Alexander V. Shapeev

8.6k total citations · 6 hit papers
98 papers, 6.1k citations indexed

About

Alexander V. Shapeev is a scholar working on Materials Chemistry, Atomic and Molecular Physics, and Optics and Mechanics of Materials. According to data from OpenAlex, Alexander V. Shapeev has authored 98 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 82 papers in Materials Chemistry, 20 papers in Atomic and Molecular Physics, and Optics and 17 papers in Mechanics of Materials. Recurrent topics in Alexander V. Shapeev's work include Machine Learning in Materials Science (49 papers), X-ray Diffraction in Crystallography (14 papers) and Graphene research and applications (12 papers). Alexander V. Shapeev is often cited by papers focused on Machine Learning in Materials Science (49 papers), X-ray Diffraction in Crystallography (14 papers) and Graphene research and applications (12 papers). Alexander V. Shapeev collaborates with scholars based in Russia, Germany and United States. Alexander V. Shapeev's co-authors include Evgeny V. Podryabinkin, Bohayra Mortazavi, Xiaoying Zhuang, Timon Rabczuk, Fazel Shojaei, Ivan S. Novikov, Fritz Körmann, Brahmanandam Javvaji, Jörg Neugebauer and Artem R. Oganov and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Advanced Materials and The Journal of Chemical Physics.

In The Last Decade

Alexander V. Shapeev

94 papers receiving 6.0k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

2016 1.0k citations Alexander V. Shapeev profile →
Performance and Cost Assessment of Machine Learning Interatomic Potentials

2020 617 citations Alexander V. Shapeev et al. profile →
Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles

2020 482 citations Bohayra Mortazavi, Brahmanandam Javvaji et al. Nano Energy profile →
Active learning of linearly parametrized interatomic potentials

2017 462 citations Evgeny V. Podryabinkin, Alexander V. Shapeev profile →
Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning

2019 280 citations Evgeny V. Podryabinkin, Alexander V. Shapeev et al. Physical review. B. profile →
First‐Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine‐Learning Interatomic Potentials

2021 263 citations Bohayra Mortazavi, Evgeny V. Podryabinkin et al. profile →

Peers

Countries citing papers authored by Alexander V. Shapeev

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Alexander V. Shapeev

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander V. Shapeev. A scholar is included among the top collaborators of Alexander V. Shapeev 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 Alexander V. Shapeev. Alexander V. Shapeev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Tuning of mechanical properties of doped PbTe-based thermoelectric materials driven by intrinsic defects 2025 ·Journal of Materials Chemistry A ·Ilya V. Chepkasov, (unknown), (unknown), (unknown), (unknown), Alexander V. Shapeev, (unknown), Artem R. Oganov, Z. Dashevsky, Dmitry G. Kvashnin, Alexander G. Kvashnin	0
2	Towards reliable calculations of thermal rate constants: Ring polymer molecular dynamics for the OH + HBr → Br + H2O reaction 2024 ·Chemical Physics Letters ·(unknown), (unknown), Yury V. Suleimanov, Alexander V. Shapeev	4
3	Exhaustive search for novel multicomponent alloys with brute force and machine learning 2024 ·npj Computational Materials ·(unknown), (unknown), Alexander V. Shapeev, Evgeny V. Podryabinkin	2
4	Electronic Moment Tensor Potentials include both electronic and vibrational degrees of freedom 2024 ·npj Computational Materials ·Prashanth Srinivasan, (unknown), Blazej Grabowski, Alexander V. Shapeev	6
5	Equivariant tensor network potentials 2024 ·Machine Learning Science and Technology ·(unknown), Alexander V. Shapeev	4
6	Anharmonicity in bcc refractory elements: A detailed ab initio analysis 2023 ·Physical review. B. ·Prashanth Srinivasan, Alexander V. Shapeev, Jörg Neugebauer, Fritz Körmann, Blazej Grabowski	13
7	Machine learning-driven synthesis of TiZrNbHfTaC5 high-entropy carbide 2023 ·npj Computational Materials ·A. Ya. Pak, (unknown), (unknown), (unknown), (unknown), (unknown), (unknown), Alexander V. Shapeev, Alexander G. Kvashnin	31
8	Atomistic modeling of the mechanical properties: the rise of machine learning interatomic potentials 2023 ·Materials Horizons ·Bohayra Mortazavi, Xiaoying Zhuang, Timon Rabczuk, Alexander V. Shapeev	91
9	Highly anisotropic mechanical and optical properties of 2D NbOX2 (X = Cl, Br, I) revealed by first-principle 2022 ·Nanotechnology ·Bohayra Mortazavi, Masoud Shahrokhi, Brahmanandam Javvaji, Alexander V. Shapeev, Xiaoying Zhuang	23
10	Machine learning for deep elastic strain engineering of semiconductor electronic band structure and effective mass 2021 ·npj Computational Materials ·Evgenii Tsymbalov, Zhe Shi, Ming Dao, Subra Suresh, Ju Li, Alexander V. Shapeev	28
11	Bayesian learning of thermodynamic integration and numerical convergence for accurate phase diagrams 2021 ·Physical review. B. ·(unknown), (unknown), (unknown), Alexander V. Shapeev	8
12	Validation of moment tensor potentials for fcc and bcc metals using EXAFS spectra 2021 ·arXiv (Cornell University) ·Alexander V. Shapeev, Dmitry Bocharov, Alexei Kuzmin	8
13	Metallization of diamond 2020 ·Proceedings of the National Academy of Sciences ·Zhe Shi, Ming Dao, Evgenii Tsymbalov, Alexander V. Shapeev, Ju Li, Subra Suresh	35
14	Young’s Modulus and Tensile Strength of Ti₃C₂ MXene Nanosheets As Revealed by In Situ TEM Probing, AFM Nanomechanical Mapping, and Theoretical Calculations 2020 ·Nano Letters ·Konstantin L. Firestein, Joel E. von Treifeldt, Dmitry G. Kvashnin, Joseph F. S. Fernando, Chao Zhang, Alexander G. Kvashnin, Evgeny V. Podryabinkin, Alexander V. Shapeev, Dumindu P. Siriwardena, Павел Б. Сорокин, Dmitri Golberg	167
15	Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles breakdown → 2020 ·Nano Energy ·Bohayra Mortazavi, Brahmanandam Javvaji, Fazel Shojaei, Timon Rabczuk, Alexander V. Shapeev, Xiaoying Zhuang	482
16	Deep elastic strain engineering of bandgap through machine learning 2019 ·Proceedings of the National Academy of Sciences ·Zhe Shi, Evgenii Tsymbalov, Ming Dao, Subra Suresh, Alexander V. Shapeev, Ju Li	83
17	Automated Calculation of Thermal Rate Coefficients using Ring Polymer Molecular Dynamics and Machine-Learning Interatomic Potentials with Active Learning: Application to Thermally Activated Gas Phase Chemical Reactions. 2018 ·arXiv (Cornell University) ·Ivan S. Novikov, Yury V. Suleimanov, Alexander V. Shapeev	1
18	Active learning of linear interatomic potentials 2016 ·arXiv (Cornell University) ·Evgeny V. Podryabinkin, Alexander V. Shapeev	2
19	Moment Tensor Potentials 2016 ·arXiv (Cornell University) ·Alexander V. Shapeev	214
20	Consistent Energy-Based Atomistic/Continuum Coupling for Two-Body Potential: 1D and 2D Case 2010 ·arXiv (Cornell University) ·Alexander V. Shapeev	11

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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