Rajesh Jha
- Mechanical Engineering top 10%
- Heat Transfer and Optimization 4
- Astronomy and Astrophysics top 10%
- Astro and Planetary Science 6
- Solar and Space Plasma Dynamics 4
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- Magnetic Properties and Applications 4
- General Materials Science top 10%
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- Machine Learning in Materials Science 5
- Microstructure and mechanical properties 4
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- Aluminum Alloy Microstructure Properties 7
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- Geological and Geochemical Analysis 3
- Co-authors
- George S. DulikravichNirupam ChakrabortiJ. N. GoswamiD. LalFan MinJ. SchwartzR. C. ReedyR. E. McGuire
- Partner nations
- United StatesIndiaBrazil
In The Last Decade
Rajesh Jha
35 papers receiving 505 citations
Peers
Comparison fields: 5 of 61
- Mechanical Engineering 244
- Astronomy and Astrophysics 88
- Electronic, Optical and Magnetic Materials 82
- General Materials Science 12
- Materials Chemistry 171
Countries citing papers authored by Rajesh Jha
This map shows the geographic impact of Rajesh Jha's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rajesh Jha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rajesh Jha more than expected).
Fields of papers citing papers by Rajesh Jha
This network shows the impact of papers produced by Rajesh Jha. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rajesh Jha. The network helps show where Rajesh Jha may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rajesh Jha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | 2022 | 1 | |
| 4 | 2022 | 10 | |
| 5 | 2021 | 1 | |
| 6 | 2020 | 11 | |
| 7 | 2019 | 8 | |
| 8 | Optimal Mean Radius and Volume Fraction of the Nanocrsytalline Phase in Softmagnetic Alloys: A Combined Machine Learning and Calphad Approach | 2017 | 1 |
| 9 | 2016 | 27 | |
| 10 | 2016 | 29 | |
| 11 | 2015 | 6 | |
| 12 | Multi-objective design and optimization of hard magnetic alloys free of rare earths | 2015 | 3 |
| 13 | 2014 | 35 | |
| 14 | 2012 | 8 | |
| 15 | 2005 | 7 | |
| 16 | TL and Nuclear Track Studies in Shergotty and Other SNC Meteorites | 1985 | 5 |
| 17 | 1984 | 1 | |
| 18 | 1984 | 27 | |
| 19 | Secular variations in solar flare proton fluxes | 1983 | 1 |
| 20 | Solar flare particle fluences during solar cycles 19, 20 and 21 | 1983 | 3 |
About Rajesh Jha
Rajesh Jha is a scholar working on Mechanical Engineering, Astronomy and Astrophysics and Metals and Alloys, having authored 37 papers that have together received 527 indexed citations. Recurring topics across this work include Aluminum Alloy Microstructure Properties (7 papers), Astro and Planetary Science (6 papers), Machine Learning in Materials Science (5 papers), Heat Transfer and Optimization (4 papers), Microstructure and mechanical properties (4 papers), Solar and Space Plasma Dynamics (4 papers), Magnetic Properties and Applications (4 papers) and Geological and Geochemical Analysis (3 papers). The work is most often cited by research in Mechanical Engineering (244 citations), Astronomy and Astrophysics (88 citations) and Electronic, Optical and Magnetic Materials (82 citations). Rajesh Jha has collaborated with scholars based in United States, India and Brazil. Frequent co-authors include George S. Dulikravich, Nirupam Chakraborti, J. N. Goswami, D. Lal, Fan Min, J. Schwartz, R. C. Reedy, R. E. McGuire, C.C. Koch and Y. Liu.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.