VO2 film temperature dynamics at low-frequency current self-oscillations

Bortnikov, Sergey G.; Алиев, В. Ш.; Badmaeva, I. A.; Mzhelskiy, Ivan V.

doi:10.1063/1.5010971

Cited by 9 publications

(11 citation statements)

References 17 publications

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“…This is a similar behavior to the one reported by Goodwill et al during a singular threshold switching events . Similar breathing mode behavior of the current constriction has been reported in VO 2 -based devices. , …”

Section: Results and Discussionsupporting

confidence: 90%

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Electrical and Thermal Dynamics of Self-Oscillations in TaO_x-Based Threshold Switching Devices

Zhao

Goodwill

et al. 2020

ACS Appl. Electron. Mater.

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We present experimental results of relaxation oscillations based on the TaO x threshold switching devices as a function of voltage, load resistance, and the parallel capacitance. Of particular interest are the dynamics of transitions between ON and OFF states of the device which impose an upper limit of the oscillation frequency. The dynamics have been captured by the finite element electrothermal model using only electrical conductivity vs temperature and thermally activated conductivities as input data. The model reproduced current and voltage waveforms and allowed for following the changes in current density and temperature distributions within the device during oscillations. Both undergo significant breathing-mode-type changes in each cycle as the current spontaneously constricts during the capacitance discharge/heating stage. The model points out the possible approaches toward achieving higher oscillation frequencies.

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Section: Results and Discussionsupporting

confidence: 90%

“…31 Similar breathing mode behavior of the current constriction has been reported in VO 2 -based devices. 42,43 2.5. Source Voltage Range for Sustained Oscillations.…”

Section: Resultsmentioning

confidence: 99%

Electrical and Thermal Dynamics of Self-Oscillations in TaO_x-Based Threshold Switching Devices

Zhao

Goodwill

et al. 2020

ACS Appl. Electron. Mater.

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“…In most states, the system control input u is an unknown quantity. By including the influence of u in the system stochastic interference and measurement stochastic deviation [7,8], we get x(kT + T) � Ax(kT) + w(kT), y(kT) � Cx(kT) + v(kT).…”

Section: Low-frequency Electromechanical Samplingmentioning

confidence: 99%

“…. , Λ i under each time lag is calculated according to equation (8), where i satisfies li ≫ n, and equation ( 7) is used to construct the Toeplitz matrix T 1|i ; singular value decomposition is performed on T 1|i ; then, we get…”

Section: Low-frequency Electromechanical Samplingmentioning

confidence: 99%

Adaptive Configuration Method of Low-Frequency Electromechanical Sampling Information in Building Electrical System

Bai

Zhang

2021

Mathematical Problems in Engineering

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In order to enhance the reliability of the electrical systems in low frequency, an adaptive configuration method of low-frequency electromechanical sampling information based on thyristor controlled series compensation (TCSC) is designed. The electrical system is simplified to a linear invariant system, and a stochastic subspace identification (SSI) method is established by using the singular value decomposition principle to collect low-frequency electromechanical sampling information. The reference channel technology is introduced to design the reference channel covariance matrix to judge whether low-frequency information is generated and improve the efficiency of sampling information acquisition. The architecture and working principle of the controllable series compensation device are analyzed, and the test signal method is used to evaluate the low-frequency modes and the information required by the device among the electrical system regions of buildings. The alternative input signals are selected by comparing different input signal residue ratios. The TCSC device parameters are adjusted by the compensation residue phase method, so as to realize the adaptive configuration of different low-frequency electromechanical sampling information and ensure the stable operation of the electrical system. The experimental results show that the proposed configuration scheme can effectively improve the damping ratio of the system and has an excellent effect on suppressing the continuous oscillation under a low-frequency fault.

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“…This gives rise to the so called volatile Mott memristors [14][15][16][17][18] because, upon removal of electrical stimulus, these devices reset back spontaneously to the high resistive state (HRS) from the low resistive state (LRS). Experimental evidence [19][20][21][22] points towards self-heating as driving this transition by increasing the device temperature.…”

mentioning

confidence: 99%

Role of ambient temperature in modulation of behavior of vanadium dioxide volatile memristors and oscillators for neuromorphic applications

Carapezzi

Delacour

Plews

et al. 2022

Sci Rep

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Volatile memristors are versatile devices whose operating mechanism is based on an abrupt and volatile change of resistivity. This switching between high and low resistance states is at the base of cutting edge technological implementations such as neural/synaptic devices or random number generators. A detailed understanding of this operating mechanisms is essential prerequisite to exploit the full potentiality of volatile memristors. In this respect, multi-physics device simulations provide a powerful tool to single out material properties and device features that are the keys to achieve desired behaviors. In this paper, we perform 3D electrothermal simulations of volatile memristors based on vanadium dioxide (VO$$_{2}$$ 2 ) to accurately investigate the interplay among Joule effect, heat dissipation and the external temperature $$T_{0}$$ T 0 over their resistive switching mechanism. In particular, we extract from our simulations a simplified model for the effect of $$T_{0}$$ T 0 over the negative differential resistance (NDR) region of such devices. The NDR of VO$$_{2}$$ 2 devices is pivotal for building VO$$_{2}$$ 2 oscillators, which have been recently shown to be essential elements of oscillatory neural networks (ONNs). ONNs are innovative neuromorphic circuits that harness oscillators’ phases to compute. Our simulations quantify the impact of $$T_{0}$$ T 0 over figures of merit of VO$$_{2}$$ 2 oscillator, such as frequency, voltage amplitude and average power per cycle. Our findings shed light over the interlinked thermal and electrical behavior of VO$$_{2}$$ 2 volatile memristors and oscillators, and provide a roadmap for the development of ONN technology.

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VO2 film temperature dynamics at low-frequency current self-oscillations

Cited by 9 publications

References 17 publications

Electrical and Thermal Dynamics of Self-Oscillations in TaO_x-Based Threshold Switching Devices

Electrical and Thermal Dynamics of Self-Oscillations in TaO_x-Based Threshold Switching Devices

Adaptive Configuration Method of Low-Frequency Electromechanical Sampling Information in Building Electrical System

Role of ambient temperature in modulation of behavior of vanadium dioxide volatile memristors and oscillators for neuromorphic applications

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VO2 film temperature dynamics at low-frequency current self-oscillations

Cited by 9 publications

References 17 publications

Electrical and Thermal Dynamics of Self-Oscillations in TaOx-Based Threshold Switching Devices

Electrical and Thermal Dynamics of Self-Oscillations in TaOx-Based Threshold Switching Devices

Adaptive Configuration Method of Low-Frequency Electromechanical Sampling Information in Building Electrical System

Role of ambient temperature in modulation of behavior of vanadium dioxide volatile memristors and oscillators for neuromorphic applications

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Electrical and Thermal Dynamics of Self-Oscillations in TaO_x-Based Threshold Switching Devices

Electrical and Thermal Dynamics of Self-Oscillations in TaO_x-Based Threshold Switching Devices