G. N. Dayananda

518 total citations
19 papers, 416 citations indexed

About

G. N. Dayananda is a scholar working on Materials Chemistry, Polymers and Plastics and Mechanical Engineering. According to data from OpenAlex, G. N. Dayananda has authored 19 papers receiving a total of 416 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Materials Chemistry, 7 papers in Polymers and Plastics and 5 papers in Mechanical Engineering. Recurrent topics in G. N. Dayananda's work include Shape Memory Alloy Transformations (11 papers), Polymer composites and self-healing (6 papers) and Silicone and Siloxane Chemistry (4 papers). G. N. Dayananda is often cited by papers focused on Shape Memory Alloy Transformations (11 papers), Polymer composites and self-healing (6 papers) and Silicone and Siloxane Chemistry (4 papers). G. N. Dayananda collaborates with scholars based in India, Czechia and Belgium. G. N. Dayananda's co-authors include Petr Šittner, K.K. Mahesh, V. Novák, Francisco Manuel Braz Fernandes, David Vokoun, R. Stalmans, A. Revathi, P. Senthilkumar, M. Umapathy and R. Suresh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Materials Science and Engineering A and Journal of materials research/Pratt's guide to venture capital sources.

In The Last Decade

G. N. Dayananda

19 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G. N. Dayananda India 10 297 106 88 63 49 19 416
Xudan Yao United Kingdom 12 131 0.4× 90 0.8× 115 1.3× 89 1.4× 28 0.6× 20 392
Yoshiki Sugimoto Japan 13 245 0.8× 224 2.1× 111 1.3× 56 0.9× 20 0.4× 35 425
Zhengxian Liu China 11 101 0.3× 180 1.7× 175 2.0× 83 1.3× 59 1.2× 24 391
Gabriella Faiella Italy 10 320 1.1× 63 0.6× 202 2.3× 144 2.3× 16 0.3× 13 446
Yang Qin China 10 188 0.6× 98 0.9× 52 0.6× 37 0.6× 17 0.3× 22 322
Farzin Najafi Iran 8 194 0.7× 71 0.7× 43 0.5× 89 1.4× 39 0.8× 11 338
Jeonyoon Lee United States 11 216 0.7× 163 1.5× 97 1.1× 97 1.5× 31 0.6× 31 438
R. Pramanik India 11 98 0.3× 69 0.7× 27 0.3× 145 2.3× 25 0.5× 27 307
Victor Ekene Ogbonna South Africa 10 149 0.5× 118 1.1× 171 1.9× 109 1.7× 10 0.2× 28 367

Countries citing papers authored by G. N. Dayananda

Since Specialization
Citations

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

Fields of papers citing papers by G. N. Dayananda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. N. Dayananda

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

All Works

19 of 19 papers shown
1.
Revathi, A., et al.. (2018). Influence of soft segments on thermo-mechanical behaviour of novel epoxy based shape memory polymers. Institutional Repository @ NAL (University of Southampton). 25(1). 68–73. 2 indexed citations
2.
Yatish, K.V., H. S. Lalithamba, R. Suresh, & G. N. Dayananda. (2018). Sodium phosphate synthesis through glycerol purification and its utilization for biodiesel production from dairy scum oil to economize production cost. Sustainable Energy & Fuels. 2(6). 1299–1304. 16 indexed citations
3.
Revathi, A., et al.. (2017). Investigations on tensile creep of CNT-epoxy shape memory polymer nanocomposites. International Journal of Nanotechnology. 14(9/10/11). 945–945. 2 indexed citations
4.
Dayananda, G. N., et al.. (2016). Effect of Cross-linking Density on Creep and Recovery Behavior in Epoxy-Based Shape Memory Polymers (SMEPs) for Structural Applications. Journal of Materials Engineering and Performance. 25(12). 5314–5322. 10 indexed citations
5.
Revathi, A., et al.. (2014). Influence of temperature on tensile behavior of multiwalled carbon nanotube modified epoxy nanocomposites. Journal of materials research/Pratt's guide to venture capital sources. 29(15). 1635–1641. 3 indexed citations
6.
Senthilkumar, P., et al.. (2014). Low Cycle Fatigue Evaluation of NiTi SESMA Thin Wires. Journal of Materials Engineering and Performance. 23(7). 2429–2436. 6 indexed citations
7.
Senthilkumar, P., et al.. (2013). A posteriori processing for estimation of low cycle fatigue failure in SESMA wires. Materials Science and Engineering A. 594. 212–217. 3 indexed citations
8.
Senthilkumar, P., et al.. (2013). Development and wind tunnel evaluation of a shape memory alloy based trim tab actuator for a civil aircraft. Smart Materials and Structures. 22(9). 95025–95025. 5 indexed citations
9.
Revathi, A., et al.. (2013). Effect of strain on the thermomechanical behavior of epoxy based shape memory polymers. Journal of Polymer Research. 20(5). 50 indexed citations
10.
Revathi, A., et al.. (2012). Characterization of shape memory behaviour of CTBN-epoxy resin system. Journal of Polymer Research. 19(6). 25 indexed citations
11.
Senthilkumar, P., et al.. (2011). Experimental evaluation of a shape memory alloy wire actuator with a modulated adaptive controller for position control. Smart Materials and Structures. 21(1). 15015–15015. 19 indexed citations
12.
Ramanaiah, Beeram China, et al.. (2011). Smart Aerodynamic Surface for a Typical Military Aircraft Using Shape Memory Elements. Journal of Aircraft. 48(6). 1968–1977. 7 indexed citations
13.
Dayananda, G. N., et al.. (2011). Autoclaves for Aerospace Applications: Issues and Challenges. SHILAP Revista de lepidopterología. 2011. 1–11. 25 indexed citations
14.
Dayananda, G. N., et al.. (2007). Effect of strain rate on properties of superelastic NiTi thin wires. Materials Science and Engineering A. 486(1-2). 96–103. 67 indexed citations
15.
Novák, V., Petr Šittner, G. N. Dayananda, Francisco Manuel Braz Fernandes, & K.K. Mahesh. (2007). Electric resistance variation of NiTi shape memory alloy wires in thermomechanical tests: Experiments and simulation. Materials Science and Engineering A. 481-482. 127–133. 95 indexed citations
16.
Dayananda, G. N., et al.. (2007). Shape Memory Alloy Based Smart Landing Gear for an Airship. Journal of Aircraft. 44(5). 1469–1477. 11 indexed citations
17.
Dayananda, G. N., et al.. (2003). Development of electronic actuation system for shape-memory-alloy-based aerospace structures. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5062. 914–914. 2 indexed citations
18.
Kamath, Gopalakrishna M., et al.. (2003). Modified thermomechanical modeling approach for shape memory alloy behavior. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5062. 928–928. 1 indexed citations
19.
Šittner, Petr, David Vokoun, G. N. Dayananda, & R. Stalmans. (2000). Recovery stress generation in shape memory Ti50Ni45Cu5 thin wires. Materials Science and Engineering A. 286(2). 298–311. 67 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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