Abstract:In spite of the strong interest in brain-like or neuromorphic computation, relatively few devices have emerged whose neuromorphic behavior is embedded in the hardware itself and not reliant on external programming of synaptic weights. We describe here a neuromorphic device based on a TiO2 nanowire that exhibits an associative memory response to the time correlation between voltage and optical stimuli. Memristive characteristics are also observed with current-voltage sweeps showing hysteresis loops and continuu… Show more
“…[163] For this reason, by manipulating the amount of oxygen vacancies at the interface, it is possible to achieve multiple resistance states. Interestingly, it was shown that neuromorphic-like devices based on TiO 2 nanowires can be sensitive to heterogeneous physical stimuli, as shown by O'Kelly et al [166] that reported associative memory with time-dependent correlation in between voltage and optical pulse stimuli. Lin et al, [164] considering similar Au/TiO 2 NW/Au devices, proposed that plasmonic-enhanced optical absorption at the TiO 2 /Au interface induced by femtosecond laser irradiation can enhance the mechanical and electrical properties of contacts, allowing an engineering of the local concentration of charged defects in TiO 2 NW near the interface.…”
Section: Single Crystalline Nwsmentioning
confidence: 96%
“…[164,166,253,254,267,[290][291][292][293] In semiconductor oxides, the electronic conductivity can be modified by photon irradiation. However, it was demonstrated that the transition between resistance states can be modulated or even induced by using different stimuli, such as illumination.…”
Memristive devices are considered one of the most promising candidates to overcome technological limitations for realizing next‐generation memories, logic applications, and neuromorphic systems in the modern nanoelectronics and information technology. Despite the continuous efforts, understanding the resistive switching mechanism underlying memristive/neuromorphic behavior still represents a challenge. Metal oxide nanowire‐based memristors appear suitable model systems for a deeper understanding of the involved physical/chemical phenomena due the possibility for localizing and investigating the switching mechanism. In practical aspects, nanowire‐based devices can be grown using a bottom‐up approach, thus being considered reliable candidates for going beyond the current scaling limitations of the top‐down approach by the standard lithography. In addition, taking into advantage of the high surface‐to‐volume ratio of these nanostructures, new device functionalities can be achieved by exploiting surface effects. In the literature, a variety of nanowire‐based devices such as single nanowires, nanowire arrays, and networks are reported to exhibit memristive behavior, explained by different switching mechanisms. This work provides a comparative review and a comprehensive analysis of device performances and physical phenomena responsible for memristive and neuromorphic behavior in such nanostructures. The analysis of the state‐of‐art of memristor devices based on nanowires and nanorods represent a milestone toward the development of nanowire‐based artificial neural networks.
“…[163] For this reason, by manipulating the amount of oxygen vacancies at the interface, it is possible to achieve multiple resistance states. Interestingly, it was shown that neuromorphic-like devices based on TiO 2 nanowires can be sensitive to heterogeneous physical stimuli, as shown by O'Kelly et al [166] that reported associative memory with time-dependent correlation in between voltage and optical pulse stimuli. Lin et al, [164] considering similar Au/TiO 2 NW/Au devices, proposed that plasmonic-enhanced optical absorption at the TiO 2 /Au interface induced by femtosecond laser irradiation can enhance the mechanical and electrical properties of contacts, allowing an engineering of the local concentration of charged defects in TiO 2 NW near the interface.…”
Section: Single Crystalline Nwsmentioning
confidence: 96%
“…[164,166,253,254,267,[290][291][292][293] In semiconductor oxides, the electronic conductivity can be modified by photon irradiation. However, it was demonstrated that the transition between resistance states can be modulated or even induced by using different stimuli, such as illumination.…”
Memristive devices are considered one of the most promising candidates to overcome technological limitations for realizing next‐generation memories, logic applications, and neuromorphic systems in the modern nanoelectronics and information technology. Despite the continuous efforts, understanding the resistive switching mechanism underlying memristive/neuromorphic behavior still represents a challenge. Metal oxide nanowire‐based memristors appear suitable model systems for a deeper understanding of the involved physical/chemical phenomena due the possibility for localizing and investigating the switching mechanism. In practical aspects, nanowire‐based devices can be grown using a bottom‐up approach, thus being considered reliable candidates for going beyond the current scaling limitations of the top‐down approach by the standard lithography. In addition, taking into advantage of the high surface‐to‐volume ratio of these nanostructures, new device functionalities can be achieved by exploiting surface effects. In the literature, a variety of nanowire‐based devices such as single nanowires, nanowire arrays, and networks are reported to exhibit memristive behavior, explained by different switching mechanisms. This work provides a comparative review and a comprehensive analysis of device performances and physical phenomena responsible for memristive and neuromorphic behavior in such nanostructures. The analysis of the state‐of‐art of memristor devices based on nanowires and nanorods represent a milestone toward the development of nanowire‐based artificial neural networks.
away quickly when the light stimuli are removed. [3][4][5] In other words, traditional photodetectors can detect the images like a retina, but they lack the memory function owned by the visual cortex (see schematic illustration of human visual system in Figure 1a). To realize both detection and memory functions so as to better imitate the human visual system, researchers have attempted to integrate the photodetectors with the nonvolatile memory devices. [6][7][8][9] For example, a bioinspired visual system comprising an In 2 O 3 nanowire photodetector connected in series with an Al 2 O 3 memristor was fabricated recently, which could capture a butterflyshaped image and store it for more than 1 week. [9] In such integrated devices, however, the units responsible for detection, processing, and storage of optical information are physically separated, resulting in high power consumption for data transfer between different units (just as the Von Neumann bottleneck [10,11] ).A simple yet effective humanoid optoelectronic device emerging recently is the artificial optoelectronic synapse based on the photoelectric memristor, which can co-locate the detection and memory functions in a single unit. As the name suggests, a photoelectric memristor can continuously change its resistance upon light stimuli, resembling the physiological The rapid development of artificial intelligence technology has led to the urge for artificial optoelectronic synapses with visual perception and memory capabilities. A new type of artificial optoelectronic synapse, namely a photo electric memcapacitor, is proposed and demonstrated. This photoelectric memcapacitor, with a planar Au/La 1.875 Sr 0.125 NiO 4 /Au metal-semiconductormetal structure, displays a complementary optical and electrical modulation of capacitance, which can be attributed to the charge trapping/detrapping induced Schottky barrier variation. It further exhibits versatile synaptic functions, such as photonic potentiation/electric depression, pairedpulse facilitation, short/longterm memory, and "learningexperience" behavior. Moreover, the photoplasticity of the memcapacitor can be modulated by varying the frequency of applied AC voltage, thus enabling selfadaptive optical signal detection and mimicry of interestmodulated human visual memory. Therefore, it represents a new paradigm for artificial optoelectronic synapses and opens up opportunities for developing lowpower humanoid optoelectronic devices.
“…Boland and co‐workers developed a TiO 2 nanowire memristive synapse using combined optical and electrical stimulation . Figure a shows the scanning electron microscopy image of a TiO 2 nanowire with Au contacts.…”
Section: Photoelectric Synapsesmentioning
confidence: 99%
“…f) Schematic energy band diagram of the Au/TiO 2 interface (i) at 2 V hold condition and (ii) during excitation with coincident stimuli composed of a voltage (Δ V ) and optical ( ħω ) pulse. Reproduced with permission . Copyright 2016, Wiley‐VCH.…”
Neuromorphic computing based on a non‐von Neumann architecture is a promising way for the efficient implementation of artificial intelligence. A neuromorphic computing system is mainly composed of artificial synapses and neurons. Various electronic neuromorphic devices have been developed by different technologies. Neuromorphic photonics combines the efficiency of neural networks and the speed of photonics to build computing systems. Compared with their electronic counterparts, photonic neurons and synapses have the potential advantages of ultrafast operation speed, large bandwidth, and no electrical interconnect power loss, inherent to the computing by optical means. Therefore, photonic neuromorphic devices are attracting more and more attention. This work reviews the recent advances in the development of photonic synapses. Both purely photonic synapses and photoelectric synapses are described. Their structures and working mechanisms are discussed in detail.
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