Maya Narayanan Nair

1.4k citations
50 papers · 999 indexed · h-index 16
Topics
Graphene research and applications (19 papers)Polymer Nanocomposites and Properties (10 papers)Polymer crystallization and properties (10 papers)
Partner nations
FranceUnited StatesIndia

In The Last Decade

Maya Narayanan Nair

45 papers receiving 976 citations

Peers

Maya Narayanan Nair
Comparison fields: 5 of 63
  • Materials Chemistry 705
  • Electrical and Electronic Engineering 277
  • Atomic and Molecular Physics, and Optics 256
  • Biomedical Engineering 167
  • Polymers and Plastics 160
Replace Pengfei Fu with:
Pengfei Fu China
K. D. Patel India
Yue Chan China
Tianzhong Yang China
Xueyun Zhou China
Beth M. Nichols United States
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Citations per field
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Citations per year

Countries citing papers authored by Maya Narayanan Nair

Since Specialization
Citations

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

Fields of papers citing papers by Maya Narayanan Nair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya Narayanan Nair. 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 Maya Narayanan Nair. The network helps show where Maya Narayanan Nair may publish in the future.

Co-authorship network of co-authors of Maya Narayanan Nair

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 5
4 0
5 0
6 1
7 0
8 5
9 3
10 12
11 24
12
First determination of the valence band dispersion of CH3NH3PbI3 hybrid organic-inorganic perovskite
3
13
Semiconducting graphene and its incommensurate SiC interface
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14 131
15 11
16 8
17 14
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19 7
20 11

About Maya Narayanan Nair

Maya Narayanan Nair is a scholar working on Polymers and Plastics, Materials Chemistry and Biomaterials, having authored 50 papers that have together received 999 indexed citations. Recurring topics across this work include Graphene research and applications (19 papers), Polymer Nanocomposites and Properties (10 papers) and Polymer crystallization and properties (10 papers). The work is most often cited by research in Materials Chemistry (705 citations), Polymers and Plastics (160 citations) and Atomic and Molecular Physics, and Optics (256 citations). Maya Narayanan Nair has collaborated with scholars based in France, United States and India. Frequent co-authors include Antonio Tejeda, A. Taleb‐Ibrahimi, Arlensiú Celis, M. R. Gopinathan Nair, E. H. Conrad, Claire Berger, Walter A. de Heer, M. S. Nevius, Adam Heller and Matthew Conrad. Their work appears in journals such as Physical Review Letters, Angewandte Chemie International Edition 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.

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