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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.

Machine Learning Assisted Electrochemical Prediction of Corrosion Resistance in Additively Manufactured Ti6Al4V Biomaterials under Simulated Physiological Conditions

2026International Journal of Scientific Research in Mechanical and Materials EngineeringJournalOpen access

10.32628/ijsrmme261038 Full text0 citations

Authors

2 authors across 3 institutions in 3 countries.

Samuel Anane AkentenFirst author
- Kwame Nkrumah University (ZM)
- Kwame Nkrumah University of Science and Technology (GH)
Onuh Mathew IjigaSenior author
- Benue State University (NG)
as printed: Onuh Matthew Ijiga

Fields

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

Additive Manufacturing Materials and Processeslevel 3 · 0.88
Titanium Alloys Microstructure and Propertieslevel 3 · 0.07
Hydrogen embrittlement and corrosion behaviors in metalslevel 3 · 0.01

Sources

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

openalexseen September 9, 2026
2026 · International Journal of Scientific Research in Mechanical and Materials Engineering · 0 citations
https://openalex.org/W7162072854

Machine Learning Assisted Electrochemical Prediction of Corrosion Resistance in Additively Manufactured Ti6Al4V Biomaterials under Simulated Physiological Conditions · Sankore