Aditya Nandy
- Materials Chemistry top 5%
- Inorganic Chemistry top 1%
- Computational Theory and Mathematics top 1%
- Renewable Energy, Sustainability and the Environment top 5%
- Catalysis top 5%
- Co-authors
- Heather J. KulikChenru DuanJon Paul JanetFang LiuMichael G. TaylorTzuhsiung YangSeyed Mohamad MoosaviBerend Smit
- Topics
- Machine Learning in Materials Science (33 papers)Computational Drug Discovery Methods (18 papers)Metal-Organic Frameworks: Synthesis and Applications (13 papers)
- Partner nations
- United StatesSwitzerlandItaly
In The Last Decade
Aditya Nandy
56 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Materials Chemistry 1.6k
- Inorganic Chemistry 855
- Computational Theory and Mathematics 462
- Renewable Energy, Sustainability and the Environment 312
- Catalysis 306
Countries citing papers authored by Aditya Nandy
This map shows the geographic impact of Aditya Nandy'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 Aditya Nandy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya Nandy more than expected).
Fields of papers citing papers by Aditya Nandy
This network shows the impact of papers produced by Aditya Nandy. 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 Aditya Nandy. The network helps show where Aditya Nandy may publish in the future.
Co-authorship network of co-authors of Aditya Nandy
This figure shows the co-authorship network connecting the top 25 collaborators of Aditya Nandy. A scholar is included among the top collaborators of Aditya Nandy 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 Aditya Nandy. Aditya Nandy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 56 | |
| 5 | 1 | |
| 6 | 25 | |
| 7 | 13 | |
| 8 | 21 | |
| 9 | 19 | |
| 10 | 4 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 31 | |
| 14 | 16 | |
| 15 | 12 | |
| 16 | 9 | |
| 17 | 92 | |
| 18 | Understanding the diversity of the metal-organic framework ecosystembreakdown → | 426 |
| 19 | 1 | |
| 20 | Stream Sediment and Soil Samples by Microwave Digestion Followed by ICP-MS Measurement | 2 |
About Aditya Nandy
Aditya Nandy is a scholar working on Catalysis, Inorganic Chemistry and Computational Theory and Mathematics, having authored 56 papers that have together received 2.2k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (33 papers), Computational Drug Discovery Methods (18 papers) and Metal-Organic Frameworks: Synthesis and Applications (13 papers). The work is most often cited by research in Inorganic Chemistry (855 citations), Catalysis (306 citations) and Materials Chemistry (1.6k citations). Aditya Nandy has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Heather J. Kulik, Chenru Duan, Jon Paul Janet, Fang Liu, Michael G. Taylor, Tzuhsiung Yang, Seyed Mohamad Moosavi, Berend Smit, Peter G. Boyd and Kevin Maik Jablonka. Their work appears in journals such as Chemical Reviews, Journal of the American Chemical Society and Nature Communications.
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.