Pankaj Rajak
- Materials Chemistry top 10%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Atomic and Molecular Physics, and Optics
- Mechanical Engineering
- Co-authors
- Aiichiro NakanoPriya VashishtaRajiv K. KaliaAravind KrishnamoorthyFuyuki ShimojoKen‐ichi NomuraSungwook HongSubodh Tiwari
- Topics
- Machine Learning in Materials Science (19 papers)2D Materials and Applications (12 papers)MXene and MAX Phase Materials (7 papers)
- Partner nations
- United StatesJapanThailand
In The Last Decade
Pankaj Rajak
40 papers receiving 949 citations
Peers
Comparison fields: 5 of 79
- Materials Chemistry 689
- Electrical and Electronic Engineering 248
- Biomedical Engineering 215
- Atomic and Molecular Physics, and Optics 110
- Mechanical Engineering 93
Countries citing papers authored by Pankaj Rajak
This map shows the geographic impact of Pankaj Rajak'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 Pankaj Rajak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pankaj Rajak more than expected).
Fields of papers citing papers by Pankaj Rajak
This network shows the impact of papers produced by Pankaj Rajak. 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 Pankaj Rajak. The network helps show where Pankaj Rajak may publish in the future.
Co-authorship network of co-authors of Pankaj Rajak
This figure shows the co-authorship network connecting the top 25 collaborators of Pankaj Rajak. A scholar is included among the top collaborators of Pankaj Rajak 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 Pankaj Rajak. Pankaj Rajak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 17 | |
| 3 | 133 | |
| 4 | 5 | |
| 5 | 38 | |
| 6 | 25 | |
| 7 | 2 | |
| 8 | 30 | |
| 9 | 23 | |
| 10 | Machine learning of reaction pathways in chemical vapor deposition of MoS 2 monolayers | 1 |
| 11 | 41 | |
| 12 | 60 | |
| 13 | 44 | |
| 14 | 12 | |
| 15 | Structural Phase Transformation in Strained Monolayer MoWSe 2 Alloy | 1 |
| 16 | 25 | |
| 17 | 6 | |
| 18 | 130 | |
| 19 | 18 | |
| 20 | 52 |
About Pankaj Rajak
Pankaj Rajak is a scholar working on Metals and Alloys, Materials Chemistry and Physical and Theoretical Chemistry, having authored 42 papers that have together received 967 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (19 papers), 2D Materials and Applications (12 papers) and MXene and MAX Phase Materials (7 papers). The work is most often cited by research in Materials Chemistry (689 citations), Ceramics and Composites (32 citations) and Polymers and Plastics (73 citations). Pankaj Rajak has collaborated with scholars based in United States, Japan and Thailand. Frequent co-authors include Aiichiro Nakano, Priya Vashishta, Rajiv K. Kalia, Aravind Krishnamoorthy, Fuyuki Shimojo, Ken‐ichi Nomura, Sungwook Hong, Subodh Tiwari, David J. Singh and Lindsay Bassman Oftelie. Their work appears in journals such as Physical Review Letters, The Journal of Chemical Physics and Nano 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.