Best Researcher Award
Chijioke Peter Egole
Federal University of Technology Owerri
| Chijioke Peter Egole |
| Affiliation |
Federal University of Technology Owerri |
| Country |
Nigeria |
| Scopus ID |
57213355410 |
| Documents |
18 |
| Citations |
61 |
| h-index |
5 |
| Subject Area |
Materials Science |
| Event |
Best Paper Awards |
| ORCID |
0000-0003-0797-6527 |
The Best Researcher Award profile recognizes the scholarly contributions and research engagement of Chijioke Peter Egole of the Federal University of Technology Owerri. The profile highlights publication activity, citation visibility, interdisciplinary relevance, and research performance indicators associated with contributions in Materials Science and related academic domains.[1]
Abstract
This academic recognition article presents a concise and structured overview of the scholarly profile of Chijioke Peter Egole of the Federal University of Technology Owerri. The evaluation highlights key academic indicators including publication output, citation performance, subject specialization, and sustained engagement in Materials Science research activities. The profile reflects documented scholarly contributions and participation in scientific communication through indexed publications and measurable research visibility. Consideration within the Best Researcher Award framework recognizes evidence of knowledge dissemination, academic productivity, and contribution to advancing scientific understanding while supporting broader objectives related to research excellence and scholarly development.
Keywords
Materials Science; Research Excellence; Academic Recognition; Citation Analysis; Scopus Profile; Research Evaluation; Scholarly Contributions; Publication Metrics
Introduction
Research awards are frequently used as institutional and professional mechanisms to recognize sustained scientific contributions and measurable academic outcomes. Such evaluations commonly incorporate publication activity, citation performance, and evidence of continuing scholarly engagement. Dr Egole’s profile aligns with these indicators through documented academic output and disciplinary participation.[2]
Research Profile
- Researcher: Chijioke Peter Egole
- Institution: Federal University of Technology Owerri
- Subject Focus: Materials Science
- Indexed Documents: 18
- Total Citations: 61
- h-index: 5
Research Contributions
Research contributions attributed to the profile demonstrate engagement with material characterization, scientific analysis methodologies, and publication dissemination practices within engineering and materials-related disciplines. The documented output indicates continuity in scholarly activity and participation in peer-reviewed communication channels.[3]
Publications
- Indexed publication portfolio represented through Scopus metrics.
- Citation accumulation reflecting scholarly reach.
Research Impact
Research impact indicators provide a quantitative and qualitative perspective on scholarly visibility. Citation activity and indexed documents demonstrate evidence of knowledge dissemination and contribute to evaluation frameworks commonly used across academic recognition programs.[1]
Award Suitability
Based on available academic indicators, the profile demonstrates characteristics typically considered during recognition processes including publication continuity, indexed research visibility, and measurable citation performance. Evaluation remains subject to formal award criteria and independent review procedures.[4]
Conclusion
This article provides a structured academic overview supporting consideration within a Best Researcher Award context. The profile illustrates research participation, scholarly output, and recognized bibliometric indicators relevant to academic assessment frameworks.
External Links
References
- Elsevier. (n.d.). Scopus author details: Dr Chijioke Peter Egole, Author ID 57213355410. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57213355410
- ORCID Registry. Research profile information.
https://orcid.org/0000-0003-0797-6527
-
High entropy alloys in electrocatalytic conversion and hydrogen energy storage: Machine learning-assisted prediction of intermediate reaction descriptors- A comprehensive review.
https://www.sciencedirect.com/science/article/abs/pii/S0360319926020914
-
Strength–ductility enhancement in high‑entropy alloys: Dislocation mechanisms and hybrid pathways — a comprehensive review.
https://www.sciencedirect.com/science/article/abs/pii/S0925838826002707
- Best Paper Awards. Award information and evaluation overview.
International Research Excellence and Best Paper Awards