Neha Kanwar Rawat
- Polymers and Plastics top 10%
- Biomaterials top 10%
- Biomedical Engineering
- Process Chemistry and Technology top 5%
- Materials Chemistry
- Co-authors
- Halima KhatoonSajid IqbalSharif AhmadPrem N. GuptaAshish BaldiSatish Kumar SharmaAshutosh Kumar DubeyAnil Kumar
- Topics
- Conducting polymers and applications (6 papers)Drug Solubulity and Delivery Systems (3 papers)Organic Electronics and Photovoltaics (3 papers)
- Partner nations
- IndiaUnited StatesUnited Arab Emirates
In The Last Decade
Neha Kanwar Rawat
26 papers receiving 451 citations
Peers
Comparison fields: 5 of 96
- Polymers and Plastics 177
- Biomaterials 112
- Biomedical Engineering 87
- Process Chemistry and Technology 77
- Materials Chemistry 69
Countries citing papers authored by Neha Kanwar Rawat
This map shows the geographic impact of Neha Kanwar Rawat'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 Neha Kanwar Rawat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neha Kanwar Rawat more than expected).
Fields of papers citing papers by Neha Kanwar Rawat
This network shows the impact of papers produced by Neha Kanwar Rawat. 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 Neha Kanwar Rawat. The network helps show where Neha Kanwar Rawat may publish in the future.
Co-authorship network of co-authors of Neha Kanwar Rawat
This figure shows the co-authorship network connecting the top 25 collaborators of Neha Kanwar Rawat. A scholar is included among the top collaborators of Neha Kanwar Rawat 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 Neha Kanwar Rawat. Neha Kanwar Rawat 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 | 1 | |
| 3 | 67 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 7 | |
| 10 | 141 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 35 | |
| 14 | 19 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | Optimization of Surface Roughness, Material Removal Rate and Tool Wear Rate in EDM using Taguchi Method | 5 |
| 18 | 43 | |
| 19 | 46 | |
| 20 | 13 |
About Neha Kanwar Rawat
Neha Kanwar Rawat is a scholar working on Pharmaceutical Science, Polymers and Plastics and Filtration and Separation, having authored 28 papers that have together received 465 indexed citations. Recurring topics across this work include Conducting polymers and applications (6 papers), Drug Solubulity and Delivery Systems (3 papers) and Organic Electronics and Photovoltaics (3 papers). The work is most often cited by research in Process Chemistry and Technology (77 citations), Polymers and Plastics (177 citations) and Biomaterials (112 citations). Neha Kanwar Rawat has collaborated with scholars based in India, United States and United Arab Emirates. Frequent co-authors include Halima Khatoon, Sajid Iqbal, Sharif Ahmad, Prem N. Gupta, Ashish Baldi, Satish Kumar Sharma, Ashutosh Kumar Dubey, Anil Kumar, Ranjna Sirohi and Anujit Ghosal. Their work appears in journals such as RSC Advances, Biomedicine & Pharmacotherapy and Current Pharmaceutical Design.
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.