A Highly Transparent Artificial Photonic Nociceptor

Kumar, Mohit; Kim, Hong-Sik; Kim, Sangho

doi:10.1002/adma.201900021

Cited by 131 publications

(158 citation statements)

References 47 publications

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“…[6] To emulate visual perception of retina, photonic synapses can combine two functions of sensing and synaptic elements in a single device with a more compact form than the conventional one that consists of two devices. [3,[7][8][9][10][11][12][13][14][15] The dual functions of artificial synapse and photosensor would give abilities that are beyond those of a simple sensing device, i.e., photonic synapses can process detected light signals and track the history including light intensity, and the number, duration, and frequency of exposure. [14,16] Thus, these photonic synapses are applicable for smart sensors for the Internet of Things, biomedical electronics, soft robots, and neural prostheses.…”

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confidence: 99%

Retina‐Inspired Carbon Nitride‐Based Photonic Synapses for Selective Detection of UV Light

et al. 2020

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Photonic synapses combine sensing and processing in a single device, so they are promising candidates to emulate visual perception of a biological retina. However, photonic synapses with wavelength selectivity, which is a key property for visual perception, have not been developed so far. Herein, organic photonic synapses that selectively detect UV rays and process various optical stimuli are presented. The photonic synapses use carbon nitride (C3N4) as an UV‐responsive floating‐gate layer in transistor geometry. C3N4 nanodots dominantly absorb UV light; this trait is the basis of UV selectivity in these photonic synapses. The presented devices consume only 18.06 fJ per synaptic event, which is comparable to the energy consumption of biological synapses. Furthermore, in situ modulation of exposure to UV light is demonstrated by integrating the devices with UV transmittance modulators. These smart systems can be further developed to combine detection and dose‐calculation to determine how and when to decrease UV transmittance for preventive health care.

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confidence: 99%

Retina‐Inspired Carbon Nitride‐Based Photonic Synapses for Selective Detection of UV Light

et al. 2020

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“…Figure 3e illustrates variations of the synaptic weight (or EPSC) with different spiking intervals, where the stimulus train at each frequency consists of ten continuous stimulus spikes (2 V, 10 ms). [7,8] Therefore, these results strongly indicate that our ultrashort vertical transistor has great potential for painful perception recognition. However, the amplitude of the EPSC clearly increases as the frequency of the stimulus train increases.…”

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confidence: 56%

“…In this figure, our device exhibits typical nonpainful behavior characteristics with stimuli lower than the threshold plane, but exhibits significant pain when the external stimuli exceed the threshold plane. [7,8] Therefore, these results strongly indicate that our ultrashort vertical transistor has great potential for painful perception recognition.…”

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confidence: 56%

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A Sub‐10 nm Vertical Organic/Inorganic Hybrid Transistor for Pain‐Perceptual and Sensitization‐Regulated Nociceptor Emulation

et al. 2019

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Pain‐perceptual nociceptors (PPN) are essential sensory neurons that recognize harmful stimuli and can empower the human body to react appropriately and perceive precisely unusual or dangerous conditions in the real world. Furthermore, the sensitization‐regulated nociceptors (SRN) can greatly assist pain‐sensitive human to reduce pain sensation by normalizing hyperexcitable central neural activity. Therefore, the implementation of PPNs and SRNs in hardware using emerging nanoscale devices can greatly improve the efficiency of bionic medical machines by giving them different sensitivities to external stimuli according to different purposes. However, current most‐normal organic/oxide transistors face a great challenge due to channel scaling, especially in the sub‐10 nm channel technology. Here, a sub‐10 nm indium‐tin‐oxide transistor with an ultrashort vertical channel as low as ≈3 nm, using sodium alginate bio‐polymer electrolyte as gate dielectric, is demonstrated. This device can emulate important characteristics of PPN such as pain threshold, memory of prior injury, and pain sensitization/desensitization. Furthermore, the most intriguing character of SRN can be achieved by tuning the channel thickness. The proposed device can open new avenues for the fascinating applications of next‐generation neuromorphic brain‐like systems, such as bio‐inspired electronic skins and humanoid robots.

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“…In addition, ReRAM-based artificial synapses have been used to demonstrate artificial nociceptors (Section 5.2). [78,79,120,121] However, the current increases rapidly, so the device consumes a large amount of energy.…”

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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A Highly Transparent Artificial Photonic Nociceptor

Cited by 131 publications

References 47 publications

Retina‐Inspired Carbon Nitride‐Based Photonic Synapses for Selective Detection of UV Light

Retina‐Inspired Carbon Nitride‐Based Photonic Synapses for Selective Detection of UV Light

A Sub‐10 nm Vertical Organic/Inorganic Hybrid Transistor for Pain‐Perceptual and Sensitization‐Regulated Nociceptor Emulation

Flexible Neuromorphic Electronics for Computing, Soft Robotics, and Neuroprosthetics

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