Divya Nayar
Impact in
-
- Thermodynamic properties of mixtures
- Filtration and Separation top 10%
Papers in
-
- Protein Structure and Dynamics 16
-
- Material Dynamics and Properties 7
- Co-authors
- Nico F. A. van der Vegt (7 shared papers)Charusita Chakravarty (7 shared papers)Manish Agarwal (1 shared paper)Valeria Molinero (1 shared paper)Debdas Dhabal (1 shared paper)Ioana M. Ilie (1 shared paper)W. J. Briels (1 shared paper)Wouter K. den Otter (1 shared paper)
In The Last Decade
Divya Nayar
28 papers receiving 668 citations
Peers
Comparison fields: 5 of 97
- Fluid Flow and Transfer Processes 66
- Filtration and Separation 20
- Molecular Medicine 31
- Atomic and Molecular Physics, and Optics 170
- Materials Chemistry 249
Countries citing papers authored by Divya Nayar
This map shows the geographic impact of Divya Nayar'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 Divya Nayar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Divya Nayar more than expected).
Fields of papers citing papers by Divya Nayar
This network shows the impact of papers produced by Divya Nayar. 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 Divya Nayar. The network helps show where Divya Nayar may publish in the future.
Co-authors
The 25 scholars most cited alongside Divya Nayar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 101 | |
| 2 | 2011 | 81 | |
| 3 | 2018 | 66 | |
| 4 | 2013 | 64 | |
| 5 | 2012 | 52 | |
| 6 | 2017 | 44 | |
| 7 | 2018 | 33 | |
| 8 | 2020 | 29 | |
| 9 | 2018 | 25 | |
| 10 | 2021 | 24 | |
| 11 | 2014 | 19 | |
| 12 | 2022 | 16 | |
| 13 | 2024 | 16 | |
| 14 | 2016 | 14 | |
| 15 | 2021 | 12 | |
| 16 | 2023 | 12 | |
| 17 | 2020 | 12 | |
| 18 | 2012 | 10 | |
| 19 | 2023 | 8 | |
| 20 | 2021 | 8 |
About Divya Nayar
Divya Nayar is a scholar working on Molecular Biology, Materials Chemistry, Atomic and Molecular Physics, and Optics, Fluid Flow and Transfer Processes and Organic Chemistry, having authored 29 papers that have together received 668 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (16 papers), Material Dynamics and Properties (7 papers), Spectroscopy and Quantum Chemical Studies (6 papers), Computational Drug Discovery Methods (4 papers), Rheology and Fluid Dynamics Studies (4 papers), Surfactants and Colloidal Systems (3 papers), Theoretical and Computational Physics (3 papers) and Proteins in Food Systems (3 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (66 citations), Filtration and Separation (20 citations), Molecular Medicine (31 citations), Atomic and Molecular Physics, and Optics (170 citations) and Materials Chemistry (249 citations). Divya Nayar has collaborated with scholars based in India, Germany and Slovakia. Frequent co-authors include Nico F. A. van der Vegt, Charusita Chakravarty, Manish Agarwal, Valeria Molinero, Debdas Dhabal, Ioana M. Ilie, W. J. Briels, Wouter K. den Otter, U. Deva Priyakumar and Sanjoy Bandyopadhyay. Their work appears in journals such as The Journal of Physical Chemistry B, Physical Chemistry Chemical Physics, The Journal of Chemical Physics, ACS Omega and Scientific Data.
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.