P.L. Narayana

1.1k total citations
41 papers, 817 citations indexed

About

P.L. Narayana is a scholar working on Mechanical Engineering, Materials Chemistry and Mechanics of Materials. According to data from OpenAlex, P.L. Narayana has authored 41 papers receiving a total of 817 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Mechanical Engineering, 22 papers in Materials Chemistry and 7 papers in Mechanics of Materials. Recurrent topics in P.L. Narayana's work include Titanium Alloys Microstructure and Properties (15 papers), Additive Manufacturing Materials and Processes (12 papers) and Metallurgy and Material Forming (6 papers). P.L. Narayana is often cited by papers focused on Titanium Alloys Microstructure and Properties (15 papers), Additive Manufacturing Materials and Processes (12 papers) and Metallurgy and Material Forming (6 papers). P.L. Narayana collaborates with scholars based in South Korea, India and Saudi Arabia. P.L. Narayana's co-authors include N.S. Reddy, Jae‐Keun Hong, Jong‐Taek Yeom, Chan Hee Park, Seong-Woo Choi, Chenglin Li, Seong-Woong Kim, Jae H. Kim, Sang Won Lee and Sangwon Lee and has published in prestigious journals such as The Science of The Total Environment, Chemosphere and Materials Science and Engineering A.

In The Last Decade

P.L. Narayana

40 papers receiving 790 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
P.L. Narayana South Korea 19 525 415 147 121 102 41 817
Azlan Ahmad Malaysia 15 366 0.7× 190 0.5× 78 0.5× 103 0.9× 63 0.6× 36 710
Uday Vaidya United States 11 470 0.9× 158 0.4× 372 2.5× 92 0.8× 30 0.3× 26 911
Hua Sun China 17 806 1.5× 625 1.5× 108 0.7× 203 1.7× 58 0.6× 28 1.4k
Víctor Esteban Reyes-Cruz Mexico 12 940 1.8× 289 0.7× 68 0.5× 277 2.3× 22 0.2× 51 1.2k
Mehran Dadkhah Italy 15 360 0.7× 252 0.6× 66 0.4× 165 1.4× 22 0.2× 23 755
Mxolisi Brendon Shongwe South Africa 21 1.1k 2.1× 570 1.4× 295 2.0× 106 0.9× 19 0.2× 139 1.5k
Lingling Ren China 17 411 0.8× 164 0.4× 44 0.3× 188 1.6× 31 0.3× 44 788
Guichuan Li Belgium 19 755 1.4× 272 0.7× 43 0.3× 284 2.3× 364 3.6× 30 1.1k
Rajasekaran Saminathan India 16 467 0.9× 123 0.3× 91 0.6× 48 0.4× 26 0.3× 56 735
Norhayati Ahmad Malaysia 16 298 0.6× 184 0.4× 42 0.3× 224 1.9× 92 0.9× 48 821

Countries citing papers authored by P.L. Narayana

Since Specialization
Citations

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

Fields of papers citing papers by P.L. Narayana

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P.L. Narayana. 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 P.L. Narayana. The network helps show where P.L. Narayana may publish in the future.

Co-authorship network of co-authors of P.L. Narayana

This figure shows the co-authorship network connecting the top 25 collaborators of P.L. Narayana. A scholar is included among the top collaborators of P.L. Narayana 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 P.L. Narayana. P.L. Narayana 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.
Paturi, Uma Maheshwera Reddy, et al.. (2025). Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys. Crystals. 15(5). 404–404. 2 indexed citations
2.
Narayana, P.L., et al.. (2025). Artificial Neural Network Modeling of Ti-6Al-4V Alloys to Correlate Their Microstructure and Mechanical Properties. Materials. 18(5). 1099–1099. 3 indexed citations
3.
Narayana, P.L., et al.. (2025). Artificial neural network-based prediction of stacking fault energy in Fe-Cr-Mn-C-N steels. Canadian Metallurgical Quarterly. 65(2). 1451–1459. 1 indexed citations
4.
Narayana, P.L., Jae H. Kim, & Jae‐Keun Hong. (2024). Microstructural evolution and tensile properties of direct energy deposited Ti-4Al-5Co-0.25Si alloy during heat treatment. Journal of Alloys and Compounds. 993. 174657–174657. 6 indexed citations
5.
Reddy, B.S., P.L. Narayana, Uma Maheshwera Reddy Paturi, et al.. (2023). Modeling capacitance of carbon-based supercapacitors by artificial neural networks. Journal of Energy Storage. 72. 108537–108537. 13 indexed citations
6.
Reddy, B.S., Uma Maheshwera Reddy Paturi, Jaekyung Sung, et al.. (2023). Neural Network Models for Estimating the Impact of Physicochemical and Operational Parameters on the Specific Capacity of Activated-Carbon-Based Supercapacitors. Energy & Fuels. 37(19). 15084–15094.
7.
Narayana, P.L., et al.. (2023). Effect of Oxygen Content on Microstructure and Mechanical Properties of Additive Manufactured Ti-6Al-4V. Korean Journal of Metals and Materials. 61(9). 714–720. 11 indexed citations
8.
Kim, Jae H., et al.. (2023). Enhancing the mechanical properties and corrosion resistance of commercially pure titanium using tungsten carbide composites fabricated via additive manufacturing. Journal of Materials Research and Technology. 27. 5070–5081. 8 indexed citations
9.
Narayana, P.L., Xiaosong Wang, Abeer Ali Alnuaim, et al.. (2021). Artificial neural networks modeling for lead removal from aqueous solutions using iron oxide nanocomposites from bio-waste mass. Environmental Research. 199. 111370–111370. 32 indexed citations
10.
Narayana, P.L., Jae H. Kim, Sangwon Lee, et al.. (2021). Novel eutectoid Ti-5Ni alloy fabricated via direct energy deposition. Scripta Materialia. 200. 113918–113918. 28 indexed citations
11.
Reddy, B.S., P.L. Narayana, S. K. Khadheer Pasha, et al.. (2021). Knowledge extraction of sonophotocatalytic treatment for acid blue 113 dye removal by artificial neural networks. Environmental Research. 204(Pt D). 112359–112359. 13 indexed citations
12.
Reddy, B.S., V E Sathishkumar, P.L. Narayana, et al.. (2021). Prediction of batch sorption of barium and strontium from saline water. Environmental Research. 197. 111107–111107. 12 indexed citations
13.
Wang, Xiaosong, et al.. (2021). Modeling the quantitative effect of alloying elements on the M temperature of high carbon steel by artificial neural networks. Materials Letters. 291. 129573–129573. 8 indexed citations
14.
Reddy, B.S., Jayaraman Theerthagiri, P.L. Narayana, et al.. (2021). Modeling and optimization of process parameters of biofilm reactor for wastewater treatment. The Science of The Total Environment. 787. 147624–147624. 18 indexed citations
15.
Narayana, P.L., Lakshmi Prasanna Lingamdinne, Rama Rao Karri, et al.. (2021). Predictive capability evaluation and optimization of Pb(II) removal by reduced graphene oxide-based inverse spinel nickel ferrite nanocomposite. Environmental Research. 204(Pt A). 112029–112029. 46 indexed citations
16.
Li, Chenglin, P.L. Narayana, Jae‐Keun Hong, et al.. (2021). Formation of equiaxed grains in selective laser melted pure titanium during annealing. Journal of Materials Research and Technology. 11. 301–311. 32 indexed citations
17.
Reddy, B.S., P.L. Narayana, Abdulwahed Fahad Alrefaei, et al.. (2021). Modeling cyclic volatile methylsiloxanes removal efficiency from wastewater by ZnO-coated aluminum anode using artificial neural networks. Journal of King Saud University - Science. 33(2). 101339–101339. 3 indexed citations
18.
Sivanantham, Vinu, et al.. (2020). Modeling and optimization of chlorophenol rejection for spiral wound reverse osmosis membrane modules. Chemosphere. 268. 129345–129345. 3 indexed citations
19.
Narayana, P.L., Sang Won Lee, Chan Hee Park, et al.. (2020). Modeling high-temperature mechanical properties of austenitic stainless steels by neural networks. Computational Materials Science. 179. 109617–109617. 36 indexed citations
20.
Narayana, P.L., Chenglin Li, Seong-Woong Kim, et al.. (2019). High strength and ductility of electron beam melted β stabilized γ-TiAl alloy at 800°C. Materials Science and Engineering A. 756. 41–45. 41 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Azlan Ahmad Breakdown of academic impact, for papers by Uday Vaidya Breakdown of academic impact, for papers by Hua Sun Breakdown of academic impact, for papers by Víctor Esteban Reyes-Cruz Breakdown of academic impact, for papers by Mehran Dadkhah Breakdown of academic impact, for papers by Mxolisi Brendon Shongwe Breakdown of academic impact, for papers by Lingling Ren Breakdown of academic impact, for papers by Guichuan Li Breakdown of academic impact, for papers by Rajasekaran Saminathan Breakdown of academic impact, for papers by Norhayati Ahmad
Rankless by CCL
2026