C. Serpico

3.5k total citations
172 papers, 2.4k citations indexed

About

C. Serpico is a scholar working on Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials and Condensed Matter Physics. According to data from OpenAlex, C. Serpico has authored 172 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 127 papers in Atomic and Molecular Physics, and Optics, 89 papers in Electronic, Optical and Magnetic Materials and 77 papers in Condensed Matter Physics. Recurrent topics in C. Serpico's work include Magnetic properties of thin films (109 papers), Magnetic Properties and Applications (82 papers) and Theoretical and Computational Physics (59 papers). C. Serpico is often cited by papers focused on Magnetic properties of thin films (109 papers), Magnetic Properties and Applications (82 papers) and Theoretical and Computational Physics (59 papers). C. Serpico collaborates with scholars based in Italy, United States and France. C. Serpico's co-authors include I.D. Mayergoyz, M. d’Aquino, G. Bertotti, C. Visone, R. Bonin, Giovanni Miano, Giorgio Bertotti, Alessandro Magni, Giuseppe Milano and Patrick Thiran and has published in prestigious journals such as Physical Review Letters, Nature Communications and Applied Physics Letters.

In The Last Decade

C. Serpico

165 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
C. Serpico Italy 24 1.8k 1.1k 808 691 312 172 2.4k
H. Muraoka Japan 26 2.3k 1.3× 1.2k 1.1× 482 0.6× 595 0.9× 318 1.0× 326 2.9k
Yuri Gaididei Ukraine 29 1.9k 1.1× 572 0.5× 215 0.3× 829 1.2× 667 2.1× 97 2.4k
Hans Fangohr United Kingdom 27 2.0k 1.1× 918 0.8× 461 0.6× 1.0k 1.5× 415 1.3× 146 2.6k
Kensuke Kobayashi Japan 29 3.2k 1.8× 628 0.6× 1.3k 1.5× 920 1.3× 481 1.5× 137 3.7k
M. d’Aquino Italy 20 1.1k 0.6× 542 0.5× 512 0.6× 415 0.6× 185 0.6× 115 1.4k
Huabing Wang China 26 961 0.5× 613 0.5× 979 1.2× 1.5k 2.1× 220 0.7× 196 2.5k
M. Fatih Erden United States 18 1.1k 0.6× 374 0.3× 386 0.5× 201 0.3× 379 1.2× 50 1.9k
Xiao-Ping Liu China 17 1.4k 0.8× 652 0.6× 136 0.2× 163 0.2× 707 2.3× 25 2.1k
J.J. Miles United Kingdom 16 914 0.5× 411 0.4× 243 0.3× 282 0.4× 211 0.7× 94 1.4k
B. Pannetier France 32 2.5k 1.4× 486 0.4× 436 0.5× 2.4k 3.4× 479 1.5× 125 3.6k

Countries citing papers authored by C. Serpico

Since Specialization
Citations

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

Fields of papers citing papers by C. Serpico

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. Serpico. 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 C. Serpico. The network helps show where C. Serpico may publish in the future.

Co-authorship network of co-authors of C. Serpico

This figure shows the co-authorship network connecting the top 25 collaborators of C. Serpico. A scholar is included among the top collaborators of C. Serpico 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 C. Serpico. C. Serpico 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.
Sangiao, Soraya, J. M. De Teresa, M. Muñoz, et al.. (2025). Self-Modulation Instability in High Power Ferromagnetic Resonance of BiYIG Nanodisks. Physical Review Letters. 135(5). 56703–56703. 1 indexed citations
2.
d’Aquino, M., et al.. (2024). Mode-resolved micromagnetics study of parametric spin wave excitation in thin-film disks. Physical review. B.. 110(6). 5 indexed citations
3.
Lebrun, Romain, et al.. (2024). Non-hermiticity in spintronics: oscillation death in coupled spintronic nano-oscillators through emerging exceptional points. Nature Communications. 15(1). 971–971. 6 indexed citations
4.
Pancaldi, Matteo, et al.. (2022). Magnetization switching in the inertial regime. CINECA IRIS Institutial research information system (Parthenope University of Naples). 26 indexed citations
5.
d’Aquino, M., et al.. (2022). Impact of Magneto-Electric Coupling on Metastable Magnetic States in Thin Disks. IEEE Transactions on Magnetics. 58(8). 1–5.
6.
d’Aquino, M., et al.. (2021). A Local Gauge Description of the Interaction Between Magnetization and Electric Field in a Ferromagnet. IEEE Transactions on Magnetics. 58(2). 1–4. 2 indexed citations
7.
Scalera, Valentino, et al.. (2021). Numerical Solution of the Fokker-Planck Equation by Spectral Collocation and Finite-Element Methods for Stochastic Magnetization Dynamics. IEEE Transactions on Magnetics. 58(2). 1–4. 4 indexed citations
8.
Bruckner, Florian, et al.. (2021). Computational Micromagnetics based on Normal Modes: bridging the gap between macrospin and full spatial discretization. arXiv (Cornell University). 14 indexed citations
9.
Scalera, Valentino, et al.. (2020). Analysis in k-Space of Magnetization Dynamics Driven by Strong Terahertz Fields. IEEE Transactions on Magnetics. 57(2). 1–5. 2 indexed citations
10.
Isernia, N., Valentino Scalera, C. Serpico, & F. Villone. (2020). Energy balance during disruptions. Plasma Physics and Controlled Fusion. 62(9). 95024–95024. 1 indexed citations
11.
Hudl, Matthias, M. d’Aquino, Matteo Pancaldi, et al.. (2019). Nonlinear Magnetization Dynamics Driven by Strong Terahertz Fields. Physical Review Letters. 123(19). 197204–197204. 24 indexed citations
12.
López-Dı́az, L., et al.. (2016). Large Hysteresis effect in Synchronization of Nanocontact Vortex Oscillators by Microwave Fields. Scientific Reports. 6(1). 31630–31630. 7 indexed citations
13.
Bertotti, G., C. Serpico, & I.D. Mayergoyz. (2013). Probabilistic Aspects of Magnetization Relaxation in Single-Domain Nanomagnets. Physical Review Letters. 110(14). 147205–147205. 13 indexed citations
14.
Mayergoyz, I.D., C. Serpico, & Giorgio Bertotti. (2010). On Stability of Magnetization Dynamics in Nanoparticles. IEEE Transactions on Magnetics. 46(6). 1718–1721. 2 indexed citations
15.
Bertotti, G., C. Serpico, I.D. Mayergoyz, et al.. (2005). Magnetization Switching and Microwave Oscillations in Nanomagnets Driven by Spin-Polarized Currents. Physical Review Letters. 94(12). 127206–127206. 158 indexed citations
16.
Serpico, C., M. d’Aquino, C. Visone, & Daniele Davino. (2003). A new class of Preisach-type isotropic vector model of hysteresis. Physica B Condensed Matter. 343(1-4). 117–120. 17 indexed citations
17.
Serpico, C., I.D. Mayergoyz, & G. Bertotti. (2003). Analytical solutions of Landau–Lifshitz equation for precessional switching. Journal of Applied Physics. 93(10). 6909–6911. 41 indexed citations
18.
Mayergoyz, I.D. & C. Serpico. (2000). Eddy-current losses in magnetic conductors with abrupt magnetic transitions. IEEE Transactions on Magnetics. 36(4). 1962–1969. 2 indexed citations
19.
Miano, Giovanni, C. Serpico, & C. Visone. (1997). Cellular networks for simulating evolution partial differential equations. IOS Press eBooks. 111–117. 2 indexed citations
20.
Serpico, C., Gianluca Setti, & Patrick Thiran. (1997). Analogies between cellular neural networks and partial differential equations. Institutional Research Information System University of Ferrara (University of Ferrara). 157–162. 1 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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