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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.

Prediction of mechanical properties of Newboulia laevis particulate composite material using artificial neural network (ANN)

2025Modelling and Simulation in Materials Science and EngineeringJournalOpen access

10.1088/1361-651x/ae4f05 Full text0 citations

Authors

5 authors across 3 institutions in 1 country.

Peter Okechukwu ChikeluFirst author
- Nnamdi Azikiwe University (NG)
S. C. Nwigbo
- Nnamdi Azikiwe University (NG)
as printed: Solomon Chuka Nwigbo
Raphael Emeka Ozioko
- Enugu State University of Science and Technology (NG)
Christian Emeka Okafor
- Nnamdi Azikiwe University (NG)
Leo Aganyi MorgaSenior author
- University of Calabar (NG)

Fields

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

Natural Fiber Reinforced Compositeslevel 3 · 0.95
Material Selection and Propertieslevel 3 · 0.00
Mechanical Engineering and Vibrations Researchlevel 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
2025 · Modelling and Simulation in Materials Science and Engineering · 0 citations
https://openalex.org/W7134839449

Prediction of mechanical properties of Newboulia laevis particulate composite material using artificial neural network (ANN) · Sankore