K. N.

1.1k total citations
42 papers, 696 citations indexed

About

K. N. is a scholar working on Plant Science, Mechanics of Materials and Biomedical Engineering. According to data from OpenAlex, K. N. has authored 42 papers receiving a total of 696 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Plant Science, 13 papers in Mechanics of Materials and 10 papers in Biomedical Engineering. Recurrent topics in K. N.'s work include Genetics and Plant Breeding (13 papers), Thermoelastic and Magnetoelastic Phenomena (12 papers) and Nanofluid Flow and Heat Transfer (7 papers). K. N. is often cited by papers focused on Genetics and Plant Breeding (13 papers), Thermoelastic and Magnetoelastic Phenomena (12 papers) and Nanofluid Flow and Heat Transfer (7 papers). K. N. collaborates with scholars based in India, Mali and Russia. K. N.'s co-authors include Om Prakash Yadav, Dinesh Kumar, A. S. Rao, R. K. Bhatt, A. K. Jukanti, C. L. L. Gowda, V. Manga, Jitendra Singh, Mahalingam Govindaraj and Subrahamanyam Upadhyay and has published in prestigious journals such as Theoretical and Applied Genetics, Crop Science and Journal of Heat Transfer.

In The Last Decade

K. N.

39 papers receiving 652 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. N. India 14 377 159 121 97 77 42 696
Ali Asghari Iran 12 264 0.7× 34 0.2× 81 0.7× 46 0.5× 65 0.8× 80 523
Sunil K. Mathanker United States 12 185 0.5× 80 0.5× 184 1.5× 10 0.1× 88 1.1× 32 588
Hesham Ibrahim Egypt 9 350 0.9× 152 1.0× 36 0.3× 144 1.5× 42 0.5× 26 672
Zhiguo Li China 14 405 1.1× 33 0.2× 66 0.5× 24 0.2× 6 0.1× 36 777
Yasuhiro Yogo Japan 15 329 0.9× 113 0.7× 85 0.7× 12 0.1× 27 0.4× 68 715
Manjit Singh India 23 747 2.0× 211 1.3× 26 0.2× 88 0.9× 42 0.5× 78 1.4k
Vaibhav Kumar Singh India 12 284 0.8× 53 0.3× 68 0.6× 17 0.2× 31 0.4× 68 458
Caterina Marè Italy 11 1.2k 3.1× 68 0.4× 30 0.2× 153 1.6× 263 3.4× 19 1.4k
P. Schaare New Zealand 12 270 0.7× 46 0.3× 116 1.0× 13 0.1× 17 0.2× 31 671
O. J. Loewer United States 14 98 0.3× 48 0.3× 18 0.1× 90 0.9× 89 1.2× 62 497

Countries citing papers authored by K. N.

Since Specialization
Citations

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

Fields of papers citing papers by K. N.

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. N.

This figure shows the co-authorship network connecting the top 25 collaborators of K. N.. A scholar is included among the top collaborators of K. N. 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 K. N.. K. N. 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
1.
2.
Chaurasiya, Vikas, Subrahamanyam Upadhyay, K. N., & Jitendra Singh. (2023). Taylor–Galerkin–Legendre-wavelet approach to the analysis of a moving fin with size-dependent thermal conductivity and temperature-dependent internal heat generation. Journal of Thermal Analysis and Calorimetry. 148(22). 12565–12581. 6 indexed citations
3.
N., K., et al.. (2022). Three phase bio-heat transfer model in three-dimensional space for multiprobe cryosurgery. Journal of Thermal Analysis and Calorimetry. 147(24). 14491–14507. 6 indexed citations
4.
5.
Chaurasiya, Vikas, K. N., & Jitendra Singh. (2021). Heat transfer analysis for the solidification of a binary eutectic system under imposed movement of the material. Journal of Thermal Analysis and Calorimetry. 147(4). 3229–3246. 27 indexed citations
6.
Kumar, Mukesh & K. N.. (2021). NUMERICAL SIMULATION OF TIME-FRACTIONAL BIOHEAT TRANSFER MODEL DURING CRYOSURGICAL TREATMENT OF SKIN CANCER. Computational Thermal Sciences An International Journal. 13(4). 51–75. 5 indexed citations
7.
N., K., et al.. (2021). Analysis of DPL Bioheat Transfer Model During Thermal Treatment. International Journal of Applied and Computational Mathematics. 7(2). 4 indexed citations
8.
Gupta, S. K., Abhishek Rathore, K. D. Mungra, et al.. (2020). Identification of heterotic groups in South-Asian-bred hybrid parents of pearl millet. Theoretical and Applied Genetics. 133(3). 873–888. 17 indexed citations
9.
Govindaraj, Mahalingam, O. P. Yadav, B. S. Rajpurohit, et al.. (2020). Genetic Variability, Diversity and Interrelationship for Twelve Grain Minerals in 122 Commercial Pearl Millet Cultivars in India. Agricultural Research. 9(4). 516–525. 15 indexed citations
10.
Kumar, Pappu & K. N.. (2019). Numerical solution of generalized DPL model using wavelet method during thermal therapy applications. International Journal of Biomathematics. 12(3). 1950032–1950032. 10 indexed citations
11.
Govindaraj, Mahalingam, A. S. Rao, H Shivade, & K. N.. (2018). Effect of grain colour on iron and zinc density in pearl millet. Indian Journal of Genetics and Plant Breeding (The). 78(2). 247–247. 6 indexed citations
12.
Kumar, Pappu & K. N.. (2016). FRACTIONAL MODELING OF HYPERBOLIC BIOHEAT TRANSFER EQUATION DURING THERMAL THERAPY. Journal of Mechanics in Medicine and Biology. 17(3). 1750058–1750058. 11 indexed citations
13.
Jukanti, A. K., C. L. L. Gowda, K. N., V. Manga, & R. K. Bhatt. (2016). Crops that feed the world 11. Pearl Millet (Pennisetum glaucum L.): an important source of food security, nutrition and health in the arid and semi-arid tropics. Food Security. 8(2). 307–329. 110 indexed citations
14.
Upadhyay, Subrahamanyam, et al.. (2015). Numerical solution of two point boundary value problems by wavelet Galerkin method. International Journal of Applied Mathematical Research. 4(4). 496–512. 9 indexed citations
15.
Sahrawat, K. L., et al.. (2014). Comparative Evaluation of Ground and Unground Pearl Millet and Sorghum Grain Samples for Determining Total Iron and Zinc. Communications in Soil Science and Plant Analysis. 45(9). 1259–1268. 1 indexed citations
16.
Upadhyay, Subrahamanyam, et al.. (2014). Comparative analysis of power-law type fin problem using wavelet collocation and Galerkin methods. International Journal of Applied Mathematical Research. 3(4). 534–534. 5 indexed citations
17.
Govindaraj, Mahalingam, et al.. (2013). Combining Ability and Heterosis for Grain Iron and Zinc Densities in Pearl Millet. Crop Science. 53(2). 507–517. 61 indexed citations
18.
N., K. & R. P. Thakur. (1996). Smut reaction of pearl millet hybrids affected by fertility restoration and genetic resistance of parental lines. Euphytica. 90(1). 31–37. 8 indexed citations
19.
N., K. & A. S. Rao. (1991). Effect of d2 dwarfing gene on grain yield and yield components in pearl millet near-isogenic lines. Euphytica. 52(1). 25–31. 9 indexed citations
20.
N., K., et al.. (1980). Diallel analysis of heading date in rice (Oryza sativa L.). Theoretical and Applied Genetics. 57(1). 43–47. 4 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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