A. Yu. Kuksin

1.7k total citations
51 papers, 1.4k citations indexed

About

A. Yu. Kuksin is a scholar working on Materials Chemistry, Aerospace Engineering and Geophysics. According to data from OpenAlex, A. Yu. Kuksin has authored 51 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Materials Chemistry, 10 papers in Aerospace Engineering and 9 papers in Geophysics. Recurrent topics in A. Yu. Kuksin's work include Nuclear Materials and Properties (18 papers), Microstructure and mechanical properties (16 papers) and Fusion materials and technologies (14 papers). A. Yu. Kuksin is often cited by papers focused on Nuclear Materials and Properties (18 papers), Microstructure and mechanical properties (16 papers) and Fusion materials and technologies (14 papers). A. Yu. Kuksin collaborates with scholars based in Russia, United States and Australia. A. Yu. Kuksin's co-authors include A. V. Yanilkin, Vladimir Stegailov, Sergey Starikov, Daria Smirnova, G. É. Norman, Vasiliy S. Krasnikov, Alexander E. Mayer, Svetlana Starikovskaia, Maryia Nudnova and Andrei Starikovskii and has published in prestigious journals such as Nano Letters, Journal of Applied Physics and Physical Review B.

In The Last Decade

A. Yu. Kuksin

50 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Yu. Kuksin Russia 22 1.0k 342 275 203 192 51 1.4k
Sergey Starikov Russia 26 1.1k 1.0× 393 1.1× 247 0.9× 212 1.0× 172 0.9× 85 1.7k
A. V. Yanilkin Russia 21 1.1k 1.1× 321 0.9× 164 0.6× 246 1.2× 89 0.5× 77 1.3k
H. Grimmer Switzerland 24 1.1k 1.0× 492 1.4× 143 0.5× 267 1.3× 222 1.2× 86 1.8k
Mihai‐Cosmin Marinica France 28 2.3k 2.2× 696 2.0× 164 0.6× 220 1.1× 153 0.8× 66 2.7k
Florian Kargl Germany 20 1.2k 1.1× 617 1.8× 221 0.8× 61 0.3× 82 0.4× 77 1.6k
K. O. E. Henriksson Finland 18 1.1k 1.1× 405 1.2× 98 0.4× 285 1.4× 63 0.3× 34 1.3k
R. Ravelo United States 18 1.3k 1.3× 387 1.1× 126 0.5× 575 2.8× 136 0.7× 45 1.9k
A. Litnovsky Germany 28 1.7k 1.7× 612 1.8× 280 1.0× 479 2.4× 360 1.9× 133 2.3k
D. Herlach Germany 19 869 0.8× 469 1.4× 213 0.8× 581 2.9× 151 0.8× 108 1.7k
Toru Sasaki Japan 16 486 0.5× 102 0.3× 116 0.4× 195 1.0× 375 2.0× 198 1.4k

Countries citing papers authored by A. Yu. Kuksin

Since Specialization
Citations

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

Fields of papers citing papers by A. Yu. Kuksin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Yu. Kuksin. 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 A. Yu. Kuksin. The network helps show where A. Yu. Kuksin may publish in the future.

Co-authorship network of co-authors of A. Yu. Kuksin

This figure shows the co-authorship network connecting the top 25 collaborators of A. Yu. Kuksin. A scholar is included among the top collaborators of A. Yu. Kuksin 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 A. Yu. Kuksin. A. Yu. Kuksin 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.
Kuksin, A. Yu., et al.. (2023). Preparation and investigation of properties of resveratrol and solubilizers compositions. Russian Journal of Biotherapy. 22(2). 65–73. 1 indexed citations
2.
Starikov, Sergey, et al.. (2017). Multiscale Modeling of Uranium Mononitride: Point Defects Diffusion, Self-Diffusion, Phase Composition. Defect and diffusion forum/Diffusion and defect data, solid state data. Part A, Defect and diffusion forum. 375. 101–113. 6 indexed citations
3.
Kuksin, A. Yu., et al.. (2016). Glide mobility of the 1/2[1 1 0](0 0 1) edge dislocation in UO2 from molecular dynamics simulation. International Journal of Plasticity. 89. 85–95. 34 indexed citations
4.
Zograf, George, Mikhail V. Rybin, Dmitry Zuev, et al.. (2016). Modeling of formation mechanism and optical properties of Si/Au core-shell nanoparticles. 330. 460–463. 3 indexed citations
5.
Kuksin, A. Yu. & A. V. Yanilkin. (2016). Formation of Defects in Displacement Cascades in Molybdenum: Simulation of Molecular Dynamics. The Physics of Metals and Metallography. 117(3). 230–237. 4 indexed citations
6.
Kuksin, A. Yu., et al.. (2016). Nucleation and the spall strength of liquid metals. Journal of Physics Conference Series. 774. 12030–12030. 3 indexed citations
7.
Kuksin, A. Yu. & A. V. Yanilkin. (2015). Dislocation nucleation and motion in metals and alloys at high-rate deformation: Molecular dynamic simulation. Mechanics of Solids. 50(1). 44–51. 17 indexed citations
8.
Kuksin, A. Yu., et al.. (2015). The diffusion of point defects in uranium mononitride: Combination of DFT and atomistic simulation with novel potential. Journal of Alloys and Compounds. 658. 385–394. 30 indexed citations
9.
Smirnova, Daria, A. Yu. Kuksin, & Sergey Starikov. (2014). Investigation of point defects diffusion in bcc uranium and U–Mo alloys. Journal of Nuclear Materials. 458. 304–311. 52 indexed citations
10.
Smirnova, Daria, A. Yu. Kuksin, Sergey Starikov, et al.. (2013). A ternary EAM interatomic potential for U–Mo alloys with xenon. Modelling and Simulation in Materials Science and Engineering. 21(3). 35011–35011. 71 indexed citations
11.
Инсепов, З., J. Rest, Abdellatif M. Yacout, et al.. (2012). Atomistic and Kinetic Simulations of Radiation Damage in Molybdenum. MRS Proceedings. 1444. 1 indexed citations
12.
Krasnikov, Vasiliy S., et al.. (2012). Dynamics and Kinetics of Dislocations in Metals and Alloys Under Dynamic Loading. MRS Proceedings. 1535. 1 indexed citations
13.
Инсепов, З., J. Rest, Abdellatif M. Yacout, et al.. (2011). Derivation of kinetic coefficients by atomistic methods for studying defect behavior in Mo. Journal of Nuclear Materials. 425(1-3). 41–47. 10 indexed citations
14.
Starikov, Sergey, З. Инсепов, J. Rest, et al.. (2011). Radiation-induced damage and evolution of defects in Mo. Physical Review B. 84(10). 49 indexed citations
15.
Kuksin, A. Yu., G. É. Norman, V. V. Pisarev, Vladimir Stegailov, & A. V. Yanilkin. (2010). Theory and molecular dynamics modeling of spall fracture in liquids. Physical Review B. 82(17). 79 indexed citations
16.
Pisarev, V. V., A. Yu. Kuksin, G. É. Norman, et al.. (2009). MICROSCOPIC THEORY AND KINETIC MODEL OF SPALL IN LIQUIDS. AIP conference proceedings. 801–804. 1 indexed citations
17.
Kuksin, A. Yu., G. É. Norman, Vladimir Stegailov, & A. V. Yanilkin. (2007). Modeling of Al crystal fracture under high-rate strain based on atomistic simulations. Bulletin of the American Physical Society. 3 indexed citations
18.
Kuksin, A. Yu., G. É. Norman, & Vladimir Stegailov. (2007). The phase diagram and spinodal decomposition of metastable states of Lennard-Jones system. High Temperature. 45(1). 37–48. 30 indexed citations
19.
Kuksin, A. Yu. & A. V. Yanilkin. (2007). Kinetic model of fracture at high strain rates in the example of crystalline aluminum. Doklady Physics. 52(4). 186–190. 13 indexed citations
20.
Norman, G. É., A. Yu. Kuksin, Vladimir Stegailov, et al.. (2007). ATOMISTIC SIMULATION OF PLASTICITY AND FRACTURE OF CRYSTALLINE AND POLYCRYSTALLINE METALS UNDER HIGH STRAIN RATE. AIP conference proceedings. 329–334. 4 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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