Arunkumar Chitteth Rajan

816 total citations
10 papers, 657 citations indexed

About

Arunkumar Chitteth Rajan is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Arunkumar Chitteth Rajan has authored 10 papers receiving a total of 657 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Materials Chemistry, 6 papers in Electrical and Electronic Engineering and 3 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Arunkumar Chitteth Rajan's work include Machine Learning in Materials Science (3 papers), Graphene research and applications (2 papers) and Molecular Junctions and Nanostructures (2 papers). Arunkumar Chitteth Rajan is often cited by papers focused on Machine Learning in Materials Science (3 papers), Graphene research and applications (2 papers) and Molecular Junctions and Nanostructures (2 papers). Arunkumar Chitteth Rajan collaborates with scholars based in South Korea, India and United States. Arunkumar Chitteth Rajan's co-authors include Abhishek K. Singh, Hiroshi Mizuseki, Avanish Mishra, Kwang‐Ryeol Lee, Swanti Satsangi, Kwang S. Kim, Rampi Ramprasad, Harikrishna Sahu, Pranav Shetty and Chao Zhang and has published in prestigious journals such as ACS Nano, Chemistry of Materials and ACS Applied Materials & Interfaces.

In The Last Decade

Arunkumar Chitteth Rajan

10 papers receiving 643 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Arunkumar Chitteth Rajan South Korea 9 512 206 133 86 77 10 657
Shuhao Zhang China 12 572 1.1× 208 1.0× 93 0.7× 31 0.4× 90 1.2× 28 695
Chuhong Wang United States 11 411 0.8× 315 1.5× 52 0.4× 43 0.5× 91 1.2× 26 738
Klaus Stoewe Germany 5 325 0.6× 97 0.5× 99 0.7× 38 0.4× 73 0.9× 9 475
Kameel Abdel‐Latif United States 11 436 0.9× 281 1.4× 251 1.9× 28 0.3× 38 0.5× 13 672
Suyong Han United States 11 309 0.6× 185 0.9× 215 1.6× 33 0.4× 32 0.4× 18 559
Arthur France‐Lanord United States 17 561 1.1× 659 3.2× 149 1.1× 44 0.5× 113 1.5× 33 1.1k
Amir Hajibabaei South Korea 12 551 1.1× 517 2.5× 61 0.5× 39 0.5× 187 2.4× 24 910
Deepak Kamal United States 10 496 1.0× 131 0.6× 181 1.4× 56 0.7× 25 0.3× 12 665
Tianyi Wu Canada 5 301 0.6× 108 0.5× 222 1.7× 120 1.4× 42 0.5× 9 585
Ziyang Zhang China 13 189 0.4× 172 0.8× 155 1.2× 201 2.3× 64 0.8× 41 622

Countries citing papers authored by Arunkumar Chitteth Rajan

Since Specialization
Citations

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

Fields of papers citing papers by Arunkumar Chitteth Rajan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arunkumar Chitteth Rajan. 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 Arunkumar Chitteth Rajan. The network helps show where Arunkumar Chitteth Rajan may publish in the future.

Co-authorship network of co-authors of Arunkumar Chitteth Rajan

This figure shows the co-authorship network connecting the top 25 collaborators of Arunkumar Chitteth Rajan. A scholar is included among the top collaborators of Arunkumar Chitteth Rajan 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 Arunkumar Chitteth Rajan. Arunkumar Chitteth Rajan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Gurnani, Rishi, et al.. (2025). A physics-enforced neural network to predict polymer melt viscosity. npj Computational Materials. 11(1). 8 indexed citations
2.
Li, Mingzhe, Liang Yue, Arunkumar Chitteth Rajan, et al.. (2023). Low-temperature 3D printing of transparent silica glass microstructures. Science Advances. 9(40). eadi2958–eadi2958. 46 indexed citations
3.
Shetty, Pranav, et al.. (2023). A general-purpose material property data extraction pipeline from large polymer corpora using natural language processing. npj Computational Materials. 9(1). 52–52. 81 indexed citations
4.
Rajan, Arunkumar Chitteth, et al.. (2023). Engineering conjugated porous polymers for nitroaromatic sensing. Chemical Papers. 77(12). 7409–7419. 1 indexed citations
5.
Sahu, Harikrishna, Lihua Chen, Arunkumar Chitteth Rajan, et al.. (2021). An Informatics Approach for Designing Conducting Polymers. ACS Applied Materials & Interfaces. 13(45). 53314–53322. 27 indexed citations
6.
Mishra, Avanish, Swanti Satsangi, Arunkumar Chitteth Rajan, et al.. (2019). Accelerated Data-Driven Accurate Positioning of the Band Edges of MXenes. The Journal of Physical Chemistry Letters. 10(4). 780–785. 56 indexed citations
7.
Rajan, Arunkumar Chitteth, Avanish Mishra, Swanti Satsangi, et al.. (2018). Machine-Learning-Assisted Accurate Band Gap Predictions of Functionalized MXene. Chemistry of Materials. 30(12). 4031–4038. 311 indexed citations
8.
Rajan, Arunkumar Chitteth, Jeonghun Yun, Yeonchoo Cho, et al.. (2014). Two Dimensional Molecular Electronics Spectroscopy for Molecular Fingerprinting, DNA Sequencing, and Cancerous DNA Recognition. ACS Nano. 8(2). 1827–1833. 71 indexed citations
9.
Thomas, Simil, et al.. (2014). In Search of a Two-Dimensional Material for DNA Sequencing. The Journal of Physical Chemistry C. 118(20). 10855–10858. 38 indexed citations
10.
Rajan, Arunkumar Chitteth, et al.. (2014). Molecular sensing using armchair graphene nanoribbon. Journal of Computational Chemistry. 35(26). 1916–1920. 18 indexed citations

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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