Artificial Synapse Emulated by Charge Trapping‐Based Resistive Switching Device

Zhang, Shirui; Zhou, Li; Mao, Jing‐Yu; Ren, Yi; Yang, Jiaqin; Yang, Guang-Hu; Zhu, Xin; Han, Su‐Ting; Roy, Vellaisamy A. L.; Zhou, Ye

doi:10.1002/admt.201800342

Cited by 113 publications

(114 citation statements)

References 41 publications

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“…3c), demonstrating a typical spike-rate dependent plasticity (SRDP). 47 This short-term enhanced plasticity enables GAS to act as a dynamic lter for information transmission. 21 It is obvious that Li-GAS shows a better dynamic ltering ( Fig.…”

Section: Resultsmentioning

confidence: 99%

Graphdiyne-Based Ultra-Responsive Artificial Synapse with Multi-Ion Diffusive Dynamics for Mimicking Efferent Nerves

Wei¹,

Shi²,

Sun³

et al. 2020

Preprint

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Somatosensory nerves require synapses to respond efficiently and in parallel for receving and transmiting biological signals. The gap between biological systems and conventional electronics needs ionotronics to bridge. However, the exploration of new materials and the systematic construction of ionotronics still pose challenges. Graphdiyne, a highly π-extended two-dimensional (2D) carbon allotrope, has demonstrated potential applications in ionic peripheral systems for its inherent network holes that can be used for rapid and selective transmission of diverse ions. Here, a graphdiyne-based artificial synapse (GAS), exhibiting intrinsic short-term plasticity, has been proposed to mimic the biological signal transmission behaviors. An record-breaking impulse responsiveness (±5 mV) that is an order of magnitude exceeding biological level has been realized for ultra-sensitive and power-efficient brain-inspired applications, with the lowest femtowatt-level consumption (~16.7 fW). Most importantly, GAS is capable of parallelly processing signals transmitted from multiple preneurons and therefore realizing dynamic logics and spatiotemporal rules. In a proof-of-concept demonstration, our artificial efferent nerve, connecting GAS with artificial muscles, completes the information integration of preneurons and the information output of motor neurons, which is advantageous for coalescing multiple sensory feedbacks (e.g., visual and tactile) and reacting to these events. Our synaptic element has potential applications in bioinspired peripheral nervous systems of soft electronics and neurorobotics.

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Section: Resultsmentioning

confidence: 99%

Graphdiyne-Based Ultra-Responsive Artificial Synapse with Multi-Ion Diffusive Dynamics for Mimicking Efferent Nerves

Wei¹,

Shi²,

Sun³

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Artificial synapses have been developed based on various structures, materials, and mechanisms to mimic the structure and synaptic plasticity of biological synapses. Conventional memory mechanisms (e.g., conductive filament, [54,75,[77][78][79][80][81][82][83][84][85][86] Schottky junction, [87][88][89] charge trapping, [82,[90][91][92][93][94][95] phase change, [75,[96][97][98] ferroelectricity, [99][100][101][102][103][104][105][106][107] ion migration [4,51,74,108] ) have been extended to the implementation of synaptic properties. Artificial synapses, i.e., transistors that exploit electrochemical reactions have also been developed.…”

Section: Mechanismsmentioning

confidence: 99%

“…in insulating layers, and the electron injection mechanism changes from Ohmic (ln(I) ∼ V α , α ≈ 1) to space-charge-limited-current (SCLC) (α ≈ 2) conduction in which the number of injected carriers exceeds the number of thermally generated carriers ( Figure 5c). [82,90,91] When the metal electrode and the insulating layer are in Ohmic contact and the trap-free state is maintained, the current is controlled by the space charge. In artificial synapses in which charge-trapping nanoparticles (NPs) (e.g., Au NP [90] and mica [91] ) have been added to the middle layer, the voltage caused trapping of charges in the nanomaterial, so current flow followed the SCLC conduction mechanism.…”

Section: Two-terminal Devicesmentioning

confidence: 99%

Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics

et al. 2019

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Flexible neuromorphic electronics that emulate biological neuronal systems constitute a promising candidate for next‐generation wearable computing, soft robotics, and neuroprosthetics. For realization, with the achievement of simple synaptic behaviors in a single device, the construction of artificial synapses with various functions of sensing and responding and integrated systems to mimic complicated computing, sensing, and responding in biological systems is a prerequisite. Artificial synapses that have learning ability can perceive and react to events in the real world; these abilities expand the neuromorphic applications toward health monitoring and cybernetic devices in the future Internet of Things. To demonstrate the flexible neuromorphic systems successfully, it is essential to develop artificial synapses and nerves replicating the functionalities of the biological counterparts and satisfying the requirements for constructing the elements and the integrated systems such as flexibility, low power consumption, high‐density integration, and biocompatibility. Here, the progress of flexible neuromorphic electronics is addressed, from basic backgrounds including synaptic characteristics, device structures, and mechanisms of artificial synapses and nerves, to applications for computing, soft robotics, and neuroprosthetics. Finally, future research directions toward wearable artificial neuromorphic systems are suggested for this emerging area.

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“…In addition to the application in flash memory, upconversion materials also can be applied on ReRAM to improve the resistive switching performance. Zhai et al combined 2D materials and upconversion nanoparticles to fabricate ReRAM. In the active layer between two electrodes, molybdenum disulfide (MoS 2 ) was introduced to form a heterostructure with NaYF 4 : Yb 3+ , Er 3+ upconversion nanoparticles.…”

Section: Photo‐tunable Memorymentioning

confidence: 99%

Functional Non‐Volatile Memory Devices: From Fundamentals to Photo‐Tunable Properties

Wang

Zhang

Zhou

et al. 2019

Physica Rapid Research Ltrs

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As one of the five basic components in a modern computer system, memory plays a key role in data storage while the Von Neumann architecture still occupies a principal position in modern digital era. With the rapid development of portable electronic devices, non‐volatile memories are of great importance in human's daily life. High‐performance memory devices are highly demanded, and novel materials applied to flash memory and resistive random access memory (ReRAM) have been widely investigated. The functionalities of memories can be broadened with the development of semiconductor technologies. As a facile and low‐power electromagnetic wave, light can be another modulation medium, which will not bring destructive operation and can enhance the device performance. In this review, the focus is on flash memory and ReRAM based on various functional materials as well as the recent development of photo‐tunable memories.

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Artificial Synapse Emulated by Charge Trapping‐Based Resistive Switching Device

Cited by 113 publications

References 41 publications

Graphdiyne-Based Ultra-Responsive Artificial Synapse with Multi-Ion Diffusive Dynamics for Mimicking Efferent Nerves

Graphdiyne-Based Ultra-Responsive Artificial Synapse with Multi-Ion Diffusive Dynamics for Mimicking Efferent Nerves

Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics

Functional Non‐Volatile Memory Devices: From Fundamentals to Photo‐Tunable Properties

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