J. Suñé

9.1k total citations
297 papers, 6.2k citations indexed

About

J. Suñé is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, J. Suñé has authored 297 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 276 papers in Electrical and Electronic Engineering, 43 papers in Materials Chemistry and 42 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in J. Suñé's work include Semiconductor materials and devices (196 papers), Advancements in Semiconductor Devices and Circuit Design (133 papers) and Advanced Memory and Neural Computing (117 papers). J. Suñé is often cited by papers focused on Semiconductor materials and devices (196 papers), Advancements in Semiconductor Devices and Circuit Design (133 papers) and Advanced Memory and Neural Computing (117 papers). J. Suñé collaborates with scholars based in Spain, United States and China. J. Suñé's co-authors include E. Miranda, Ernest Y. Wu, X. Aymerich, M. Nafrı́a, David Jiménez, Shibing Long, C. Cagli, Ming Liu, Ferran Martı́n and Xiaojuan Lian and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

J. Suñé

285 papers receiving 6.0k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
J. Suñé 5.9k 1.1k 829 594 407 297 6.2k
R. Degraeve 10.9k 1.9× 2.4k 2.2× 802 1.0× 593 1.0× 566 1.4× 441 11.2k
Dirk J. Wouters 4.8k 0.8× 1.9k 1.8× 991 1.2× 200 0.3× 855 2.1× 242 5.3k
Gouri Sankar Kar 3.8k 0.6× 1.5k 1.4× 432 0.5× 1.4k 2.3× 391 1.0× 315 4.6k
In-Kyeong Yoo 3.9k 0.7× 1.7k 1.6× 968 1.2× 287 0.5× 1.1k 2.6× 28 4.4k
Ming‐Jinn Tsai 5.9k 1.0× 1.7k 1.6× 1.4k 1.6× 216 0.4× 1.4k 3.5× 147 6.2k
E. Miranda 4.6k 0.8× 986 0.9× 1.2k 1.4× 178 0.3× 531 1.3× 282 4.7k
Xiangshui Miao 2.8k 0.5× 972 0.9× 1.1k 1.3× 177 0.3× 432 1.1× 226 3.4k
M. Nafrı́a 4.1k 0.7× 967 0.9× 333 0.4× 568 1.0× 235 0.6× 280 4.5k
B. Govoreanu 4.1k 0.7× 1.1k 1.1× 610 0.7× 331 0.6× 575 1.4× 169 4.3k
Chenhsin Lien 2.9k 0.5× 1.3k 1.3× 384 0.5× 361 0.6× 412 1.0× 127 3.4k

Countries citing papers authored by J. Suñé

Since Specialization
Citations

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

Fields of papers citing papers by J. Suñé

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Suñé

This figure shows the co-authorship network connecting the top 25 collaborators of J. Suñé. A scholar is included among the top collaborators of J. Suñé 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 J. Suñé. J. Suñé 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.
Miranda, E., et al.. (2026). Trap-Controlled Conduction and Metal–Insulator Transition in Superconducting Cuprate Memristors. ACS Applied Electronic Materials. 8(3). 1099–1107.
2.
Balcells, Ll., et al.. (2025). Field‐Induced Phase Transitions in Cuprate Superconductors for Cryogenic in‐Memory Computing. Small. 21(14). e2411908–e2411908. 2 indexed citations
3.
Milano, Gianluca, Luca Boarino, Luca Callegaro, et al.. (2025). A quantum resistance memristor for an intrinsically traceable International System of Units standard. Nature Nanotechnology. 20(12). 1884–1890. 1 indexed citations
4.
Suñé, J., et al.. (2024). Event-Driven Stochastic Compact Model for Resistive Switching Devices. IEEE Transactions on Electron Devices. 71(8). 4649–4654. 3 indexed citations
5.
Miranda, E., et al.. (2023). SPICE Simulation of Quantum Transport in Al 2 O 3 /HfO 2 -Based Antifuse Memory Cells. IEEE Electron Device Letters. 44(7). 1180–1183. 1 indexed citations
6.
Aguirre, Fernando, Eszter Piros, Nico Kaiser, et al.. (2023). Simulation of the effect of material properties on yttrium oxide memristor-based artificial neural networks. SHILAP Revista de lepidopterología. 1(3). 1 indexed citations
7.
Suñé, J., Fernando Aguirre, Mireia Bargalló González, F. Campabadal, & E. Miranda. (2023). Exploring Conductance Quantization Effects in Electroformed Filaments for Their Potential Application to a Resistance Standard. Advanced Quantum Technologies. 6(7). 5 indexed citations
8.
Roldán, J.B., Rodrigo Picos, E. Miranda, et al.. (2021). On the Thermal Models for Resistive Random Access Memory Circuit Simulation. Nanomaterials. 11(5). 1261–1261. 45 indexed citations
9.
Gonzalez‐Rosillo, Juan Carlos, Mariona Coll, Regina Dittmann, et al.. (2019). Engineering Oxygen Migration for Homogeneous Volume Resistive Switching in 3‐Terminal Devices. Advanced Electronic Materials. 5(9). 22 indexed citations
10.
Petzold, Stefan, E. Miranda, S. U. Sharath, et al.. (2019). Analysis and simulation of the multiple resistive switching modes occurring in HfOx-based resistive random access memories using memdiodes. Journal of Applied Physics. 125(23). 24 indexed citations
11.
Palau, Anna, Juan Carlos Gonzalez‐Rosillo, X. Granados, et al.. (2018). Electrochemical Tuning of Metal Insulator Transition and Nonvolatile Resistive Switching in Superconducting Films. ACS Applied Materials & Interfaces. 10(36). 30522–30531. 23 indexed citations
12.
Li, Yu, Meiyun Zhang, Shibing Long, et al.. (2017). Investigation on the Conductive Filament Growth Dynamics in Resistive Switching Memory via a Universal Monte Carlo Simulator. Scientific Reports. 7(1). 11204–11204. 30 indexed citations
13.
Miranda, E., J. Suñé, Chengbin Pan, et al.. (2017). Equivalent circuit model for the electron transport in 2D resistive switching material systems. 86–89. 5 indexed citations
14.
Li, Yang, Shibing Long, Yang Liu, et al.. (2015). Conductance Quantization in Resistive Random Access Memory. Nanoscale Research Letters. 10(1). 420–420. 84 indexed citations
15.
Zhang, Meiyun, Shibing Long, Guo‐Ming Wang, et al.. (2014). Statistical characteristics of reset switching in Cu/HfO2/Pt resistive switching memory. Nanoscale Research Letters. 9(1). 2500–2500. 13 indexed citations
16.
Long, Shibing, L. Perniola, C. Cagli, et al.. (2013). Voltage and Power-Controlled Regimes in the Progressive Unipolar RESET Transition of HfO2-Based RRAM. Scientific Reports. 3(1). 2929–2929. 136 indexed citations
17.
Miranda, E., David Jiménez, J. Suñé, et al.. (2012). Nonhomogeneous spatial distribution of filamentary leakage current paths in circular area Pt/HfO2/Pt capacitors. Journal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena. 31(1). 8 indexed citations
18.
Baquero, R., et al.. (2006). Facing Challenges and Requirements for in-vehicle intelligent applications. 3 indexed citations
19.
Suñé, J. & Ernest Y. Wu. (2004). Hydrogen-Release Mechanisms in the Breakdown of ThinSiO2Films. Physical Review Letters. 92(8). 87601–87601. 59 indexed citations
20.
Suñé, J., et al.. (1989). On the SiOx transition layer in abrupt Si-SiO2 chemical interface in MOS structures. Surface Science. 208(3). 463–472. 9 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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