Transport, Magnetic, and Memristive Properties of a Nanogranular (CoFeB)
                x
              (LiNbO
                y
              )100–x Composite Material

Rylkov, V. V.; Николаев, С. Н.; Демин, В. А.; Emelyanov, A. V.; Ситников, А. В.; Nikiruy, K. E.; Леванов, В. А.; Presnyakov, M. Yu.; Талденков, А. Н.; Vasiliev, Alexander L.; Chernoglazov, K. Yu.; Веденеев, А. С.; Kalinin, Yu. E.; Granovsky, A. B.; Тугушев, В. В.; Бугаев, А. С.

doi:10.1134/s1063776118020152

Cited by 61 publications

(33 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It is important that the position of filaments is determined by the existing chains of CoFeB metal granules inside the LiNbO 3 matrix. [20] Apparently for this reason, the CFB-LNO memristors don't need an electroforming process and have a fairly good plasticity: it is possible to set more than 256 resistive states. [44] However, the very first IV cycle can differ from the following cycles, but the cycleto-cycle variation coefficient is not more than 2%.…”

Section: Spike-timing-dependent Plasticitymentioning

confidence: 99%

“…In this case, the variability of parameters, both device to device and cycle to cycle, could be significant because of the random character of the filament (bridge) formation process. However, an introduction of metal nanoparticles into a dielectric matrix [19,20] or special dislocation engineering [21] allows one to confine the filament formation in definite channels. This increases the memristor parameters' repeatability and reproducibility, which is crucial for the NS training.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spike‐Timing‐Dependent and Spike‐Shape‐Independent Plasticities with Dopamine‐Like Modulation in Nanocomposite Memristive Synapses

Nikiruy

Surazhevsky

Демин

et al. 2020

Physica Status Solidi (a)

View full text Add to dashboard Cite

In hardware neuromorphic systems (NSs), memristors are used as synaptic connections. In such systems, spike‐timing‐dependent plasticity (STDP) is a promising local learning rule. Herein, STDP is studied in a system composed of a pair of hardware or software neurons connected by a (CoFeB)x(LiNbO3)100−x nanocomposite‐based memristor. The dopamine‐like modulation of memristor‐based STDP is implemented simply by the change in the polarity of spikes generated by artificial neurons operating in the inhibitory or excitatory mode. This modulation method is shown to be compatible with hardware neurons, different spike shapes, and is used in spiking NSs with bioinspired dopamine‐like reinforcement learning.

show abstract

Section: Spike-timing-dependent Plasticitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spike‐Timing‐Dependent and Spike‐Shape‐Independent Plasticities with Dopamine‐Like Modulation in Nanocomposite Memristive Synapses

Nikiruy

Surazhevsky

Демин

et al. 2020

Physica Status Solidi (a)

View full text Add to dashboard Cite

show abstract

“…In contrast to these works, here we pay special attention to the region of concentration x = 44 − 48 at.%, below the percolation threshold of the investigated NC. In this region, the temperature dependence of the electrical conductivity was found to follow the unusual logarithmic law in a wide temperature range T ≈ 10 − 200 K [9]. It was recently shown theoretically [21,22], that such behaviour is not connected with the dimension of the system and the weak-localization-induced Figure 1: a) Dark-field STEM image of the film cross-section (x = 48 at.%, from Ref.…”

Section: Introductionmentioning

confidence: 90%

“…The granular (CoFeB) x (LiNbO 3 ) 100−x metal-insulator nanocomposite (NC) is a synthetic multiferroic system that can be of great interest due to possibilities of non-trivial magneto-electric effects [8]. Recently, this NC was proposed as promising material for realizing resistive switching memory elements (memristors) for potential applications in neuromorfic networks [9,10]. The ion beam sputtered films of such NC demonstrate an interesting structural special feature: the CoFeB metallic FM phase has a tendency to form essentially non-spherical granules inside the LiNbO insulator matrix.…”

Section: Introductionmentioning

confidence: 99%

Mechanisms of FMR line broadening in CoFeB-LiNbO3 granular films in the vicinity of metal-insulator transition

Дровосеков

Крейнес

Barkalova

et al. 2020

Journal of Magnetism and Magnetic Materials

View full text Add to dashboard Cite

Metal-insulator (CoFeB) x (LiNbO 3 ) 100−x nanocomposite films with different content of the ferromagnetic (FM) phase x are investigated by ferromagnetic resonance (FMR) technique. A strong change of the FMR line shape is observed in the vicinity of metal-insulator transition (MIT) of the film, where the hopping-type conductivity σ modifies to the regime of a strong intergranular tunnelling, characterized by a logarithmic dependence σ(T ) at high temperatures. It is shown that below MIT, the FMR linewidth is mainly determined by the inhomogeneous distribution of the local anisotropy axes in the film plane. Above MIT, the contribution of this inhomogeneity to the line broadening decreases. At the same time, two-magnon magnetic relaxation processes begin to play a significant role in the formation of the linewidth. The observed behaviour indicates the critical role of interparticle exchange in the tunnelling regime above MIT of the nanocomposite.

show abstract

“…The memristive properties were found in structures based on inorganic oxides (TiO x , HfO x , SiO x , TaO x , etc.) [14][15][16][17][18], organic (polyaniline, polythiophene) [19][20][21] and nanocomposite [22] materials. Most memristive devices operate through the electromigration of oxygen vacancies in oxides and formation (rupture) of conductive filaments (valence change memristors) or metal bridge growth (destruction) by means of cation motion in a dielectric matrix (electrochemical metallization or ECM memristors) [1].…”

Section: Introductionmentioning

confidence: 99%

Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications

Миннеханов

Emelyanov

Lapkin

et al. 2019

Sci Rep

113

View full text Add to dashboard Cite

In this paper, the resistive switching and neuromorphic behaviour of memristive devices based on parylene, a polymer both low-cost and safe for the human body, is comprehensively studied. The Metal/Parylene/ITO sandwich structures were prepared by means of the standard gas phase surface polymerization method with different top active metal electrodes (Ag, Al, Cu or Ti of ~500 nm thickness). These organic memristive devices exhibit excellent performance: low switching voltage (down to 1 V), large OFF/ON resistance ratio (up to 10 4 ), retention (≥10 4 s) and high multilevel resistance switching (at least 16 stable resistive states in the case of Cu electrodes). We have experimentally shown that parylene-based memristive elements can be trained by a biologically inspired spike-timing-dependent plasticity (STDP) mechanism. The obtained results have been used to implement a simple neuromorphic network model of classical conditioning. The described advantages allow considering parylene-based organic memristors as prospective devices for hardware realization of spiking artificial neuron networks capable of supervised and unsupervised learning and suitable for biomedical applications.

show abstract

Transport, Magnetic, and Memristive Properties of a Nanogranular (CoFeB) x (LiNbO y )100–x Composite Material

Cited by 61 publications

References 50 publications

Spike‐Timing‐Dependent and Spike‐Shape‐Independent Plasticities with Dopamine‐Like Modulation in Nanocomposite Memristive Synapses

Spike‐Timing‐Dependent and Spike‐Shape‐Independent Plasticities with Dopamine‐Like Modulation in Nanocomposite Memristive Synapses

Mechanisms of FMR line broadening in CoFeB-LiNbO3 granular films in the vicinity of metal-insulator transition

Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications

Contact Info

Product

Resources

About