Fabio Carta

821 total citations
23 papers, 582 citations indexed

About

Fabio Carta is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Polymers and Plastics. According to data from OpenAlex, Fabio Carta has authored 23 papers receiving a total of 582 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Electrical and Electronic Engineering, 17 papers in Materials Chemistry and 6 papers in Polymers and Plastics. Recurrent topics in Fabio Carta's work include Advanced Memory and Neural Computing (14 papers), Phase-change materials and chalcogenides (11 papers) and Transition Metal Oxide Nanomaterials (6 papers). Fabio Carta is often cited by papers focused on Advanced Memory and Neural Computing (14 papers), Phase-change materials and chalcogenides (11 papers) and Transition Metal Oxide Nanomaterials (6 papers). Fabio Carta collaborates with scholars based in United States, Taiwan and Switzerland. Fabio Carta's co-authors include M. BrightSky, Huai‐Yu Cheng, Wei-Chih Chien, Ioannis Kymissis, Hsiang-Lan Lung, Robert L. Bruce, Htay Hlaing, Chang‐Hyun Kim, James Hone and Chang‐Yong Nam and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Fabio Carta

23 papers receiving 554 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fabio Carta United States 12 526 342 116 50 47 23 582
Jing Wen China 12 401 0.8× 255 0.7× 124 1.1× 32 0.6× 43 0.9× 28 460
Maksim Andreev South Korea 9 447 0.8× 245 0.7× 59 0.5× 64 1.3× 45 1.0× 13 517
Jau-Yi Wu Taiwan 8 388 0.7× 216 0.6× 56 0.5× 40 0.8× 53 1.1× 21 474
Mattia Boniardi Italy 15 617 1.2× 588 1.7× 214 1.8× 72 1.4× 46 1.0× 25 685
Pei-Jer Tzeng Taiwan 16 798 1.5× 231 0.7× 89 0.8× 76 1.5× 15 0.3× 61 822
Shunli Ma China 6 386 0.7× 212 0.6× 46 0.4× 61 1.2× 61 1.3× 13 467
Kil‐Su Jung South Korea 7 370 0.7× 184 0.5× 54 0.5× 47 0.9× 48 1.0× 12 429
Jin Feng Leong Singapore 11 496 0.9× 290 0.8× 53 0.5× 78 1.6× 62 1.3× 17 604
Alvaro Padilla United States 10 705 1.3× 330 1.0× 147 1.3× 52 1.0× 60 1.3× 12 755
Jianchi Zhang China 7 1.0k 1.9× 409 1.2× 65 0.6× 90 1.8× 77 1.6× 15 1.1k

Countries citing papers authored by Fabio Carta

Since Specialization
Citations

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

Fields of papers citing papers by Fabio Carta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Carta

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Carta. A scholar is included among the top collaborators of Fabio Carta 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 Fabio Carta. Fabio Carta 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.
Cheng, Huai‐Yu, A. Majumdar, J. Su, et al.. (2024). State-Independent Low Resistance Drift SiSbTe Phase Change Memory for Analog In-Memory Computing Applications. 1–2. 3 indexed citations
2.
Rasch, Malte J., et al.. (2024). Fast and robust analog in-memory deep neural network training. Nature Communications. 15(1). 7133–7133. 7 indexed citations
3.
Bragaglia, Valeria, Malte J. Rasch, Fabio Carta, et al.. (2024). Analog Resistive Switching Devices for Training Deep Neural Networks with the Novel Tiki-Taka Algorithm. Nano Letters. 24(3). 866–872. 12 indexed citations
4.
Gallo, Manuel Le, Corey Lammie, Julian Büchel, et al.. (2023). Using the IBM analog in-memory hardware acceleration kit for neural network training and inference. SHILAP Revista de lepidopterología. 1(4). 27 indexed citations
5.
Agrawal, Ankur, Monodeep Kar, Kyu Hyun Kim, et al.. (2023). A Switched-Capacitor Integer Compute Unit with Decoupled Storage and Arithmetic for Cloud AI Inference in 5nm CMOS. 1–2. 2 indexed citations
6.
Cheng, Huai‐Yu, Fabio Carta, Wei-Chih Chien, Hsiang-Lan Lung, & M. BrightSky. (2019). 3D cross-point phase-change memory for storage-class memory. Journal of Physics D Applied Physics. 52(47). 473002–473002. 85 indexed citations
7.
Chien, Wei-Chih, C. W. Yeh, Cheol‐Min Yang, et al.. (2019). Comprehensive Scaling Study on 3D Cross-Point PCM toward 1Znm Node for SCM Applications. T60–T61. 20 indexed citations
8.
Bruce, Robert L., Takeshi Masuda, Nanbo Gong, et al.. (2019). Confined PCM-based Analog Synaptic Devices offering Low Resistance-drift and 1000 Programmable States for Deep Learning. T66–T67. 55 indexed citations
9.
Gong, Nanbo, Wei-Chih Chien, A. Ray, et al.. (2019). Superb Endurance and Appropriate Vth of PCM Pillar Cell using Buffer Layer for 3D Cross-Point Memory. 1–4. 4 indexed citations
10.
Chien, Wei-Chih, Nanbo Gong, C. W. Yeh, et al.. (2019). Solution for PCM and OTS Intermixing on Cross-Point Phase Change Memory. 6 indexed citations
11.
Yeh, C. W., Wei-Chih Chien, Robert L. Bruce, et al.. (2018). High Endurance Self-Heating OTS-PCM Pillar Cell for 3D Stackable Memory. 205–206. 18 indexed citations
12.
Cheng, Huai‐Yu, Wei-Chih Chien, C. W. Yeh, et al.. (2018). Ultra-High Endurance and Low I<inf>OFF</inf> Selector based on AsSeGe Chalcogenides for Wide Memory Window 3D Stackable Crosspoint Memory. 37.3.1–37.3.4. 38 indexed citations
13.
Chien, Wei-Chih, C. W. Yeh, Robert L. Bruce, et al.. (2018). A Study on OTS-PCM Pillar Cell for 3-D Stackable Memory. IEEE Transactions on Electron Devices. 65(11). 5172–5179. 39 indexed citations
14.
Cheng, Huai‐Yu, Wei-Chih Chien, Erh-Kun Lai, et al.. (2017). An ultra high endurance and thermally stable selector based on TeAsGeSiSe chalcogenides compatible with BEOL IC Integration for cross-point PCM. 2.2.1–2.2.4. 41 indexed citations
15.
BrightSky, M., Takeshi Masuda, Norma Sosa, et al.. (2016). ALD-based confined PCM with a metallic liner toward unlimited endurance. 4.2.1–4.2.4. 59 indexed citations
16.
Carta, Fabio, et al.. (2015). Sequential Lateral Solidification of Silicon Thin Films on Cu BEOL-Integrated Wafers for Monolithic 3-D Integration. IEEE Transactions on Electron Devices. 62(11). 3887–3891. 5 indexed citations
17.
Carta, Fabio, S. M. Gates, Htay Hlaing, et al.. (2014). Sequential lateral solidification of silicon thin films on low-k dielectrics for low temperature integration. Applied Physics Letters. 105(24). 6 indexed citations
18.
Hlaing, Htay, Chang‐Hyun Kim, Fabio Carta, et al.. (2014). Low-Voltage Organic Electronics Based on a Gate-Tunable Injection Barrier in Vertical graphene-organic Semiconductor Heterostructures. Nano Letters. 15(1). 69–74. 108 indexed citations
19.
Kim, Chang‐Hyun, Htay Hlaing, Fabio Carta, et al.. (2013). Templating and Charge Injection from Copper Electrodes into Solution-Processed Organic Field-Effect Transistors. ACS Applied Materials & Interfaces. 5(9). 3716–3721. 28 indexed citations
20.
Carta, Fabio, et al.. (2012). Bimorph actuator with monolithically integrated CMOS OFET control. Organic Electronics. 14(1). 286–290. 6 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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