Temperature Control of Diffusive Memristor Hysteresis and Artificial Neuron Spiking

Pattnaik, Debi Prasad; Ushakov, Yury; Zhou, Zhaoxia; Borisov, Pavel; Cropper, Michael D.; Wijayantha, U.W.; Balanov, A. G.; Savel’ev, Sergey

doi:10.1103/physrevapplied.19.024065

Cited by 6 publications

(11 citation statements)

References 40 publications

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“…A lower threshold voltage in the positive voltage polarity can be explained by some silver NPs being pinned at the top Pt electrode due to its higher interface roughness. 16 After irradiation we noticed a much stronger asymmetry in the current-voltage characteristic (see for example Fig. 1(f ), red circles) with the negative branch of the I-V curves showing a greater variety of the switching behaviours across separate devices and I-V cycles, whilst the positive branch demonstrates reproducible volatile switching.…”

Section: Resultsmentioning

confidence: 89%

“…43 and 44. Some redistribution of interstitial silicon and oxygen vacancies could have also occurred due to the work function difference between the top and bottom electrodes, caused by the difference in electrode roughness 16 or electrode thickness. 43,45,46 The subsequent field application should further produce oxygen vacancies to concentrate at the electrode opposite the positive one.…”

Section: Resultsmentioning

confidence: 99%

“…7,10–12 Mechanisms behind filament formation and rupture are of critical importance for the design of neuromorphic hardware based on diffusive memristors. 2,13–16…”

Section: Introductionmentioning

confidence: 99%

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Gamma radiation-induced nanodefects in diffusive memristors and artificial neurons

Pattnaik,

Andrews,

Cropper

et al. 2023

Nanoscale

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Section: Resultsmentioning

confidence: 89%

Section: Resultsmentioning

confidence: 99%

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Gamma radiation-induced nanodefects in diffusive memristors and artificial neurons

Pattnaik,

Andrews,

Cropper

et al. 2023

Nanoscale

Self Cite

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“…Single-device receptor system A single-device receptor system is implemented as a single device without integrating a sensor module, using a stimulus-detectable material in a memristive device. Some attempts have been made based on pressure- [270,271] and light-responsive [272,273] materials; however, so far, the most commonly implemented form is that of temperature receptors designed to respond to temperature changes. [274][275][276] For example, memristors have shown potential for acting as thermoreceptors by incorporating thermosensitive materials into the insulating layer.…”

Section: 12mentioning

confidence: 99%

Artificial sensory system based on memristive devices

Kwon,

Kim,

Kim

et al. 2023

Exploration

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In the biological nervous system, the integration and cooperation of parallel system of receptors, neurons, and synapses allow efficient detection and processing of intricate and disordered external information. Such systems acquire and process environmental data in real‐time, efficiently handling complex tasks with minimal energy consumption. Memristors can mimic typical biological receptors, neurons, and synapses by implementing key features of neuronal signal‐processing functions such as selective adaption in receptors, leaky integrate‐and‐fire in neurons, and synaptic plasticity in synapses. External stimuli are sensitively detected and filtered by “artificial receptors,” encoded into spike signals via “artificial neurons,” and integrated and stored through “artificial synapses.” The high operational speed, low power consumption, and superior scalability of memristive devices make their integration with high‐performance sensors a promising approach for creating integrated artificial sensory systems. These integrated systems can extract useful data from a large volume of raw data, facilitating real‐time detection and processing of environmental information. This review explores the recent advances in memristor‐based artificial sensory systems. The authors begin with the requirements of artificial sensory elements and then present an in‐depth review of such elements demonstrated by memristive devices. Finally, the major challenges and opportunities in the development of memristor‐based artificial sensory systems are discussed.

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“…Through the use of threshold switching, a subset of typically volatile devices utilizes the diffusive dynamics of metallic nanoparticles dispersed in an insulating oxide matrix to replicate biological synapses with low power consumption [13,14]. Labeled diffusive memristors, these devices operate by forming a conductive filament of such nanoparticles between two metallic electrodes, once an applied voltage bias reaches a characteristic threshold voltage, V T [15].…”

Section: Introductionmentioning

confidence: 99%

Resistive switching study on diffusive memristors using electrochemical impedance spectroscopy

Gabbitas

Pattnaik

Zhou

et al. 2023

J. Phys. D: Appl. Phys.

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Diffusive memristors demonstrate volatile resistive switching powered by the diffusion of silver nanoparticles through the matrix of silicon dioxide. The equivalent circuit of the high resistance state has been studied via electrochemical impedance spectroscopy for two types of devices which demonstrate either analog or abrupt switching characteristics. It was found that the resistance component has a relatively good agreement with the differential resistance obtained from the I-V curves, whereas the capacitance visibly increases in the analog switching devices with increasing bias voltage as its conductive precursor filament starts forming with increasing voltage and redistribution of silver nanoparticles starts to occur at the top electrodes. Such an effect is not observed for abrupt switching device, which rapidly enters its conductive state for a small increase in bias voltage. This experimental approach allows for the identification of different types of electrical circuit behaviors in a memristive device, even before resistive switching takes place.

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Temperature Control of Diffusive Memristor Hysteresis and Artificial Neuron Spiking

Cited by 6 publications

References 40 publications

Gamma radiation-induced nanodefects in diffusive memristors and artificial neurons

Gamma radiation-induced nanodefects in diffusive memristors and artificial neurons

Artificial sensory system based on memristive devices

Resistive switching study on diffusive memristors using electrochemical impedance spectroscopy

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