Countries
Institutions
Fields
Rankings
Compare

Search institutions, scholars, countries and publications

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.

Built from

OpenAlex — works, authorships, subject classification
ROR — institutional identity
ORCID — researcher identity
Crossref — publisher confirmation

Browse

Countries
Institutions
Fields
Rankings
What we cover

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 density and surface roughness in LPBF-printed parts from recycled SS316L powder using random forest regression model

2026UiTM Institutional Repositories (Universiti Teknologi MARA)JournalOpen access

10.24191/jaeds.v6i1.167 Full text0 citations

Authors

5 authors across 5 institutions in 3 countries.

Yusuf Olanrewaju BusariFirst author
- University of Ilorin (NG)
as printed: Busari, Yusuf Olanrewaju
Abdunkarim Yakoh, Muhammad Asmadi
Abubakar, Mansir
- Al-Qalam University Katsina (NG)
Adel Mohammed Al‐Dhahebi
as printed: Al-Dhahebi, Adel Mohammed
Ajibike Joan FarounbiSenior author
as printed: Farounbi, Ajibike Joan

Fields

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

Additive Manufacturing Materials and Processeslevel 3 · 0.98
Additive Manufacturing and 3D Printing Technologieslevel 3 · 0.00
High-Temperature Coating Behaviorslevel 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 · UiTM Institutional Repositories (Universiti Teknologi MARA) · 0 citations
https://openalex.org/W7162067636

Prediction of density and surface roughness in LPBF-printed parts from recycled SS316L powder using random forest regression model · Sankore