V. Periasamy

764 total citations
34 papers, 636 citations indexed

About

V. Periasamy is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Civil and Structural Engineering. According to data from OpenAlex, V. Periasamy has authored 34 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Materials Chemistry, 14 papers in Electrical and Electronic Engineering and 9 papers in Civil and Structural Engineering. Recurrent topics in V. Periasamy's work include Corrosion Behavior and Inhibition (15 papers), Concrete Corrosion and Durability (9 papers) and Electrodeposition and Electroless Coatings (7 papers). V. Periasamy is often cited by papers focused on Corrosion Behavior and Inhibition (15 papers), Concrete Corrosion and Durability (9 papers) and Electrodeposition and Electroless Coatings (7 papers). V. Periasamy collaborates with scholars based in India and Malaysia. V. Periasamy's co-authors include Malathy Pushpavanam, Mayakrishnan Prabakaran, U. Natarajan, R. Saravanan, A. Keshav Krishna, Krishpersad Manohar, K. Rama Mohan, R. Saravanan, A. Elango and B.V. Apparao and has published in prestigious journals such as Corrosion Science, Applied Surface Science and Wear.

In The Last Decade

V. Periasamy

32 papers receiving 614 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
V. Periasamy India	14	329	216	151	124	80	34	636
J. Rodríguez Spain	20	257 0.8×	203 0.9×	47 0.3×	410 3.3×	12 0.1×	92	970
Xinhua Chen China	18	244 0.7×	136 0.6×	95 0.6×	349 2.8×	75 0.9×	89	881
Fei Long Canada	17	710 2.2×	43 0.2×	47 0.3×	343 2.8×	72 0.9×	85	1.1k
Minjeong Kim South Korea	15	111 0.3×	135 0.6×	35 0.2×	69 0.6×	21 0.3×	62	710
Dongying Wang China	17	151 0.5×	142 0.7×	59 0.4×	250 2.0×	25 0.3×	55	806
Ruiming Zhang China	18	148 0.4×	351 1.6×	11 0.1×	125 1.0×	36 0.5×	69	792
Yanan Zeng China	15	157 0.5×	56 0.3×	191 1.3×	245 2.0×	9 0.1×	84	745
J. L. Guiñón Spain	21	867 2.6×	179 0.8×	352 2.3×	323 2.6×	592 7.4×	51	1.4k
Lietai Yang United States	17	641 1.9×	106 0.5×	459 3.0×	263 2.1×	423 5.3×	73	1.0k
Penghui Gao China	16	133 0.4×	89 0.4×	39 0.3×	314 2.5×	8 0.1×	61	763

Countries citing papers authored by V. Periasamy

Since Specialization

Citations

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

Fields of papers citing papers by V. Periasamy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of V. Periasamy

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

All Works

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20 of 20 papers shown

Periasamy, V., et al.. (2025). Detecting Contaminants in Water; A Review on the Current and State-of-the-Art Technologies. Water Air & Soil Pollution. 237(6).

Periasamy, V., et al.. (2018). Self-assembly on copper surface by using imidazole derivative for corrosion protection. Journal of Adhesion Science and Technology. 32(16). 1733–1749. 20 indexed citations

Periasamy, V. & M. Venkateshwarlu. (2017). Petrography and geochemistry of Jurassic sandstones from the Jhuran Formation of Jara dome, Kachchh basin, India: Implications for provenance and tectonic setting. Journal of Earth System Science. 126(3). 13 indexed citations

Prabakaran, Mayakrishnan, et al.. (2016). Enhanced corrosion inhibition behavior of carbon steel in aqueous solution by Phosphoserine-Zn²⁺system. Journal of Adhesion Science and Technology. 30(14). 1487–1509. 13 indexed citations

Devi, Anjana, et al.. (2015). Formation, investigation and characterization of self-assembled monolayers of 5-methyl-1,3,4-thiadiazole-2-thiol in corrosion protection of copper in neutral media. Advances in Applied Science Research. 6(7). 2 indexed citations

Prabakaran, Mayakrishnan, et al.. (2015). Investigation on the inhibition effect of aspartic acid and Zn²⁺ions on carbon steel surface in aqueous solution. Journal of Adhesion Science and Technology. 30(1). 24–44. 4 indexed citations

Periasamy, V., et al.. (2014). Slurry erosion resistance of laser-modified 16Cr-5Ni stainless steel.. International Journal of ChemTech Research. 6(1). 691–704. 8 indexed citations

Prabakaran, Mayakrishnan, et al.. (2014). Corrosion protection of mild steel by a new phosphonate inhibitor system in aqueous solution. Egyptian Journal of Petroleum. 23(4). 367–377. 44 indexed citations

Krishna, A. Keshav, et al.. (2013). Assessment of heavy metal contamination in soils around chromite mining areas, Nuggihalli, Karnataka, India. Environmental Earth Sciences. 70(2). 699–708. 83 indexed citations

10.

Periasamy, V., et al.. (2013). Improvement of Slurry Erosion Wear Resistance of 16Cr-5Ni Martensite Stainless Steel by LSA and LTH. Journal of Materials Engineering and Performance. 22(12). 3689–3698. 18 indexed citations

11.

Velayutham, Thamil Selvi, Wee Chen Gan, W.H. Abd. Majid, et al.. (2013). Pyroelectricity in Synthetic Amphitropic Glycolipid for Potential Application of IR Sensor Device. Ferroelectrics. 445(1). 67–73. 5 indexed citations

12.

Periasamy, V., et al.. (2012). Effect of Surfactants on the Electrodeposition of Ni-SiC Composites. Portugaliae electrochimica acta. 30(1). 1–14. 24 indexed citations

13.

Prabakaran, Mayakrishnan, et al.. (2012). Inhibitive properties of a phosphonate-based formulation for corrosion control of carbon steel. Research on Chemical Intermediates. 39(8). 3507–3524. 11 indexed citations

14.

Subramanian, K. G., V. Periasamy, Malathy Pushpavanam, & Karthik Ramasamy. (2010). Prediction of cathode efficiency in electro-deposition of copper–tin using regression and artificial neural network model. Journal of Electroanalytical Chemistry. 648(2). 176–183. 4 indexed citations

15.

Ramanathan, K., V. Periasamy, Malathy Pushpavanam, & U. Natarajan. (2009). Particle Swarm Optimisation of hardness in nickel diamond electro composites. Archives of Materials Science and Engineering. 1. 232–236. 7 indexed citations

16.

Elango, A., et al.. (2009). Polyaniline as a corrosion inhibitor for commercial aluminium in alkaline solutions. 51(2). 97–104.

17.

Subramanian, K. G., V. Periasamy, Malathy Pushpavanam, & Karthik Ramasamy. (2009). Predictive Modeling of Copper in Electro-deposition of Bronze Using Regression and Neural Networks. Portugaliae electrochimica acta. 27(1). 47–55. 8 indexed citations

18.

Natarajan, U., et al.. (2006). A decision fusion algorithm for tool condition monitoring in drilling using Hidden Markov Model (HMM). Indian Journal of Engineering and Materials Sciences. 13(2). 103–109. 3 indexed citations

19.

Natarajan, U., V. Periasamy, & R. Saravanan. (2006). Application of particle swarm optimisation in artificial neural network for the prediction of tool life. The International Journal of Advanced Manufacturing Technology. 31(9-10). 871–876. 32 indexed citations

20.

Natarajan, U., V. Periasamy, & R. Saravanan. (2005). Application of particle swarm optimisation in artificial neural network for the prediction of tool life. The International Journal of Advanced Manufacturing Technology. 28(11-12). 1084–1088. 48 indexed citations

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