Alexander V. Shapeev
Impact in
- Materials Chemistry top 0.5%
- Machine Learning in Materials Science
- 2D Materials and Applications
- X-ray Diffraction in Crystallography
- MXene and MAX Phase Materials
- Thermal properties of materials
- Graphene research and applications
- Metals and Alloys top 2%
Papers in
-
- Machine Learning in Materials Science 49
- X-ray Diffraction in Crystallography 14
- Graphene research and applications 12
- Microstructure and mechanical properties 10
- 2D Materials and Applications 10
- MXene and MAX Phase Materials 10
- Thermal properties of materials 9
- Co-authors
- Evgeny V. Podryabinkin (15 shared papers)Bohayra Mortazavi (18 shared papers)Xiaoying Zhuang (16 shared papers)Timon Rabczuk (12 shared papers)Fazel Shojaei (7 shared papers)Fritz Körmann (8 shared papers)Ivan S. Novikov (10 shared papers)Brahmanandam Javvaji (2 shared papers)
- Journals
- npj Computational Materials (10 papers)Physical review. B. (10 papers)Carbon (6 papers)Physical Review Materials (5 papers)Computational Materials Science (5 papers)
- Partner nations
- RussiaGermanyUnited States
In The Last Decade
Alexander V. Shapeev
94 papers receiving 6.0k citations
Alexander V. Shapeev's Hit Papers
Peers
Comparison fields: 5 of 94
- Materials Chemistry 5.1k
- Metals and Alloys 153
- Structural Biology 73
- Computational Theory and Mathematics 618
- Mechanical Engineering 902
Countries citing papers authored by Alexander V. Shapeev
This map shows the geographic impact of Alexander V. Shapeev'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 Alexander V. Shapeev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander V. Shapeev more than expected).
Fields of papers citing papers by Alexander V. Shapeev
This network shows the impact of papers produced by Alexander V. Shapeev. 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 Alexander V. Shapeev. The network helps show where Alexander V. Shapeev may publish in the future.
Co-authors
The 25 scholars most cited alongside Alexander V. Shapeev, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials Hit paper breakdown → | 2016 | 1008 |
| 2 | Performance and Cost Assessment of Machine Learning Interatomic Potentials Hit paper breakdown → | 2020 | 617 |
| 3 | Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles Hit paper breakdown → | 2020 | 482 |
| 4 | Active learning of linearly parametrized interatomic potentials Hit paper breakdown → | 2017 | 462 |
| 5 | Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning Hit paper breakdown → | 2019 | 280 |
| 6 | First‐Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine‐Learning Interatomic Potentials Hit paper breakdown → | 2021 | 263 |
| 7 | Moment Tensor Potentials | 2016 | 214 |
| 8 | 2020 | 179 | |
| 9 | 2020 | 167 | |
| 10 | 2019 | 149 | |
| 11 | 2020 | 127 | |
| 12 | 2019 | 126 | |
| 13 | 2019 | 108 | |
| 14 | 2019 | 97 | |
| 15 | 2023 | 91 | |
| 16 | 2019 | 83 | |
| 17 | 2019 | 75 | |
| 18 | 2022 | 72 | |
| 19 | 2020 | 68 | |
| 20 | 2020 | 55 |
About Alexander V. Shapeev
Alexander V. Shapeev is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics, Mechanics of Materials, Mechanical Engineering and Electrical and Electronic Engineering, having authored 98 papers that have together received 6.1k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (49 papers), X-ray Diffraction in Crystallography (14 papers), Graphene research and applications (12 papers), Metal and Thin Film Mechanics (11 papers), Microstructure and mechanical properties (10 papers), 2D Materials and Applications (10 papers), MXene and MAX Phase Materials (10 papers) and Thermal properties of materials (9 papers). The work is most often cited by research in Materials Chemistry (5.1k citations), Metals and Alloys (153 citations), Structural Biology (73 citations), Computational Theory and Mathematics (618 citations) and Mechanical Engineering (902 citations). Alexander V. Shapeev has collaborated with scholars based in Russia, Germany and United States. Frequent co-authors include Evgeny V. Podryabinkin, Bohayra Mortazavi, Xiaoying Zhuang, Timon Rabczuk, Fazel Shojaei, Fritz Körmann, Ivan S. Novikov, Brahmanandam Javvaji, Jörg Neugebauer and Artem R. Oganov. Their work appears in journals such as npj Computational Materials, Physical review. B., Carbon, Physical Review Materials and Computational Materials Science.
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.