Arghya Bhowmik
- Electrical and Electronic Engineering top 5%
- Materials Chemistry top 5%
- Automotive Engineering top 2%
- Renewable Energy, Sustainability and the Environment top 5%
- Catalysis top 5%
- Co-authors
- Tejs VeggeRongshan QinPeter Bjørn JørgensenOle WintherHeine Anton HansenJ. M. García‐LastraJaysree PanUmesh V. Waghmare
- Topics
- Machine Learning in Materials Science (25 papers)Advancements in Battery Materials (23 papers)Advanced Battery Materials and Technologies (18 papers)
In The Last Decade
Arghya Bhowmik
66 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Electrical and Electronic Engineering 1.0k
- Materials Chemistry 1.0k
- Automotive Engineering 410
- Renewable Energy, Sustainability and the Environment 338
- Catalysis 243
Countries citing papers authored by Arghya Bhowmik
This map shows the geographic impact of Arghya Bhowmik'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 Arghya Bhowmik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arghya Bhowmik more than expected).
Fields of papers citing papers by Arghya Bhowmik
This network shows the impact of papers produced by Arghya Bhowmik. 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 Arghya Bhowmik. The network helps show where Arghya Bhowmik may publish in the future.
Co-authorship network of co-authors of Arghya Bhowmik
This figure shows the co-authorship network connecting the top 25 collaborators of Arghya Bhowmik. A scholar is included among the top collaborators of Arghya Bhowmik based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Arghya Bhowmik. Arghya Bhowmik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | 10 | |
| 10 | 6 | |
| 11 | 26 | |
| 12 | 7 | |
| 13 | 7 | |
| 14 | 68 | |
| 15 | Automatic migration path exploration for multivalent battery cathodes using geometrical descriptors | 15 |
| 16 | 6 | |
| 17 | 16 | |
| 18 | 1 | |
| 19 | Artificial Intelligence Applied to Battery Research: Hype or Reality?breakdown → | 339 |
| 20 | 18 |
About Arghya Bhowmik
Arghya Bhowmik is a scholar working on Catalysis, Automotive Engineering and Materials Chemistry, having authored 73 papers that have together received 2.0k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (25 papers), Advancements in Battery Materials (23 papers) and Advanced Battery Materials and Technologies (18 papers). The work is most often cited by research in Catalysis (243 citations), Automotive Engineering (410 citations) and Materials Chemistry (1.0k citations). Arghya Bhowmik has collaborated with scholars based in Denmark, India and Germany. Frequent co-authors include Tejs Vegge, Rongshan Qin, Peter Bjørn Jørgensen, Ole Winther, Heine Anton Hansen, J. M. García‐Lastra, Jaysree Pan, Umesh V. Waghmare, Elixabete Ayerbe and Ivano E. Castelli. Their work appears in journals such as Chemical Reviews, Journal of the American Chemical Society and Physical Review Letters.
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.