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.

Machine learning-accelerated inverse design of energy materials: A critical review of graph neural networks, physics-informed models, and generative AI for batteries, perovskite solar cells, and electrocatalysts

2026Next MaterialsJournalOpen access

10.1016/j.nxmate.2026.102969 Full text0 citations

Authors

2 authors across 2 institutions in 1 country.

Ignatius Echezona EkengwuFirst authorCorresponding
- Nnamdi Azikiwe University (NG)
Bonaventure Onyeka EkengwuSenior author
- University of Nigeria (NG)

Fields

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

Machine Learning in Materials Sciencelevel 3 · 0.99
Perovskite Materials and Applicationslevel 3 · 0.00
Model Reduction and Neural Networkslevel 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 · Next Materials · 0 citations
https://openalex.org/W7171773090

Machine learning-accelerated inverse design of energy materials: A critical review of graph neural networks, physics-informed models, and generative AI for batteries, perovskite solar cells, and electrocatalysts · Sankore