В. А. Демин

2.4k total citations
107 papers, 1.7k citations indexed

About

В. А. Демин is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Polymers and Plastics. According to data from OpenAlex, В. А. Демин has authored 107 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Electrical and Electronic Engineering, 48 papers in Cellular and Molecular Neuroscience and 23 papers in Polymers and Plastics. Recurrent topics in В. А. Демин's work include Advanced Memory and Neural Computing (72 papers), Neuroscience and Neural Engineering (43 papers) and Photoreceptor and optogenetics research (23 papers). В. А. Демин is often cited by papers focused on Advanced Memory and Neural Computing (72 papers), Neuroscience and Neural Engineering (43 papers) and Photoreceptor and optogenetics research (23 papers). В. А. Демин collaborates with scholars based in Russia, Italy and United States. В. А. Демин's co-authors include A. V. Emelyanov, П. К. Кашкаров, V. V. Rylkov, M. V. Kovalchuk, Victor Erokhin, K. E. Nikiruy, Dmitry Lapkin, А. В. Ситников, А. А. Миннеханов and Yu. P. Buzulukov and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and Journal of Applied Physics.

In The Last Decade

В. А. Демин

100 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
В. А. Демин Russia 21 1.3k 742 360 320 291 107 1.7k
Sangho Shin South Korea 23 1.6k 1.2× 535 0.7× 193 0.5× 110 0.3× 160 0.5× 81 1.9k
Adnan Mehonić United Kingdom 20 2.1k 1.6× 808 1.1× 266 0.7× 342 1.1× 332 1.1× 53 2.2k
A. V. Emelyanov Russia 22 1.2k 1.0× 665 0.9× 306 0.8× 262 0.8× 247 0.8× 103 1.5k
Ye Zhuo United States 15 2.6k 2.0× 1.1k 1.4× 514 1.4× 465 1.5× 555 1.9× 26 2.8k
Yijun Li China 17 1.1k 0.9× 374 0.5× 207 0.6× 198 0.6× 372 1.3× 39 1.6k
Fabien Alibart France 22 2.0k 1.6× 980 1.3× 407 1.1× 330 1.0× 345 1.2× 63 2.2k
Ali Khiat United Kingdom 22 1.9k 1.5× 1.0k 1.4× 441 1.2× 303 0.9× 160 0.5× 51 2.0k
Д. С. Королев Russia 18 744 0.6× 364 0.5× 210 0.6× 83 0.3× 258 0.9× 84 1.1k
Julien Borghetti United States 13 3.1k 2.4× 1.7k 2.2× 495 1.4× 462 1.4× 390 1.3× 16 3.2k

Countries citing papers authored by В. А. Демин

Since Specialization
Citations

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

Fields of papers citing papers by В. А. Демин

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by В. А. Демин. 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 В. А. Демин. The network helps show where В. А. Демин may publish in the future.

Co-authorship network of co-authors of В. А. Демин

This figure shows the co-authorship network connecting the top 25 collaborators of В. А. Демин. A scholar is included among the top collaborators of В. А. Демин 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 В. А. Демин. В. А. Демин 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.
Emelyanov, A. V., S. A. Zav’yalov, П. А. Форш, et al.. (2025). Photosensitive resistive switching in parylene–PbTe nanocomposite memristors for neuromorphic computing. Nanoscale. 17(14). 8484–8495. 6 indexed citations
2.
Emelyanov, A. V., et al.. (2024). Parylene-MoOx crossbar memristors as a volatile reservoir and non-volatile readout: a homogeneous reservoir computing system. Nanoscale. 16(44). 20628–20636. 10 indexed citations
3.
Emelyanov, A. V., et al.. (2024). Plasticity of parylene memristors: Compact phenomenological model and synaptic properties. Chaos Solitons & Fractals. 190. 115784–115784. 7 indexed citations
4.
Emelyanov, A. V., et al.. (2023). Memristive circuit-based model of central pattern generator to reproduce spinal neuronal activity in walking pattern. Frontiers in Neuroscience. 17. 1124950–1124950. 6 indexed citations
5.
Демин, В. А., et al.. (2023). Model of Multifilamentary Resistive Switching for a Memristor with Hopping Conductivity. Nanobiotechnology Reports. 18(2). 305–317. 3 indexed citations
6.
Малахов, С. Н., et al.. (2023). Multi-Terminal Nonwoven Stochastic Memristive Devices Based on Polyamide-6 and Polyaniline for Neuromorphic Computing. Biomimetics. 8(2). 189–189. 7 indexed citations
7.
Emelyanov, A. V., K. E. Nikiruy, В. А. Демин, et al.. (2023). Compact Model for Describing the Plasticity of Memristors Based on Nanolayers of LiNbO3 and (Co–Fe–B)х(LiNbO3)100–х Composite According to the Biosimilar STDP Rule. Nanobiotechnology Reports. 18(S2). S421–S426. 2 indexed citations
8.
Battistoni, Silvia, А. А. Миннеханов, S. A. Zav’yalov, et al.. (2023). Combination of Organic‐Based Reservoir Computing and Spiking Neuromorphic Systems for a Robust and Efficient Pattern Classification. SHILAP Revista de lepidopterología. 5(6). 42 indexed citations
9.
10.
Миннеханов, А. А., A. V. Emelyanov, М. Л. Занавескин, et al.. (2022). Parylene-based memristive crossbar structures with multilevel resistive switching for neuromorphic computing. Nanotechnology. 33(25). 255201–255201. 20 indexed citations
11.
Emelyanov, A. V., et al.. (2022). Nanocomposite parylene-C memristors with embedded Ag nanoparticles for biomedical data processing. Organic Electronics. 102. 106455–106455. 18 indexed citations
12.
Миннеханов, А. А., A. V. Emelyanov, Е. В. Кукуева, et al.. (2021). Parylene-based memristive synapses for hardware neural networks capable of dopamine-modulated STDP learning. Journal of Physics D Applied Physics. 54(48). 484002–484002. 14 indexed citations
13.
Lapkin, Dmitry, A. V. Emelyanov, А. А. Миннеханов, et al.. (2020). Associative STDP-like learning of neuromorphic circuits based on polyaniline memristive microdevices. Journal of Physics D Applied Physics. 53(41). 414001–414001. 26 indexed citations
14.
Mikhaylov, Alexey, Alexey Pimashkin, Yana Pigareva, et al.. (2020). Neurohybrid Memristive CMOS-Integrated Systems for Biosensors and Neuroprosthetics. Frontiers in Neuroscience. 14. 358–358. 144 indexed citations
15.
Emelyanov, A. V., K. E. Nikiruy, А. В. Ситников, et al.. (2019). Self-adaptive STDP-based learning of a spiking neuron with nanocomposite memristive weights. Nanotechnology. 31(4). 45201–45201. 68 indexed citations
16.
Lapkin, Dmitry, С. Н. Малахов, В. А. Демин, С. Н. Чвалун, & L. A. Feĭgin. (2019). Hybrid polyaniline/polyamide-6 fibers and nonwoven materials for assembling organic memristive elements. Synthetic Metals. 254. 63–67. 15 indexed citations
17.
Zinicovscaia, Inga, et al.. (2018). Accumulation of silver nanoparticles in mice tissues studied by neutron activation analysis. Journal of Radioanalytical and Nuclear Chemistry. 318(2). 985–989. 19 indexed citations
18.
Rylkov, V. V., С. Н. Николаев, В. А. Демин, et al.. (2018). Transport, Magnetic, and Memristive Properties of a Nanogranular (CoFeB) x (LiNbO y )100–x Composite Material. Journal of Experimental and Theoretical Physics. 126(3). 353–367. 51 indexed citations
19.
Демин, В. А., Victor Erokhin, П. К. Кашкаров, & M. V. Kovalchuk. (2014). Electrochemical model of the polyaniline based organic memristive device. Journal of Applied Physics. 116(6). 24 indexed citations
20.
Демин, В. А., Е. А. Константинова, & П. К. Кашкаров. (2010). Luminescence and photosensitization properties of ensembles of silicon nanocrystals in terms of an exciton migration model. Journal of Experimental and Theoretical Physics. 111(5). 830–843. 3 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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