Igor Stanković

647 citations
35 papers · 502 · h-index 13

Impact in

Papers in

Igor Stanković

33 papers receiving 490 citations

Peers

Igor Stanković
Comparison fields: 5 of 68
  • Condensed Matter Physics 107
  • Biomedical Engineering 190
  • Materials Chemistry 184
  • Atomic and Molecular Physics, and Optics 102
  • Polymers and Plastics 35
Replace Emmanuelle Pauliac-Vaujour with:
Emmanuelle Pauliac-Vaujour United Kingdom
Hongmei Feng China
Nasser Mohieddin Abukhdeir Canada
M. Lucci Italy
Yang Zou China
Tieren Gao United States
Pedro A. Sánchez Austria
Linlin Wang China
Jana Přívratská Czechia
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Citations per field
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Citations per year

Countries citing papers authored by Igor Stanković

Since Specialization
Citations

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

Fields of papers citing papers by Igor Stanković

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Igor Stanković, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Igor Stanković Line = papers co-authored together Igor Stanković links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201289
2 201457
3 201653
4 201728
5 201527
6 200224
7 201923
8 201620
9 201619
10 201318
11 201216
12 200814
13 200414
14 200311
15 20139
16
Usage of neural network for the prediction of surface roughness after the roller burnishing
20128
17 20188
18 20248
19 20138
20 20047

About Igor Stanković

Igor Stanković is a scholar working on Atomic and Molecular Physics, and Optics, Materials Chemistry, Electrical and Electronic Engineering, Biomedical Engineering and Mechanics of Materials, having authored 35 papers that have together received 502 indexed citations. Recurring topics across this work include Force Microscopy Techniques and Applications (7 papers), Characterization and Applications of Magnetic Nanoparticles (5 papers), Geomagnetism and Paleomagnetism Studies (3 papers), Magnetic properties of thin films (3 papers), Ionic liquids properties and applications (3 papers), Theoretical and Computational Physics (3 papers), Organic Electronics and Photovoltaics (2 papers) and Advanced Sensor and Energy Harvesting Materials (2 papers). The work is most often cited by research in Condensed Matter Physics (107 citations), Biomedical Engineering (190 citations), Materials Chemistry (184 citations), Atomic and Molecular Physics, and Optics (102 citations) and Polymers and Plastics (35 citations). Igor Stanković has collaborated with scholars based in Serbia, Germany and Switzerland. Frequent co-authors include René Messina, Martin Kröger, Siegfried Hess, Aleksandar Matković, Borislav Vasić, Radoš Gajić, Nenad Vukmirović, Konstantinos Gkagkas, Marko Mladenović and Veerapandian Ponnuchamy. Their work appears in journals such as Nanoscale, Physica A Statistical Mechanics and its Applications, Computer Physics Communications, Physical Review B and Carbon.

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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