080/00986445.2025.2611396 Full text2 citations

Authors

10 authors across 4 institutions in 4 countries.

Kamil Kayode KatibiFirst authorCorresponding
Kamil Kayode KatibiFirst authorCorresponding
Kamil Kayode KatibiFirst authorCorresponding
Arun Kumar Shukla
Ibrahim Garba Shitu
- Sule Lamido University Kafin Hausa (NG)
Khalid M. Alotaibi
Ahamad Imran
Ahamad Imran
Ahamad Imran
Rukayat Afolake OladipupoSenior author

Fields

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

Membrane Separation Technologieslevel 3 · 0.96
Membrane-based Ion Separation Techniqueslevel 3 · 0.01
Wastewater Treatment and Nitrogen Removallevel 3 · 0.00

Sources

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

openalexseen September 9, 2026
2026 · Chemical Engineering Communications · 2 citations
https://openalex.org/W7118161921

Predicting fouling resistance in spiral-wound ultrafiltration membranes: a machine learning approach for high-recovery wastewater treatment · Sankore