Natalia Kireeva
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Molecular Biology
- Electrical and Electronic Engineering
- Catalysis top 10%
- Co-authors
- Alexandre VarnekIgor I. BaskinВ. С. ПервовVitaly P. Solov’evА. Yu. TsivadzeIgor V. TetkoGilles MarcouDragos Horvath
- Topics
- Computational Drug Discovery Methods (11 papers)Advancements in Battery Materials (7 papers)Machine Learning in Materials Science (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPhysical Chemistry Chemical PhysicsIndustrial & Engineering Chemistry Research
In The Last Decade
Natalia Kireeva
28 papers receiving 526 citations
Peers
Comparison fields: 5 of 87
- Computational Theory and Mathematics 228
- Materials Chemistry 193
- Molecular Biology 106
- Electrical and Electronic Engineering 103
- Catalysis 80
Countries citing papers authored by Natalia Kireeva
This map shows the geographic impact of Natalia Kireeva'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 Natalia Kireeva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalia Kireeva more than expected).
Fields of papers citing papers by Natalia Kireeva
This network shows the impact of papers produced by Natalia Kireeva. 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 Natalia Kireeva. The network helps show where Natalia Kireeva may publish in the future.
Co-authorship network of co-authors of Natalia Kireeva
This figure shows the co-authorship network connecting the top 25 collaborators of Natalia Kireeva. A scholar is included among the top collaborators of Natalia Kireeva 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 Natalia Kireeva. Natalia Kireeva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 6 | |
| 4 | 0 | |
| 5 | 9 | |
| 6 | 10 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 50 | |
| 10 | 19 | |
| 11 | 9 | |
| 12 | 9 | |
| 13 | 4 | |
| 14 | 3 | |
| 15 | 108 | |
| 16 | 14 | |
| 17 | 15 | |
| 18 | 47 | |
| 19 | 12 | |
| 20 | 17 |
About Natalia Kireeva
Natalia Kireeva is a scholar working on Filtration and Separation, Computational Theory and Mathematics and Catalysis, having authored 30 papers that have together received 536 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Advancements in Battery Materials (7 papers) and Machine Learning in Materials Science (5 papers). The work is most often cited by research in Filtration and Separation (33 citations), Computational Theory and Mathematics (228 citations) and Catalysis (80 citations). Natalia Kireeva has collaborated with scholars based in Russia, France and Germany. Frequent co-authors include Alexandre Varnek, Igor I. Baskin, В. С. Первов, Vitaly P. Solov’ev, А. Yu. Tsivadze, Igor V. Tetko, Gilles Marcou, Dragos Horvath, Héléna A. Gaspar and С. Л. Кузнецов. Their work appears in journals such as SHILAP Revista de lepidopterología, Physical Chemistry Chemical Physics and Industrial & Engineering Chemistry Research.
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.