G. Molas

3.2k total citations · 1 hit paper
142 papers, 2.0k citations indexed

About

G. Molas is a scholar working on Electrical and Electronic Engineering, Materials Chemistry and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, G. Molas has authored 142 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 142 papers in Electrical and Electronic Engineering, 30 papers in Materials Chemistry and 15 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in G. Molas's work include Advanced Memory and Neural Computing (104 papers), Semiconductor materials and devices (102 papers) and Ferroelectric and Negative Capacitance Devices (80 papers). G. Molas is often cited by papers focused on Advanced Memory and Neural Computing (104 papers), Semiconductor materials and devices (102 papers) and Ferroelectric and Negative Capacitance Devices (80 papers). G. Molas collaborates with scholars based in France, Italy and United States. G. Molas's co-authors include Elisa Vianello, B. De Salvo, E. Nowak, L. Perniola, P. Blaise, G. Ghibaudo, S. Deleonibus, M. Bernard, A. Toffoli and Xavier Correig and has published in prestigious journals such as Nature, Nature Communications and Applied Physics Letters.

In The Last Decade

G. Molas

139 papers receiving 2.0k citations

Hit Papers

The growing memristor ind... 2025 2026 2025 10 20 30
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The growing memristor industry
    2025 35 citations Mario Lanza, Sebastián Pazos et al. Nature profile →

Author Peers

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

Author Last Decade Papers Cites
G. Molas 1.9k 531 275 240 168 142 2.0k
B. De Salvo 2.2k 1.2× 820 1.5× 192 0.7× 250 1.0× 213 1.3× 183 2.4k
Robin Jacobs-Gedrim 1.4k 0.7× 1.1k 2.0× 216 0.8× 270 1.1× 114 0.7× 36 1.9k
Jong‐Ho Bae 1.8k 1.0× 406 0.8× 93 0.3× 253 1.1× 64 0.4× 136 1.9k
Umesh Chand 1.6k 0.9× 589 1.1× 429 1.6× 396 1.6× 74 0.4× 47 1.8k
Congyan Lu 841 0.4× 302 0.6× 162 0.6× 151 0.6× 53 0.3× 63 927
Chunmeng Dou 1.2k 0.6× 214 0.4× 299 1.1× 306 1.3× 44 0.3× 75 1.4k
Beiju Huang 1.1k 0.6× 373 0.7× 108 0.4× 132 0.6× 244 1.5× 109 1.4k
Keun Heo 2.0k 1.1× 1.2k 2.2× 334 1.2× 503 2.1× 131 0.8× 64 2.5k
Di Geng 1.7k 0.9× 696 1.3× 303 1.1× 142 0.6× 54 0.3× 107 1.9k

Countries citing papers authored by G. Molas

Since Specialization
Citations

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

Fields of papers citing papers by G. Molas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Molas

This figure shows the co-authorship network connecting the top 25 collaborators of G. Molas. A scholar is included among the top collaborators of G. Molas 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 G. Molas. G. Molas 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.
Piccoli, Marco, N. Castellani, J. F. Nodin, et al.. (2025). On Chip Customized Learning on Resistive Memory Technology for Secure Edge AI. 1–3.
2.
Lanza, Mario, Sebastián Pazos, Fernando Aguirre, et al.. (2025). The growing memristor industry. Nature. 640(8059). 613–622. 35 indexed citations breakdown →
3.
Navarro, G., M. Bernard, C. Carabasse, et al.. (2024). 1S1R Multi-Level-Cell for Dense Quantized Recurrent Spiking Neural Network Inference Computing. 1 indexed citations
4.
Pillonnet, Gaël, et al.. (2024). How Significant Is SET Programming Strategy in Enhancing RRAM Technology?. SPIRE - Sciences Po Institutional REpository. 653–656.
5.
Deleruyelle, Damien, Quentin Rafhay, N. Castellani, et al.. (2023). Investigation of resistance fluctuations in ReRAM: physical origin, temporal dependence and impact on memory reliability. HAL (Le Centre pour la Communication Scientifique Directe). 1–6. 9 indexed citations
6.
Lanza, Mario, et al.. (2023). The gap between academia and industry in resistive switching research. Nature Electronics. 6(4). 260–263. 32 indexed citations
7.
Bianchi, S., Erika Covi, Alessandro Bricalli, et al.. (2023). A self-adaptive hardware with resistive switching synapses for experience-based neurocomputing. Nature Communications. 14(1). 1565–1565. 29 indexed citations
8.
Molas, G., et al.. (2022). A high throughput generative vector autoregression model for stochastic synapses. Frontiers in Neuroscience. 16. 941753–941753. 5 indexed citations
9.
Levisse, Alexandre, Mathieu Moreau, E. Nowak, et al.. (2019). Switching Event Detection and Self-Termination Programming Circuit for Energy Efficient ReRAM Memory Arrays. IEEE Transactions on Circuits & Systems II Express Briefs. 66(5). 748–752. 10 indexed citations
10.
Molas, G., Gilbert Sassine, C. Cagli, et al.. (2018). (Invited) Resistive Memories (RRAM) Variability: Challenges and Solutions. ECS Transactions. 86(3). 35–47. 27 indexed citations
11.
Giraud, Bastien, Alessandro Grossi, N. Castellani, et al.. (2018). In-depth Characterization of Resistive Memory-Based Ternary Content Addressable Memories. HAL (Le Centre pour la Communication Scientifique Directe). 20.3.1–20.3.4. 17 indexed citations
12.
Sassine, Gilbert, Alexandre Levisse, C. Cagli, et al.. (2018). Sub-pJ consumption and short latency time in RRAM arrays for high endurance applications. HAL (Le Centre pour la Communication Scientifique Directe). P–MY.2. 20 indexed citations
13.
Navarro, G., Anthonin Verdy, G. Bourgeois, et al.. (2017). Innovative PCM+OTS device with high sub-threshold non-linearity for non-switching reading operations and higher endurance performance. T94–T95. 33 indexed citations
14.
Molas, G., Elisa Vianello, F. Dahmani, et al.. (2014). Controlling oxygen vacancies in doped oxide based CBRAM for improved memory performances. 6.1.1–6.1.4. 30 indexed citations
15.
Vianello, Elisa, Olivier Thomas, Boubacar Traoré, et al.. (2013). Back-end 3D integration of HfO<inf>2</inf>-based RRAMs for low-voltage advanced IC digital design. 235–238. 4 indexed citations
16.
Vianello, Elisa, F. Driussi, P. Blaise, et al.. (2011). Explanation of the Charge Trapping Properties of Silicon Nitride Storage Layers for NVMs—Part II: Atomistic and Electrical Modeling. IEEE Transactions on Electron Devices. 58(8). 2490–2499. 44 indexed citations
17.
Molas, G., R. Kies, M. Bocquet, et al.. (2010). Investigation of charge-trap memories with AlN based band engineered storage layers. 1–4. 1 indexed citations
18.
Molas, G., M. Bocquet, Julien Buckley, et al.. (2008). Evaluation of HfAlO high-k materials for control dielectric applications in non-volatile memories. Microelectronic Engineering. 85(12). 2393–2399. 8 indexed citations
19.
Grampeix, H., G. Molas, M. Bocquet, et al.. (2007). Effect of Nitridation for High-K Layers by ALCVDTM in Order to Decrease the Trapping in Non Volatile Memories. ECS Transactions. 11(7). 213–225. 3 indexed citations
20.
Molas, G., M. Bocquet, Julien Buckley, et al.. (2007). Investigation of hafnium-aluminate alloys in view of integration as interpoly dielectrics of future Flash memories. Solid-State Electronics. 51(11-12). 1540–1546. 20 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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