Andrij Vasylenko

697 total citations
23 papers, 436 citations indexed

About

Andrij Vasylenko is a scholar working on Materials Chemistry, Electrical and Electronic Engineering and Mechanical Engineering. According to data from OpenAlex, Andrij Vasylenko has authored 23 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Materials Chemistry, 7 papers in Electrical and Electronic Engineering and 3 papers in Mechanical Engineering. Recurrent topics in Andrij Vasylenko's work include Machine Learning in Materials Science (6 papers), Graphene research and applications (5 papers) and Advanced Battery Materials and Technologies (4 papers). Andrij Vasylenko is often cited by papers focused on Machine Learning in Materials Science (6 papers), Graphene research and applications (5 papers) and Advanced Battery Materials and Technologies (4 papers). Andrij Vasylenko collaborates with scholars based in United Kingdom, Ukraine and Poland. Andrij Vasylenko's co-authors include David Quigley, Jamie Wynn, Andrew J. Morris, Paulo V. C. Medeiros, Jeremy Sloan, Quentin M. Ramasse, Stefan Jurga, Matthew S. Dyer, Matthew J. Rosseinsky and Krzysztof Kozioł and has published in prestigious journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Andrij Vasylenko

19 papers receiving 428 citations

Peers

Andrij Vasylenko
Takashi Yanase Japan
A. V. Pavlikov Russia
Jian Xiang Lian Belgium
Jae Pyung Ahn South Korea
Ana G. Silva Portugal
Megat Muhammad Ikhsan Megat Hasnan Malaysia
Cristina Palencia Spain
Yanwei Zhang China
Takashi Yanase Japan
Andrij Vasylenko
Citations per year, relative to Andrij Vasylenko Andrij Vasylenko (= 1×) peers Takashi Yanase

Countries citing papers authored by Andrij Vasylenko

Since Specialization
Citations

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

Fields of papers citing papers by Andrij Vasylenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrij Vasylenko

This figure shows the co-authorship network connecting the top 25 collaborators of Andrij Vasylenko. A scholar is included among the top collaborators of Andrij Vasylenko 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 Andrij Vasylenko. Andrij Vasylenko 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.
Vasylenko, Andrij, Dmytro Antypov, Sven Schewe, et al.. (2025). Digital features of chemical elements extracted from local geometries in crystal structures. Digital Discovery. 4(2). 477–485. 1 indexed citations
2.
Antypov, Dmytro, Andrij Vasylenko, Christopher M. Collins, et al.. (2025). Discovery of Crystalline Inorganic Solids in the Digital Age. Accounts of Chemical Research. 58(9). 1355–1365.
3.
Han, Guopeng, Luke M. Daniels, Andrij Vasylenko, et al.. (2024). Enhancement of Low Temperature Superionic Conductivity by Suppression of Li Site Ordering in Li7Si2–xGexS7I. Angewandte Chemie International Edition. 63(37). e202409372–e202409372. 4 indexed citations
4.
Antypov, Dmytro, Katie Atkinson, Matthew S. Dyer, et al.. (2024). Hierarchical Supervised Monte Carlo Ensemble Learning. 1764–1771.
5.
Antypov, Dmytro, Christopher M. Collins, Andrij Vasylenko, et al.. (2024). Statistically Derived Proxy Potentials Accelerate Geometry Optimization of Crystal Structures. ChemPhysChem. 25(12). e202400254–e202400254. 2 indexed citations
6.
Antypov, Dmytro, Katie Atkinson, Matthew S. Dyer, et al.. (2024). The Theory of Probabilistic Hierarchical Supervised Ensemble Learning. 1182–1187. 1 indexed citations
7.
Vasylenko, Andrij, Christopher M. Collins, Michael W. Gaultois, et al.. (2024). Inferring energy–composition relationships with Bayesian optimization enhances exploration of inorganic materials. The Journal of Chemical Physics. 160(5). 4 indexed citations
8.
Vasylenko, Andrij, Dmytro Antypov, Vladimir V. Gusev, et al.. (2023). Element selection for functional materials discovery by integrated machine learning of elemental contributions to properties. npj Computational Materials. 9(1). 8 indexed citations
9.
Pshyk, Oleksandr, Andrij Vasylenko, Babak Bakhit, et al.. (2022). High-entropy transition metal nitride thin films alloyed with Al: Microstructure, phase composition and mechanical properties. Materials & Design. 219. 110798–110798. 37 indexed citations
10.
Han, Guopeng, Andrij Vasylenko, Alex R. Neale, et al.. (2021). Extended Condensed Ultraphosphate Frameworks with Monovalent Ions Combine Lithium Mobility with High Computed Electrochemical Stability. Journal of the American Chemical Society. 143(43). 18216–18232. 9 indexed citations
11.
Perez, Arnaud J., Andrij Vasylenko, T. Wesley Surta, et al.. (2021). Ordered Oxygen Vacancies in the Lithium-Rich Oxide Li4CuSbO5.5, a Triclinic Structure Type Derived from the Cubic Rocksalt Structure. Inorganic Chemistry. 60(24). 19022–19034. 1 indexed citations
12.
Vasylenko, Andrij, Jacinthe Gamon, Vladimir V. Gusev, et al.. (2021). Element selection for crystalline inorganic solid discovery guided by unsupervised machine learning of experimentally explored chemistry. Nature Communications. 12(1). 5561–5561. 54 indexed citations
13.
Gamon, Jacinthe, Matthew S. Dyer, Andrij Vasylenko, et al.. (2021). Li 4.3 AlS 3.3 Cl 0.7 : A Sulfide–Chloride Lithium Ion Conductor with Highly Disordered Structure and Increased Conductivity. Chemistry of Materials. 33(22). 8733–8744. 17 indexed citations
14.
Kashtiban, Reza J., Maria G. Burdanova, Andrij Vasylenko, et al.. (2021). Linear and Helical Cesium Iodide Atomic Chains in Ultranarrow Single-Walled Carbon Nanotubes: Impact on Optical Properties. ACS Nano. 15(8). 13389–13398. 38 indexed citations
15.
Vasylenko, Andrij, Jamie Wynn, Paulo V. C. Medeiros, et al.. (2017). Encapsulated nanowires: Boosting electronic transport in carbon nanotubes. Physical review. B.. 95(12). 22 indexed citations
16.
Wynn, Jamie, Paulo V. C. Medeiros, Andrij Vasylenko, et al.. (2017). Phase diagram of germanium telluride encapsulated in carbon nanotubes from first-principles searches. Physical Review Materials. 1(7). 14 indexed citations
17.
Medeiros, Paulo V. C., Jamie Wynn, Andrij Vasylenko, et al.. (2017). Single-Atom Scale Structural Selectivity in Te Nanowires Encapsulated Inside Ultranarrow, Single-Walled Carbon Nanotubes. ACS Nano. 11(6). 6178–6185. 78 indexed citations
18.
Iatsunskyi, Igor, Andrij Vasylenko, Roman Viter, et al.. (2017). Tailoring of the electronic properties of ZnO-polyacrylonitrile nanofibers: Experiment and theory. Applied Surface Science. 411. 494–501. 37 indexed citations
19.
Medeiros, Paulo V. C., Jamie Wynn, Andrij Vasylenko, et al.. (2017). Extreme Te nanowires encapsulated within ultra-narrow single-walled carbon nanotubes. 1 indexed citations
20.
Maciejewska, Barbara M., Małgorzata Jasiurkowska-Delaporte, Andrij Vasylenko, Krzysztof Kozioł, & Stefan Jurga. (2014). Experimental and theoretical studies on the mechanism for chemical oxidation of multiwalled carbon nanotubes. RSC Advances. 4(55). 28826–28831. 36 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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