Dmytro Dudenko
- Polymers and Plastics top 2%
- Conducting polymers and applications 6
- Materials Chemistry top 5%
- Machine Learning in Materials Science 4
- Biomaterials top 5%
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- Advanced Battery Materials and Technologies 6
- Organic Electronics and Photovoltaics 6
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- Advanced NMR Techniques and Applications 9
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- Synthesis and Properties of Aromatic Compounds 6
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- Chemical Synthesis and Analysis 4
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- Computational Drug Discovery Methods 4
Dmytro Dudenko
34 papers receiving 4.2k citations
Hit Papers
Peers
Comparison fields: 5 of 173
- Polymers and Plastics 688
- Process Chemistry and Technology 99
- Materials Chemistry 1.4k
- Biomaterials 353
- Electrical and Electronic Engineering 1.3k
Countries citing papers authored by Dmytro Dudenko
This map shows the geographic impact of Dmytro Dudenko'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 Dmytro Dudenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmytro Dudenko more than expected).
Fields of papers citing papers by Dmytro Dudenko
This network shows the impact of papers produced by Dmytro Dudenko. 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 Dmytro Dudenko. The network helps show where Dmytro Dudenko may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dmytro Dudenko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2024 | 1 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 39 | |
| 6 | 2022 | 10 | |
| 7 | 2021 | 2 | |
| 8 | 2018 | 113 | |
| 9 | 2017 | 64 | |
| 10 | 2015 | 27 | |
| 11 | 2015 | 24 | |
| 12 | Ammonia as a case study for the spontaneous ionization of a simple hydrogen-bonded compoundbreakdown → | 2014 | 2965 |
| 13 | 2014 | 43 | |
| 14 | 2013 | 21 | |
| 15 | 2012 | 154 | |
| 16 | 2012 | 83 | |
| 17 | 2012 | 43 | |
| 18 | 2011 | 74 | |
| 19 | 2011 | 37 | |
| 20 | 2010 | 9 |
About Dmytro Dudenko
Dmytro Dudenko is a scholar working on Process Chemistry and Technology, Polymers and Plastics, Spectroscopy, Biomaterials and Organic Chemistry, having authored 34 papers that have together received 4.3k indexed citations. Recurring topics across this work include Advanced NMR Techniques and Applications (9 papers), Synthesis and Properties of Aromatic Compounds (6 papers), Advanced Battery Materials and Technologies (6 papers), Organic Electronics and Photovoltaics (6 papers), Conducting polymers and applications (6 papers), Chemical Synthesis and Analysis (4 papers), Machine Learning in Materials Science (4 papers) and Computational Drug Discovery Methods (4 papers). The work is most often cited by research in Polymers and Plastics (688 citations), Process Chemistry and Technology (99 citations), Materials Chemistry (1.4k citations), Biomaterials (353 citations) and Electrical and Electronic Engineering (1.3k citations). Dmytro Dudenko has collaborated with scholars based in Germany, Ukraine and Poland. Frequent co-authors include Vadym Drozd, Patryk Zaleski‐Ejgierd, Taras Palasyuk, M. I. Eremets, Sergey A. Medvedev, Stanimir Bonev, Pavel G. Naumov, I. A. Troyan, Hongbo Wang and Michael Ryan Hansen. Their work appears in journals such as Macromolecules, Chemistry - A European Journal, Nature Communications, Journal of the American Chemical Society and Polymer Chemistry.
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.