Innovative Research Award
Jeslin Jebish G P — Scott Christian College (Autonomous), Nagercoil, India
| Jeslin Jebish G P | |
|---|---|
| Affiliation | Scott Christian College, Nagercoil |
| Country | India |
| Google Scholar | IUCgka8AAAAJ |
| Documents | 8 |
| Citations | 6 |
| h-index | 1 |
| Subject Area | Machine Learning on Databases |
| Event | International Database Scientist Awards |
| Scopus | 59938914400 |
Jeslin Jebish G P is an early-career Physics researcher associated with Scott Christian College, Nagercoil, whose work spans nanotechnology, functional materials, photocatalysis, photoelectrochemical water splitting, hydrogen generation, and renewable-energy systems. His documented academic record includes a submitted Ph.D. thesis, indexed publications, conference presentations, peer-review activity, faculty development, and interdisciplinary research involving computational and machine-learning approaches to materials discovery.
Abstract
Jeslin Jebish G P is a Physics researcher whose documented work focuses on titania nanotubes, nanostructured functional materials, photocatalysis, photoelectrochemical water splitting, and green hydrogen generation. His research record also includes work connecting density functional theory and machine learning with materials discovery, providing an interdisciplinary basis for considering computational approaches within emerging energy-materials research. [1]
Keywords
Machine Learning on Databases; materials discovery; nanotechnology; TiO₂ nanotubes; photocatalysis; photoelectrochemical water splitting; green hydrogen; renewable energy; functional materials; electrochemical analysis; computational materials science; scientific data analysis; sustainable energy.
Introduction
The research profile of Jeslin Jebish G P is situated primarily within experimental Physics and materials-energy research. His academic activities encompass synthesis, characterization, electrochemical evaluation, photocatalytic testing, and scientific data interpretation. The supplied record further identifies an emerging computational dimension through research on artificial intelligence, machine learning, and materials discovery for renewable-energy applications. [4]
Research Profile
Jeslin Jebish G P pursued doctoral research at Manonmaniam Sundaranar University, Tirunelveli, with Scott Christian College, Nagercoil, on the development and analysis of titania enhanced with reactive non-metals and transition metals for energy applications. His research experience covers TiO₂ nanotube synthesis by electrochemical anodisation, dopant engineering, hydrogen evolution, photocatalytic and photoelectrochemical evaluation, and advanced material characterization. [1]
Research Contributions
The research profile focuses on engineering TiO₂ nanotube architectures for solar-driven hydrogen production, examining structure, composition, photocatalytic activity, and electrochemical performance. Related research explores nitrogen and transition-metal doping, heterostructures, seawater splitting, and computational materials discovery, demonstrating an interdisciplinary trajectory connecting experimental nanomaterials research with emerging data-driven methodologies for sustainable energy applications. [2]
Publications
The supplied publication record contains eight scholarly works addressing titania nanotubes, anodisation, solar-driven water splitting, green hydrogen generation, photocatalytic systems, seawater splitting, and machine-learning-assisted materials discovery. The publications indicate a progression from experimental nanostructure fabrication and characterization toward broader computational and interdisciplinary approaches in energy-materials research. [2] [3] [4]
Research Impact
The available scholarly record documents publications, presentations, peer-review activity, professional development, and research training across materials physics and renewable-energy themes. His work on TiO₂ nanotube architectures and hydrogen generation contributes to the broader research landscape of sustainable energy materials, while machine-learning-oriented materials discovery represents an emerging interdisciplinary direction. [1] [2]
Award Suitability
For the Innovative Research Award, the record demonstrates interdisciplinary research across nanostructured materials, hydrogen energy, photocatalysis, electrochemical methods, scientific data analysis, and emerging machine-learning approaches to materials discovery. The documented publications and research activities support consideration for recognition, while alignment with database-focused research should be assessed according to the award’s formal criteria. [4]
Conclusion
Jeslin Jebish G P presents an early-career research profile centered on functional nanomaterials, photocatalysis, photoelectrochemical water splitting, and green hydrogen generation. His publication record additionally identifies machine learning and computational materials discovery as an emerging interdisciplinary direction. Collectively, these activities demonstrate sustained engagement with experimental and data-informed research in advanced energy materials. [1]
External Links
References
- Google Scholar. (n.d.). Jeslin Jebish G P — Google Scholar profile. https://scholar.google.com/citations?hl=en&user=IUCgka8AAAAJ
- GP, J. J., & Jebin, R. P. (2026). Designing titania nanotube architectures through anodization for high-performance green hydrogen generation. Next Materials, 11, Article 101840. https://doi.org/10.1016/j.nxmate.2026.101840
- Jebish, J. J. G. P. (2026). Junction-engineered TiO₂ nanotube photocatalysts for efficient solar hydrogen generation: Doping strategies, structure–activity relationships, and future perspectives. Journal of Materials Science: Materials in Energy, 2(1), Article 14. https://link.springer.com/article/10.1007/s44308-026-00024-3
- Jeslin Jebish, G. P., & Jebin, R. P. (n.d.). Advances in titania nanotubes development by anodization and their role in solar-driven water splitting. Journal of Advanced Manufacturing and Processing, 7(3), Article e70005. https://doi.org/10.1002/amp2.70005