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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 volume loss of reinforced polytetrafluoroethylene matrix composites using machine learning algorithms

2024AIP conference proceedingsPublication

10.1063/5.0229592 Full text0 citations

Authors

6 authors across 2 institutions in 2 countries.

Musa Adeku IbrahimFirst authorCorresponding
- Kano State University of Technology (NG)
as printed: M. A. Ibrahim
Auwalu Yusuf Gidado
- Kano State University of Technology (NG)
as printed: A. Y. Gidado
S. T. Auwal
- Kano State University of Technology (NG)
B. I. Kunya
- Kano State University of Technology (NG)
M. Nura
- Kano State University of Technology (NG)
L. JacquelineSenior author

Fields

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

Material Properties and Applicationslevel 3 · 1.00
Dielectric materials and actuatorslevel 3 · 0.99
Polymer Nanocomposites and Propertieslevel 3 · 0.99

Sources

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

openalexseen September 9, 2026
2024 · AIP conference proceedings · 0 citations
https://openalex.org/W4402043220

Prediction of volume loss of reinforced polytetrafluoroethylene matrix composites using machine learning algorithms · Sankore