† Corresponding author. E-mail:
Project supported by the National Key R&D Program of China (Grant No. 2017YFB0405600), the National Natural Science Foundation of China (Grant Nos. 61674153, 61722407, 61974090, and 61904099), and the Natural Science Foundation of Shanghai, China (Grant No. 19ZR1474500).
With the need of the internet of things, big data, and artificial intelligence, creating new computing architecture is greatly desired for handling data-intensive tasks. Human brain can simultaneously process and store information, which would reduce the power consumption while improve the efficiency of computing. Therefore, the development of brain-like intelligent device and the construction of brain-like computation are important breakthroughs in the field of artificial intelligence. Memristor, as the fourth fundamental circuit element, is an ideal synaptic simulator due to its integration of storage and processing characteristics, and very similar activities and the working mechanism to synapses among neurons which are the most numerous components of the brains. In particular, memristive synaptic devices with optoelectronic responding capability have the benefits of storing and processing transmitted optical signals with wide bandwidth, ultrafast data operation speed, low power consumption, and low cross-talk, which is important for building efficient brain-like computing networks. Herein, we review recent progresses in optoelectronic memristor for neuromorphic computing, including the optoelectronic memristive materials, working principles, applications, as well as the current challenges and the future development of the optoelectronic memristor.
In recent years, as the information technology advances increasingly faster, the economical-technical Moore’s law that well dominated the past-century evolution of the semiconductor and integrated circuit industry is about to reach its limits in the foreseeable future at about the 2–3 nm node.[1] Simultaneously, due to the limitations of the traditional von Neumann computer architecture that generate significant latency and power consumption during frequent data movement between the physically separated central processing unit (CPU) and the memory hierarchy,[2,3] the pace of the overall computing performance improvement gradually slows down. New computing paradigms are greatly desired to repower the capability that human society deals with the big data. Mammalian brain has the ability to simultaneously store, integrate, and process information through a densely coordinated network of synapses and neurons,[4] which can greatly reduce the power consumption and improve the data management efficiency in the meanwhile when handling the analog signals detected by the sensory organs (e.g., visual information received by the retina). Inspired by the human brain’s high integration of information processing and storage, neuromorphic computing utilizing artificial neural networks built from man-made neurons and synapses is expected to break through the von Neumann bottleneck to achieve efficient and low-cost information manipulation.
Since the conceptual propose by Chua in 1971[5] and its first device demonstration in 2008,[6] memristor, as the fourth basic electronic circuit element in addition to the long-established resistor, capacitor, and inductor, is a two-terminal resistor built from top and bottom electrodes and intermediate insulating dielectric layer, and carries memory function that memorizes the new resistance state induced by voltage and current. Generally, the conductance states of a memristor can be modulated non-volatilely and reversibly through an external electric field, including steep (digital) and gradual (analog) changes in conductance.[7] The former can be used for storing and processing information, and the latter is used to simulate synaptic due to similarity to biological synapses in both the device architecture and the electrical behaviors (Figs.
Excitingly, when light regulation is introduced in memristors as an additional dimension of control approach to regulate the evolution of the CFs or the interfacial barriers, the device conductance can be modified by both pure optical means with different wavelength and intensity of the illumination, and the synergistic interplay between the optical and electric fields. Benefiting from the ultrafast operation speed, virtually unlimited bandwidth, avoidance of the crosstalk interference, elimination of electrical Joule heating, and the potential of functional integration involving optical signal sensing, handling, and storing in a single cell, optoelectronic memristors are considered as promising candidates for multifunctional neuromorphic computing (artificial visual systems, in particular) applications.[14,15]
In this contribution, we are aiming to give a timely and comprehensive review of the recent progress on the optoelectronic memristor that covers all the material, mechanism, device aspects, and briefly discuss their potential application scenario and future developments. Focus will be first concentrated on the photosensitive material systems that can be employed in optoelectronic memristive switching effects, classifying as inorganic metal oxides, organics, organic–inorganic halide perovskites, and two-dimensional (2D) materials. Afterwards, the working principles of optoelectronic memristor devices, including the light-induced or light-assisted modulation of the interface barrier, molecular isomerization, ion diffusion, chemical reaction, and structural transition, are discussed. Finally, a brief overview of the device application in neuromorphic computing, some important challenges, and future prospective research areas is summarized.
To physically implement optoelectronic memristors, photosensitive semiconductor or insulating materials should be used as the switching matrix. Till date, various of materials, including the metal oxide system, organic materials, organic–metal halide perovskite, and 2D materials, have been proposed to be used in constructing optoelectronic memristive devices.[16]
Metal oxides, having excellent optical, electrical, and magnetic properties, are important fundamental materials in the fields of electronic and energy devices.[17–19] In particular, the oxygen defect contents of oxide semiconductors can be regulated efficiently by external fields, which allows the easy modulation of their Fermi energy level and conductance for optoelectronic applications.[20,21] At present, binary, ternary, and complex metal oxides are widely used in optoelectronic memristors.
Due to the fluorite geometry that can tolerate the presence of oxygen vacancy defects inside the lattice while maintain its crystalline structure complete, binary cerium oxide (CeO2) is widely explored as an active material in electro-catalysis (e.g., oxygen reduction reactions, ORR) areas. More importantly, the introduction of the defect energy levels into the bandgap of the material also leads to a good optical response in the broad spectrum from ultraviolet (UV) to visible range.[22–25] Therefore, using CeO2 as the photosensitive dielectric layer in memristor devices may result in possible optoelectronic modulation characteristics.[17,18] Tan et al. designed an optoelectronic memristor with cerium oxide as the switching layer, and transparent conductive oxide indium-tin oxide (ITO) and aluminum (Al) as the top/bottom electrodes, respectively (Fig.
Different from what happens in cerium oxide, the light-induced manipulation of molybdenum valence states in the molybdenum oxide thin film may also give rise to device resistance changes.[26–28] Zhou and co-workers designed a Pb/MoOx/ITO optoelectronic memristor for storing the optical information and executing light-tunable synaptic functions.[26] Cai et al.[27] designed and constructed a hybrid Au/PMMA/Ag/MoO3/P3HT:PCBM/ZnO/ITO device (inset of Fig.
Beyond the metal oxide semiconductors, the energy band diagram at two conductive oxide interfaces can also be controlled by optical means. For instance, the Fermi level of the conductive ternary oxide Nb-doped (0.7 wt.%) SrTiO3 is usually below its conduction band. When Nb:SrTiO3 forms a junction with ITO, a Schottky barrier naturally exists at the ITO/Nb:SrTiO3 interface. Gao et al. constructed a simple double-layer ITO/Nb:SrTiO3 heterojunction artificial optoelectronic synapse, which shows responses in the entire visible light region (while more sensitive in the short wavelength range) (Fig.
In addition to the above materials, ZnO,[31,32] In2O3,[15,33] VO2,[34] In-Ga-ZnO,[9,35,36] all-inorganic perovskites[37] et al. have also been employed as photosensitive materials in optoelectronic memristor systems.
Most of the work on neuromorphic computing and memory simulation so far has been focusing on inorganic material devices. Theoretically, the change of the intrinsic properties in organic materials will also cause memristive switching for the construction of artificial synapse and neural networks.[38] In comparison with the inorganic counterparts, organic materials have the advantages of low cost, simple processing procedures, good mechanical flexibility and deformability, and the most important of all, the fine-tunability of their electronic properties through molecular design and synthesis.[39]
Huang et al.[40] reported a 2D organic semiconductor (OSC) C8-BTBT synthetized by a solution epitaxy method, the morphology of which is no longer influenced by the underneath substrates. Using C8-BTBT as the semiconductor channel and SiO2 as the gate insulating layer, a photo-responsible 2D OSC based synaptic transistor was fabricated successfully (Fig.
Nau et al.[41] designed and fabricated an organic photodiode (OPD), whose resistance was changed with photo-generated charge carriers upon illumination. The photoactive layer of the OPD device is typically a p–n bulk-heterojunction consisted of poly(3-hexylthiophen-2,5-diyl) (rr-P3HT) as the electron donating component and phenyl-C61-butyric acid methyl ester (PCBM) as the electron accepting host, sandwiched between two electrodes (Fig.
Beyond small organic molecules, photosensitive polymer materials can also be used as the switching media in optoelectronic memristor devices. Kemp’s team demonstrated an optoelectronic memristor, in which the azobenzene based polymer poly(disperse red 1 acrylate), called PDR1 A, is combined with zinc oxide (ZnO) as the active layer in ITO/ZnO/PDR1 A/Al structure devices (Fig.
Organic–inorganic halide perovskites (OHPs) are emerging star materials used in optoelectronic memristors in recent years. They have excellent light absorption characteristics, long electron–hole diffusion length, bipolar charge transport, abnormal physical defects, and adjustable band gap. CH3NH3PbI3 (MAPbI3) is currently the most representative material in OHPs.[32,44–48] The I– anions can diffuse spontaneously, which may lead to the iodine defects and influence the stability of the optoelectronic devices. In extreme cases, photovoltaic devices based on MAPbI3 may become short-circuited by I– migration. To suppress the spontaneous diffusion of I–, Zhu et al. used active metal (such as Ag) as anode materials to form stable AgIx at the electrode/MAPbI3 interface in Ag/MAPbI3/Au devices (Fig.
The optically modulated iodine vacancy movement in OHP based memristor devices was also observed by Wang and coworkers in Ag/MAPbI3/Pt devices (Fig.
Due to their ultra-thin structure and large specific surface area with high sensitivity to subtle changes happened in the local environment,[53–55] two-dimensional materials (especially their device electrical response characteristics) are very sensitive to the photo-excited charge detrapping processes.[56–59] With the rapid responding speed, multi-level switching potential, large ON/OFF ratio of the as-obtained photocurrent or photoconductivity,[60–62] 2D materials and their heterojunctions are promising candidates in optical sensing, data storage and processing, and neuromorphic computing applications.
So far, graphene, hexagonal boron nitride (h-BN), transition metal dichalcogenides (TMDs), and their heterojunctions have been widely used in optoelectronic synaptic devices.[63–69] For example, the monolayer MoS2 with direct band gap shows strong response to light irradiation. Utilizing the characteristics, Lee et al. designed a single-layer MoS2 based optoelectronic device for image sensing and detection (Fig.
In addition to the single component 2D materials, the van der Waals heterojunctions of multiple low-dimensional materials with different chemical, physical, and electronic characteristics can provide extra possibilities for more complex optoelectronic performances. Qin et al.\ first reported an optoelectronic random-access memory synaptic device based on graphene–carbon nanotubes (CNT) composite.[72] The conductance of the channel layer can be regulated by the light and electrical pulses, wherein the short-term synaptic plasticity (STP) is achieved by charge transfer between the graphene and carbon nanotubes species. With different gate voltages, the plasticity is flexibly regulated to get dynamic synapses with tunable weight. Lee et al.[69] reported a multilevel nonvolatile optical memory device based on the MoS2/h-BN/graphene heterostructure (Fig.
Beyond the above optoelectronic memristive materials, zero-dimensional quantum dots with unique edge effects are also used for optoelectronic memristors applications.[74–76] As compared with transition metal dioxides, the complex oxide systems generally need high temperature fabrication process, which is incompatible with the CMOS technology. In the meantime, an indirect band gap of these complex oxides is disadvantageous for optimizing the photoelectrical responses of the as-obtained devices. Thus, searching for dioxides with direct band gap and optimal optical-electrical characteristics could be a promising direction for the development of oxide based optoelectronic memristors. On the other hand, although perovskites exhibit excellent photo response, the poor air-humidity of this new class of organic–inorganic hybrid stability arises the critical hinderance that restricts their direct device applications. In recent years, due to the great potential in energy consumption reduction, the high-density integration ability, and the sizable photo response in a wide spectra range, 2D materials have drawn great attention and have been intensively investigated. However, the production of large area and high-quality 2D membrane is only restricted to a few materials, the growth recipe of 2D materials with large area and high quality needs to be further explored. Although there exist plenty of material candidates showing potential for future optoelectronic memristor and neuromorphic computing applications, great amount of efforts are still highly desired to overcome the scientific and technological problems before making real advancements in this particularly interesting area.
Switching mechanisms of the memristor include the ion-migration with redox processes inducing the growth and dissolution of filaments[11,77] and the regulation of the interface barrier between electrodes and dielectric layer.[20,78] Therefore, memristor characteristics can be well modulated through photo-assisted ions diffusion, chemical reaction in solid films, and photo-modulated interface barrier.[17,26,79]
Resistance of memristors can be optically modulated by changing the Fermi level of the switching materials and the interfacial Schottky barrier formed between the electrode and the dielectric layer.[31,80,81] As discussed previously, Tan et al.[17,18] designed a CeO2–x/AlOy/Al junction, in which charge trapping sites are formed at the interface between the cerium oxide and the natively oxidized aluminum oxide layers (Figs.
In some organic or hybrid organic–inorganic memristors, optical illumination can induce isomerization of the organic molecules, which in turn will lead to tuning of the device conductance.[82–85] Jaafar reported that in a photoactive azobenzene polymer based memristor device, irradiation with polarized light results in expansion (by circularly polarized light beam) or contraction (by linearly polarized light beam) of the azobenzene polymer (Fig.
Qiu and coworkers designed a hybrid structure memory by combining photo-responsive diarylethene (DAE) molecule with semiconducting 2D materials (2DMs).[86] Through the reversible photochemical isomerization (open (DAE_o) and closed (DAE_c) isomer) of the DAEs under UV and visible light illumination, the molecular orbital energy levels and consequently the charge carrier transport across the underneath 2DMs (WSe2 and black phosphorus) can be effectively modulated. As shown in the energy-level alignment of WSe2/DAE_1, BP/DAE_2, and BP/DAE_3 in Figs.
As in the case of electro-catalysis, light illumination can assist the diffusion of vacancy and ionic species in the memristors.[44,87,88] Zhu found that under the bias, the visible light illumination can inhibit the formation of
Different from photo-generated electron and hole carriers in the small bandgap dielectrics, Zhou and co-workers reported that optical illumination can also induce the excitation of oxygen ions in large bandgap HfO2 (SiO2)-based memristors, wherein the migration of the mobile oxygen ions and their recombination with the oxygen vacancies will lead to the formation of CF and thus negative photoconductivity (NP) characteristic.[89,90] In addition, the conductance of the light-modulated memristor depends on the diameter of the filament received at different current compliance (CCL) limit levels. Figure
With the participation of proton in electrochemical reaction processes, the introduction of light onto memristive switching media can also lead to the change of valance state of the constituting elements. Upon the generation of protons from the environmental water by optical illumination, Zhou et al. demonstrated that a change of Mo ion valence state from 6+ to 5+ in the MoOx thin film can result in the transition of resistance states from HRS to LRS, accompanied by the color change of the thin film from transparent to blue of the hydrogen molybdenum bronze (HyMoOx) species.[26] The reaction formulas, involving the photogenerated electrons (electrons being excited to the conduction band of MoOx) and the protons (protons being produced through the holes reacting with the absorbed water molecules in the MoOx thin films),[93,94] are listed as follows:
Chen et al. displayed an artificial visual system constructed from a serial of a photosensitive image sensor and a resistive switching memory device (Fig.
Optoelectronic memristors, whose conductance can be co-regulated by optical and electric means, have many applications including optogenetics synaptic plasticity and brain-inspired computing, efficient neuromorphic visual systems, arithmetic computing, acceleration and artificial nociceptor, etc. The following section will discuss the recent advances in the applications of optoelectronic memristors.
As the next-generation computing for beyond von Neuman architecture, artificial synapse-based neuromorphic computing can merge the central processing unit and the memory hierarchy in a single integrated circuit chip, therefore eliminating the data transfer bottleneck for high efficiency computing. Generally, a synapse is a bridge that connects the pre- and post-neurons. Pre-neuron generates action potentials that can propagate to the next neuron and induces the postsynaptic action potentials (Fig.
One of the potential applications of the optical neural network is image processing (also known as pattern recognition tasks). In conventional image processing task, the optical signals in the images are converted to electronic signals before neuromorphic computing. For example, Chen and co-workers integrated In2O3-based image sensors with Al2O3-based memristors to realize the image sensing and memristor processing toward artificial visual memory.[15] As a forward step, optoelectronic memristors offer a light-involved tuning of synaptic weight, which is advantageous in lower energy consumption and faster processing time. Ham et al. constructed a two-terminal perovskite-based optoelectronic artificial synapse, where light illumination facilitated the iodine vacancies movement in the perovskite layer, resulting in easier realization of LTP.[51] To demonstrate the pattern recognition ability, a pattern “3” is input into a neural network composed of 28 by 28 input and 10 output neurons between which are individual synapses with different synaptic weights for recognition (Fig.
Moreover, by implementing synaptic and optical-sensing functions together on a van der Waals heterostructure, Seo demonstrated an optic-neural synaptic device that is able to recognize the target colored number from 28 by 28 RGB-colored images (similar to a color-blindness test).[63] They compared two separate neural networks (Fig.
As nearly 80% of the information that one human being receives is obtained through visual perception, it is necessary to emulate the neuromorphic visual systems with integrated sensor, data storage, and processing functions through optoelectronic memristors.[101,102] Gao and co-workers demonstrated an artificial optoelectronic synapse that is suitable for the mimicry of interest-modulated human visual memories, resembling the function of iris in human eyes.[14] This is realized through the light and electric field co-modulation of the Schottky barrier at the ITO/Nb:SrTiO3 interface, where a positive voltage bias is found to enhance the photo-responsive efficiency while a negative voltage bias will suppress the photo-responsiveness. The photo-response behaves in a neuromorphic manner, while the voltage bias could represent different level of interest. Assuming that a person has low, intermediate, and high interests to the letters L, I, and H after an identical exposure time, the artificial optoelectronic memristive synapses corresponding to these letters would output low, intermediate, and high currents, respectively (Fig.
In addition to the visual recognition and memory system, artificial optoelectronic nociceptors that alert us to potential damage from extreme illuminations have also been proposed. Kumar demonstrated a highly transparent artificial photonic nociceptor which is constructed by an antimony-doped tin oxide (ATO) layer, sandwiched between ZnO and fluorine-doped tin oxide (FTO).[31] As a result of the charge trapping/detrapping at the ZnO/ATO interface, the device exhibits a loop opening in the I–V characteristics and an optically trigged nociceptive behavior (Fig.
Optoelectronic memristor, being sensitive to light, has been extensively studied with a variety of material systems, working mechanisms, and applications. In this review, we firstly summarize the materials systems of optoelectronic memristor including metal oxide semiconductor, organic materials, organic–inorganic halide perovskites, and 2D materials. Then, the working mechanisms of optoelectronic memristor, including the photo-modulated interface barrier, light-excited molecular isomerization, and photo-assisted ions diffusion and electrochemical reactions, are discussed. Lastly, applications of the optoelectronic memristor in artificial synaptic emulation, image recognition, and neuromorphic visual system are stated. Optoelectronic memristors inherit the potential capability of neuromorphic computing through artificial neural network (ANN) algorithms that conventional memristive devices have demonstrated in the past decade, while offer additional figures of merit of extra modulation methods and possibility of function integration of image formation and recognition in a single system. Although great progress has been made in the field of optoelectronic memristor in the past decade, some important challenges, including obtaining more conductance states with photo-electric linear regulation, realizing reconfigurable neural network systems in hardware devices, and mimicking the brain’s complex functions in an efficient way, need to be overcome. Thus, in the future, further comprehensive understanding the working mechanism of the optoelectronic memristor, exploring new proof-of-concept optoelectronic materials and architectures with a continuously variable synaptic plasticity for efficient neuromorphic computing, developing ultra-fast optoelectronic memristors and relative testing tools, expanding their applications in human–computer interaction (e.g., neuromorphic robotics), constructing flexible and transparent optoelectronic memristors for simulating more complex retinal functions, and emulating more receptors including auditory and olfactory should be carried out to broaden the application scenario of the optoelectronic memristor devices.
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