Alexander E. Mayer

3.6k total citations
134 papers, 2.4k citations indexed

About

Alexander E. Mayer is a scholar working on Materials Chemistry, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Alexander E. Mayer has authored 134 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 107 papers in Materials Chemistry, 37 papers in Mechanical Engineering and 31 papers in Mechanics of Materials. Recurrent topics in Alexander E. Mayer's work include Microstructure and mechanical properties (70 papers), High-Velocity Impact and Material Behavior (58 papers) and Ion-surface interactions and analysis (22 papers). Alexander E. Mayer is often cited by papers focused on Microstructure and mechanical properties (70 papers), High-Velocity Impact and Material Behavior (58 papers) and Ion-surface interactions and analysis (22 papers). Alexander E. Mayer collaborates with scholars based in Russia, Belgium and United States. Alexander E. Mayer's co-authors include Vasiliy S. Krasnikov, Polina N. Mayer, Victor V. Pogorelko, Elijah Borodin, K. V. Khishchenko, A. P. Yalovets, J.A. Van Wyk, P.M. Spear, G.S. Woods and I. Kiflawi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and Journal of Applied Physics.

In The Last Decade

Alexander E. Mayer

127 papers receiving 2.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Alexander E. Mayer Russia 30 1.9k 1.0k 702 345 320 134 2.4k
Saryu Fensin United States 29 1.5k 0.8× 1.4k 1.4× 534 0.8× 448 1.3× 248 0.8× 124 2.3k
Lisa Ventelon France 26 2.0k 1.0× 959 1.0× 434 0.6× 184 0.5× 122 0.4× 34 2.3k
Ellen K Cerreta United States 36 2.8k 1.4× 1.7k 1.7× 1.1k 1.6× 266 0.8× 377 1.2× 110 3.3k
M. Victoria Switzerland 31 2.8k 1.5× 1.3k 1.3× 713 1.0× 337 1.0× 175 0.5× 90 3.5k
István Groma Hungary 30 2.5k 1.3× 1.3k 1.3× 1.0k 1.4× 340 1.0× 149 0.5× 85 3.0k
Pedro Peralta United States 27 1.3k 0.7× 1.0k 1.0× 800 1.1× 197 0.6× 110 0.3× 122 2.0k
С. В. Разоренов Russia 27 2.3k 1.2× 892 0.9× 1.3k 1.8× 252 0.7× 864 2.7× 190 3.0k
Joel V. Bernier United States 28 1.8k 0.9× 1.4k 1.4× 834 1.2× 99 0.3× 281 0.9× 72 2.5k
Charlotte Becquart France 34 4.0k 2.1× 1.5k 1.5× 561 0.8× 409 1.2× 188 0.6× 99 4.4k
В. М. Чернов Russia 23 2.2k 1.1× 1.2k 1.2× 396 0.6× 359 1.0× 61 0.2× 196 2.5k

Countries citing papers authored by Alexander E. Mayer

Since Specialization
Citations

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

Fields of papers citing papers by Alexander E. Mayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexander E. Mayer. 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 E. Mayer. The network helps show where Alexander E. Mayer may publish in the future.

Co-authorship network of co-authors of Alexander E. Mayer

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander E. Mayer. A scholar is included among the top collaborators of Alexander E. Mayer 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 E. Mayer. Alexander E. Mayer 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.
Mayer, Alexander E., et al.. (2026). Anisotropy of Phase Transformation in Aluminum and Copper under Shock Compression: Atomistic Simulations and Neural Network Model. Computers, materials & continua/Computers, materials & continua (Print). 87(1). 1–10.
2.
Mayer, Alexander E., et al.. (2025). Experimental and numerical study of stress wave generation and attenuation in copper during laser shock peening. Journal of Applied Physics. 137(6). 1 indexed citations
3.
Mayer, Alexander E., et al.. (2025). Tensor equation of state for copper and aluminum. Computational Materials Science. 253. 113845–113845. 3 indexed citations
4.
Черепанов, А. Н., et al.. (2025). Dynamic Plasticity and Fracture of Al 7075 and V95T1 Alloys: High-Velocity Impact Experiments. SHILAP Revista de lepidopterología. 5(1). 6–6.
5.
Krasnikov, Vasiliy S., et al.. (2025). Mechanical response of metastable grain boundaries under shear deformation: A multi-scale study. International Journal of Plasticity. 195. 104524–104524.
6.
Pogorelko, Victor V., et al.. (2024). Dynamic deformation and fracture of brass: Experiments and dislocation-based model. International Journal of Plasticity. 183. 104165–104165. 4 indexed citations
7.
Krasnikov, Vasiliy S., et al.. (2024). Modeling of shock wave propagation in porous magnesium based on artificial neural network. Mechanics of Materials. 191. 104953–104953. 5 indexed citations
8.
Mayer, Alexander E., et al.. (2024). Application of deep learning for technological parameter optimization of laser shock peening of Ti-6Al-4V alloy. Frattura ed Integrità Strutturale. 18(70). 121–132. 2 indexed citations
9.
Chatziioannou, Vasileios, et al.. (2024). A cello bowing playback device? Motion capture meets robotic arm. 2749–2756. 1 indexed citations
10.
11.
Pogorelko, Victor V., et al.. (2023). Modified Taylor Impact Tests with Profiled Copper Cylinders: Experiment and Optimization of Dislocation Plasticity Model. Materials. 16(16). 5602–5602. 10 indexed citations
12.
Pogorelko, Victor V., et al.. (2023). Examination of machine learning method for identification of material model parameters. International Journal of Mechanical Sciences. 265. 108912–108912. 12 indexed citations
13.
Krasnikov, Vasiliy S., et al.. (2023). Shear Strength of Al–Cu Alloys with Different Types of Hardening Precipitates: Molecular Dynamics and Continuum Modeling. Bulletin of the Russian Academy of Sciences Physics. 87(11). 1594–1600.
14.
Mayer, Alexander E.. (2023). Influence of preliminary compressive deformation on the spall strength of aluminum single crystal. Scripta Materialia. 242. 115905–115905. 4 indexed citations
15.
Krasnikov, Vasiliy S. & Alexander E. Mayer. (2023). Initiation and Mechanisms of Plasticity in Bimetallic Al-Cu Composite. Metals. 13(1). 102–102. 3 indexed citations
16.
Mayer, Alexander E., et al.. (2022). Investigating the cello position, bow motion and cellist posture using motion capture. Proceedings of meetings on acoustics. 49. 35013–35013. 3 indexed citations
17.
Mayer, Alexander E., et al.. (2018). Experimental Technique to Study the Interaction Between a Bubble and the Particle-Laden Interface. Frontiers in Chemistry. 6. 348–348. 5 indexed citations
18.
Chung, M. S., et al.. (2012). Dielectric effect on electric fields in the vicinity of the metal–vacuum–dielectric junction. Ultramicroscopy. 132. 41–47. 7 indexed citations
19.
Chung, M. S., et al.. (2011). Enhanced field emission and breakdown near the contact between metal and dielectric. Repository of the University of Namur. 23–24. 1 indexed citations
20.
Chung, M. S., Soon Cheol Hong, P. H. Cutler, et al.. (2006). Theoretical analysis of triple junction field emission for a type of cold cathode. Journal of Vacuum Science & Technology B Microelectronics and Nanometer Structures Processing Measurement and Phenomena. 24(2). 909–912. 13 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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2026