Shaibal Mukherjee

3.6k citations
174 papers · 2.9k · h-index 30

Impact in

Papers in

    • Gas Sensing Nanomaterials and Sensors 44
    • Advanced Memory and Neural Computing 27
    • Chalcogenide Semiconductor Thin Films 27
    • ZnO doping and properties 59
    • Copper-based nanomaterials and applications 30
    • Quantum Dots Synthesis And Properties 25

Shaibal Mukherjee

168 papers receiving 2.8k citations

Peers

Shaibal Mukherjee
Comparison fields: 5 of 102
  • Bioengineering 206
  • Materials Chemistry 1.5k
  • Electrical and Electronic Engineering 1.8k
  • Electronic, Optical and Magnetic Materials 560
  • Polymers and Plastics 303
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Citations per field
00.5×2.9×
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Citations per year

Countries citing papers authored by Shaibal Mukherjee

Since Specialization
Citations

This map shows the geographic impact of Shaibal Mukherjee'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 Shaibal Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaibal Mukherjee more than expected).

Fields of papers citing papers by Shaibal Mukherjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shaibal Mukherjee. 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 Shaibal Mukherjee. The network helps show where Shaibal Mukherjee may publish in the future.

Co-authors

The 25 scholars most cited alongside Shaibal Mukherjee, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shaibal Mukherjee Line = papers co-authored together Shaibal Mukherjee links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 174 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995133
2 199495
3 202290
4 201777
5 201373
6 202268
7 201866
8 199463
9 200863
10 201859
11 201354
12 199649
13 201749
14 201642
15 201341
16 201339
17 201838
18 201838
19 202337
20 201836

About Shaibal Mukherjee

Shaibal Mukherjee is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Electronic, Optical and Magnetic Materials, Condensed Matter Physics and Cellular and Molecular Neuroscience, having authored 174 papers that have together received 2.9k indexed citations. Recurring topics across this work include ZnO doping and properties (59 papers), Gas Sensing Nanomaterials and Sensors (44 papers), Ga2O3 and related materials (36 papers), Copper-based nanomaterials and applications (30 papers), Advanced Memory and Neural Computing (27 papers), Chalcogenide Semiconductor Thin Films (27 papers), Quantum Dots Synthesis And Properties (25 papers) and GaN-based semiconductor devices and materials (18 papers). The work is most often cited by research in Bioengineering (206 citations), Materials Chemistry (1.5k citations), Electrical and Electronic Engineering (1.8k citations), Electronic, Optical and Magnetic Materials (560 citations) and Polymers and Plastics (303 citations). Shaibal Mukherjee has collaborated with scholars based in India, Australia and United States. Frequent co-authors include Sushil Pandey, Vishnu Awasthi, Arturo Casadevall, Rohit Singh, Amitesh Kumar, Mukul Gupta, Myo Than Htay, Vivek Garg, Mangal Das and Brajendra S. Sengar. Their work appears in journals such as IEEE Transactions on Electron Devices, IEEE Sensors Journal, Journal of Physics D Applied Physics, ACS Applied Nano Materials and Applied Physics 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.

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