Sambit Das

23 papers receiving 754 citations

Peers

Sambit Das
Comparison fields: 5 of 68
  • Automotive Engineering 221
  • Computational Mathematics 6
  • Mechanical Engineering 342
  • Metals and Alloys 23
  • Hardware and Architecture 31
Replace Jihun Choi with:
Jihun Choi South Korea
Eli Brosh Israel
Matthias Neubauer Austria
Lingyun Yang China
Danghui Wang China
Amit Banerjee India
Steven R. LeClair United States
Philippe Jacquet France
M. Rencz Hungary
Sambit Das relative to Jihun Choi South Korea Jihun Choi's profile →
Citations per field
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Jihun Choi · 1×
Citations per year

Countries citing papers authored by Sambit Das

Since Specialization
Citations

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

Fields of papers citing papers by Sambit Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sambit Das, 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 Sambit Das Line = papers co-authored together Sambit Das links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003345
2 2011104
3 201998
4 201936
5 201031
6 202325
7 202324
8 201321
9 202320
10 201716
11 202111
12 20198
13 20227
14 20136
15 20256
16 20125
17 20235
18 20245
19 20063
20 20123

About Sambit Das

Sambit Das is a scholar working on Materials Chemistry, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Mechanics of Materials and Condensed Matter Physics, having authored 23 papers that have together received 785 indexed citations. Recurring topics across this work include Advanced Chemical Physics Studies (4 papers), Semiconductor materials and devices (4 papers), Machine Learning in Materials Science (3 papers), Ferroelectric and Negative Capacitance Devices (2 papers), Metal and Thin Film Mechanics (2 papers), Fractional Differential Equations Solutions (2 papers), Microstructure and mechanical properties (2 papers) and Advanced NMR Techniques and Applications (2 papers). The work is most often cited by research in Automotive Engineering (221 citations), Computational Mathematics (6 citations), Mechanical Engineering (342 citations), Metals and Alloys (23 citations) and Hardware and Architecture (31 citations). Sambit Das has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Vikram Gavini, Hovav Shacham, Phani Motamarri, Denis Davydov, Krishnendu Ghosh, Shiva Rudraraju, Ravindra Jategaonkar, Wenyuan Liao, Ying Wai Li and Liang Qi. Their work appears in journals such as Physical review. B., Journal of Computational and Nonlinear Dynamics, Physical Review Materials, The Journal of Chemical Physics and Journal of Guidance Control and Dynamics.

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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