Compliance-Free Multileveled Resistive Switching in a Transparent 2D Perovskite for Neuromorphic Computing

2D Halide Perovskites for High-Performance Resistive Switching Memory and Artificial Synapse Applications

Metal halide perovskites (MHPs) are considered as promising candidates in the application of nonvolatile high-density, low-cost resistive switching (RS) memories and artificial synapses, resulting from their excellent electronic and optoelectronic properties including large light absorption coefficient, fast ion migration, long carrier diffusion length, low trap density, high defect tolerance. Among MHPs, 2D halide perovskites have exotic layered structure and great environment stability as compared with 3D counterparts. Herein, recent advances of 2D MHPs for the RS memories and artificial synapses realms are comprehensively summarized and discussed, as well as the layered structure properties and the related physical mechanisms are presented. Furthermore, the current issues and developing roadmap for the next-generation 2D MHPs RS memories and artificial synapse are elucidated.

Quasi-2D Lead-Tin Perovskite Memory Devices Fabricated by Blade Coating

Two terminal passive devices are regarded as one of the promising candidates to solve the processor-memory bottleneck in the Von Neumann computing architectures. Many different materials are used to fabricate memory devices, which have the potential to act as synapses in future neuromorphic electronics. Metal halide perovskites are attractive for memory devices as they display high density of defects with a low migration barrier. However, to become promising for a future neuromorphic technology, attention should be paid on non-toxic materials and scalable deposition processes. Herein, it is reported for the first time the successful fabrication of resistive memory devices using quasi-2D tin-lead perovskite of composition (BA)2 MA4 (Pb0.5 Sn0.5 )5 I16 by blade coating. The devices show typical memory characteristics with excellent endurance (2000 cycles), retention (105  s), and storage stability (3 months). Importantly, the memory devices successfully emulate synaptic behaviors such as spike-timing-dependent plasticity, paired-pulse facilitation, short-term potentiation, and long-term potentiation. A mix of slow (ionic) transport and fast (electronic) transport (charge trapping and de-trapping) is proven to be responsible for the observed resistive switching behavior.

Site-Specific Emulation of Neuronal Synaptic Behavior in Au Nanoparticle-Decorated Self-Organized TiOx Surface

Neuromorphic computing is a potential approach for imitating massive parallel processing capabilities of a bio-synapse. To date, memristors have emerged as the most appropriate device for designing artificial synapses for this purpose due to their excellent analog switching capacities with high endurance and retention. However, to build an operational neuromorphic platform capable of processing high-density information, memristive synapses with nanoscale footprint are important, albeit with device size scaled down, retaining analog plasticity and low power requirement often become a challenge. This paper demonstrates site-selective self-assembly of Au nanoparticles on a patterned TiOx layer formed as a result of ion-induced self-organization, resulting in site-specific resistive switching and emulation of bio-synaptic behavior (e.g., potentiation, depression, spike rate-dependent and spike timing-dependent plasticity, paired pulse facilitation, and post tetanic potentiation) at nanoscale. The use of local probe-based methods enables nanoscale probing on the anisotropic films. With the help of various microscopic and spectroscopic analytical tools, the observed results are attributed to defect migration and self-assembly of implanted Au atoms on self-organized TiOx surfaces. By leveraging the site-selective evolution of gold-nanostructures, the functionalized TiOx surface holds significant potential in a multitude of fields for developing cutting-edge neuromorphic computing platforms and Au-based biosensors with high-density integration.

Recent Advances in Cerium Oxide-Based Memristors for Neuromorphic Computing

This review article attempts to provide a comprehensive review of the recent progress in cerium oxide (CeO2)-based resistive random-access memories (RRAMs). CeO2 is considered the most promising candidate because of its multiple oxidation states (Ce3+ and Ce4+), remarkable resistive-switching (RS) uniformity in DC mode, gradual resistance transition, cycling endurance, long data-retention period, and utilization of the RS mechanism as a dielectric layer, thereby exhibiting potential for neuromorphic computing. In this context, a detailed study of the filamentary mechanisms and their types is required. Accordingly, extensive studies on unipolar, bipolar, and threshold memristive behaviors are reviewed in this work. Furthermore, electrode-based (both symmetric and asymmetric) engineering is focused for the memristor's structures such as single-layer, bilayer (as an oxygen barrier layer), and doped switching-layer-based memristors have been proved to be unique CeO2-based synaptic devices. Hence, neuromorphic applications comprising spike-based learning processes, potentiation and depression characteristics, potentiation motion and synaptic weight decay process, short-term plasticity, and long-term plasticity are intensively studied. More recently, because learning based on Pavlov's dog experiment has been adopted as an advanced synoptic study, it is one of the primary topics of this review. Finally, CeO2-based memristors are considered promising compared to previously reported memristors for advanced synaptic study in the future, particularly by utilizing high-dielectric-constant oxide memristors.

Low-Dimensional Metal-Halide Perovskites as High-Performance Materials for Memory Applications

Metal-halide perovskites have drawn profuse attention during the past decade, owing to their excellent electrical and optical properties, facile synthesis, efficient energy conversion, and so on. Meanwhile, the development of information storage technologies and digital communications has fueled the demand for novel semiconductor materials. Low-dimensional perovskites have offered a new force to propel the developments of the memory field due to the excellent physical and electrical properties associated with the reduced dimensionality. In this review, the mechanisms, properties, as well as stability and performance of low-dimensional perovskite memories, involving both molecular-level perovskites and structure-level nanostructures, are comprehensively reviewed. The property-performance correlation is discussed in-depth, aiming to present effective strategies for designing memory devices based on this new class of high-performance materials. Finally, the existing challenges and future opportunities are presented.

Image processing with a multi-level ultra-fast three dimensionally integrated perovskite nanowire array

Besides its ubiquitous applications in optoelectronics, halide-perovskites (HPs) have also carved a niche in the domain of resistive switching memories (Re-RAMs). However owing to the material and electrical instability challenges faced by HP thin-films, rarely perovskite Re-RAMs are used to experimentally demonstrate data processing which is a fundamental requirement for neuromorphic applications. Here, for the first time, lead-free, ultrahigh density HP nanowire (NW) array Re-RAM has been utilized to demonstrate image processing via design of convolutional kernels. The devices exhibited superior switching characteristics including a high endurance of 5 × 10⁶ cycles, an ultra-fast erasing and writing speed of 900 ps and 2 ns, respectively, and a retention time >5 × 10⁴ s for the resistances. The work is bolstered by an in-depth mechanistic study and first-principles simulations which provide evidence of electrochemical metallization triggering the switching. Employing the robust multi-level switching behaviour, image processing functions of embossing, outlining and sharpening were successfully implemented.

Mixed-Dimensional Formamidinium Bismuth Iodides Featuring In-Situ Formed Type-I Band Structure for Convolution Neural Networks

For valence change memory (VCM)-type synapses, a large number of vacancies help to achieve very linearly changed dynamic range, and also, the low activation energy of vacancies enables low-voltage operation. However, a large number of vacancies increases the current of artificial synapses by acting like dopants, which aggravates low-energy operation and device scalability. Here, mixed-dimensional formamidinium bismuth iodides featuring in-situ formed type-I band structure are reported for the VCM-type synapse. As compared to the pure 2D and 0D phases, the mixed phase increases defect density, which induces a better dynamic range and higher linearity. In addition, the mixed phase decreases conductivity for non-paths despite a large number of defects providing lots of conducting paths. Thus, the mixed phase-based memristor devices exhibit excellent potentiation/depression characteristics with asymmetricity of 3.15, 500 conductance states, a dynamic range of 15, pico ampere-scale current level, and energy consumption per spike of 61.08 aJ. A convolutional neural network (CNN) simulation with the Canadian Institute for Advanced Research-10 (CIFAR-10) dataset is also performed, confirming a maximum recognition rate of approximately 87%. This study is expected to lay the groundwork for future research on organic bismuth halide-based memristor synapses usable for a neuromorphic computing system.

Nanostructured perovskites for nonvolatile memory devices

Perovskite materials have driven tremendous advances in constructing electronic devices owing to their low cost, facile synthesis, outstanding electric and optoelectronic properties, flexible dimensionality engineering, and so on. Particularly, emerging nonvolatile memory devices (eNVMs) based on perovskites give birth to numerous traditional paradigm terminators in the fields of storage and computation. Despite significant exploration efforts being devoted to perovskite-based high-density storage and neuromorphic electronic devices, research studies on materials' dimensionality that has dominant effects on perovskite electronics' performances are paid little attention; therefore, a review from the point of view of structural morphologies of perovskites is essential for constructing perovskite-based devices. Here, recent advances of perovskite-based eNVMs (memristors and field-effect-transistors) are reviewed in terms of the dimensionality of perovskite materials and their potentialities in storage or neuromorphic computing. The corresponding material preparation methods, device structures, working mechanisms, and unique features are showcased and evaluated in detail. Furthermore, a broad spectrum of advanced technologies (e.g., hardware-based neural networks, in-sensor computing, logic operation, physical unclonable functions, and true random number generator), which are successfully achieved for perovskite-based electronics, are investigated. It is obvious that this review will provide benchmarks for designing high-quality perovskite-based electronics for application in storage, neuromorphic computing, artificial intelligence, information security, etc.

ABO3 multiferroic perovskite materials for memristive memory and neuromorphic computing

The unique electron spin, transfer, polarization and magnetoelectric coupling characteristics of ABO₃ multiferroic perovskite materials make them promising candidates for application in multifunctional nanoelectronic devices. Reversible ferroelectric polarization, controllable defect concentration and domain wall movement originated from the ABO₃ multiferroic perovskite materials promotes its memristive effect, which further highlights data storage, information processing and neuromorphic computing in diverse artificial intelligence applications. In particular, ion doping, electrode selection, and interface modulation have been demonstrated in ABO₃-based memristive devices for ultrahigh data storage, ultrafast information processing, and efficient neuromorphic computing. These approaches presented today including controlling the dopant in the active layer, altering the oxygen vacancy distribution, modulating the diffusion depth of ions, and constructing the interface-dependent band structure were believed to be efficient methods for obtaining unique resistive switching (RS) behavior for various applications. In this review, internal physical dynamics, preparation technologies, and modulation methods are systemically examined as well as the progress, challenges, and possible solutions are proposed for next generation emerging ABO₃-based memristive application in artificial intelligence.

2D Position-Sensitive Hybrid-Perovskite Detectors

Hybrid organic-inorganic perovskites (HOIPs) have emerged as a versatile class of semiconductors for numerous optoelectronic applications. Here, we demonstrate light-excitation-dependent two-dimensional (2D) position-sensitive detectors (PSDs) using a mixed-phase perovskite, FA_0.83Cs_0.17Pb(I_0.9Br_0.1)₃, as the active semiconductor, incorporated within a five-terminal device geometry. The light-induced lateral photovoltage, which is initiated by selective charge transfer across the metal-perovskite barrier interface, is utilized to achieve the excitation-position-dependent electric response. The 2D PSD devices exhibit a spatially dependent linear variation of the photosignal with sensitivity >50 μV mm^-1 and a low position detection error (1-2%), making them suitable for applications such as quadrant detectors. Further, it is observed that the device architecture plays a key role in controlling the dynamics and linearity of the HOIP PSDs. The large active area devices (up to ∼2 cm × 2 cm) exhibit a distinct spatial variation of the photosignal. We utilize the functionality of the PSD device for light-tracking applications by implementing a continuous detection scheme.

Halide Perovskites: A New Era of Solution-Processed Electronics

Organic-inorganic mixed halide perovskites have emerged as an excellent class of materials with a unique combination of optoelectronic properties, suitable for a plethora of applications ranging from solar cells to light-emitting diodes and photoelectrochemical devices. Recent works have showcased hybrid perovskites for electronic applications through improvements in materials design, processing, and device stability. Herein, a comprehensive up-to-date review is presented on hybrid perovskite electronics with a focus on transistors and memories. These applications are supported by the fundamental material properties of hybrid perovskite semiconductors such as tunable bandgap, ambipolar charge transport, reasonable mobility, defect characteristics, and solution processability, which are highlighted first. Then, recent progresses on perovskite-based transistors are reviewed, covering aspects of fabrication process, patterning techniques, contact engineering, 2D versus 3D material selection, and device performance. Furthermore, applications of perovskites in nonvolatile memories and artificial synaptic devices are presented. The ambient instability of hybrid perovskites and the strategies to tackle this bottleneck are also discussed. Finally, an outlook and opportunities to develop perovskite-based electronics as a competitive and feasible technology are highlighted.

Ge quantum wire memristor

Despite being known of for decades, the actual realization of memory devices based on the memristive effect is progressing slowly, due to processing requirements and the need for exotic materials which are not compatible with today's complementary-metal-oxide-semiconductor (CMOS) technology. Here, we report an experimental study on a Ge quantum wire device featuring distinct signatures of memristive behavior favorable for integration in CMOS platform technology. Embedding the quasi-1D Ge quantum wire into an electrostatically modulated back-gated field-effect transistor, we demonstrate that individual current transport channels can be addressed directly by controlling the surface trap assisted electrostatic gating. The resulting quantization of the current represents the ultimate limit of memristors with practically zero off-state current and low footprint. In addition, the proposed device has the advantage of non-destructive successive reading cycles capability. Importantly, our findings provide a framework towards fully CMOS compatible ultra-scaled Ge based memristors.

Opportunity of the Lead-Free All-Inorganic Cs3Cu2I5 Perovskite Film for Memristor and Neuromorphic Computing Applications

Recently, several types of lead halide perovskites have been demonstrated as active layers in resistive switching memory or artificial synaptic devices for neuromorphic computing applications. However, the thermal instability and toxicity of lead halide perovskites severely restricted their further practical applications. Herein, the environmentally friendly and uniform Cs₃Cu₂I₅ perovskite films are introduced to act as the active layer in the Ag/Cs₃Cu₂I₅/ITO memristor. Generally, the Ag ions could react with iodide ions and form AgI_x compounds easily, so the Ag/PMMA/Cs₃Cu₂I₅/ITO memristor was designed by employing the ultrathin polymethylmethacrylate (PMMA) layer to avoid the direct contact between the top Ag electrode and Cs₃Cu₂I₅ perovskite films. After optimization, the obtained memristor demonstrated bipolar resistive switching with low operating voltage (< ±1 V), large on/off ratio (10²), stable endurance (100 cycles), and long retention (>10⁴ s). Additionally, biological synaptic behaviors including long-term potentiation and long-term depression have been investigated. By using the MNIST handwritten recognition data set, the handwritten recognition rate based on experimental data could reach 94%. In conclusion, our work provides the opportunity of exploring the novel application for the development of next-generation neuromorphic computing based on lead-free halide perovskites.

Controllable digital resistive switching for artificial synapses and pavlovian learning algorithm

The fundamental unit of the nervous system is a synapse, which is involved in transmitting information between neurons as well as learning, memory, and forgetting processes. Two-terminal memristors can fulfil most of these requirements; however, their poor dynamic changes in resistance to input electric stimuli remain an obstacle, which must be improved for accurate and quick information processing. Herein, we demonstrate the synaptic properties of ZnO-based memristors, which were significantly enhanced (∼340 times) by geometrical modulation due to the localized electric field enhancement. Specifically, by inserting Ag-nanowires and Ag-dots into the ZnO/Si interface, the resistive switching could be controlled from a digital to analog mode. A finite element simulation revealed that the presence of Ag could enhance the localized electric field, which in turn improved the migration of ionic species. Further, the device showed a variety of comprehensive synaptic functions, for instance, paired-pulse facilitation and transformation from short-term plasticity to long-term plasticity, including the Pavlovian associative learning process in a human brain. Our study presents a novel architecture to enhance the synaptic sensitivity, and its uses in practical applications, including the artificial learning algorithm.

A Transparent Photonic Artificial Visual Cortex

Mimicking brain-like functionality with an electronic device is an essential step toward the design of future technologies including artificial visual and memory applications. Here, a proof-of-concept all-oxide-based (NiO/TiO₂ ) highly transparent (54%) heterostructure is proposed and demonstrated, which mimics the primitive functions of the visual cortex. Specifically, orientation selectivity and spatiotemporal processing similar to that of the visual cortex are demonstrated using direct optical stimuli under the self-biased condition due to photovoltaic effect, illustrating an energy-efficient approach for neuromorphic computing. The photocurrent of the device can be modulated from zero to 80 µA by simply rotating the slit by 90°. The device shows fast rise and fall times of 3 and 6 ms, respectively. Based on Kelvin probe force measurements, the observed results are attributed to a lateral photovoltaic effect. This highly transparent, self-biased, photonic triggered device paves the way for the advancement of energy-efficient neuromorphic computation.

Air-Stable Lead-Free Perovskite Thin Film Based on CsBi3I10 and Its Application in Resistive Switching Devices

The development of organic-inorganic hybrid perovskite materials has been rapid in recent years; but their applications are limited by the toxicity and stability of the materials. To address these issues in the context of resistive switching devices, an inorganic lead-free perovskite namely CsBi₃I₁₀ is developed. Uniform and pinhole-free CsBi₃I₁₀ thin films can be fabricated by using CsI-rich precursor solution via a facile antisolvent-assisted spin-coating method. The nonvolatile resistive switching devices based on CsBi₃I₁₀ demonstrate a large on/off ratio (10³), reliable retention properties (10⁴ s), and endurance (150 cycles). Conductive atomic force microscopy reveals that the high- and low-resistance states are formed by breaking and formation of conductive filaments in the perovskite thin film. Because of the excellent stability of the CsBi₃I₁₀ perovskite, the devices exhibit no obvious change in resistive switching behavior even after over 2 month storage in an ambient (60% relative humidity) environment. Our work suggests that the all-inorganic lead-free CsBi₃I₁₀ perovskite has great potential in resistive switching memory as well as in other optoelectronic devices where toxicity and stability are a concern.

High-Performance Nanofloating Gate Memory Based on Lead Halide Perovskite Nanocrystals

Lead halide perovskites have been extensively investigated in a host of optoelectronic devices, such as solar cells, light-emitting diodes, and photodetectors. The halogen vacancy defects arising from the halogen-poor growth environment are normally regarded as an unfavorable factor to restrict the device performance. Here, for the first time, we demonstrate the utilization of the vacancy defects in lead halide perovskite nanostructures for achieving high-performance nanofloating gate memories (NFGMs). CH₃NH₃PbBr₃ nanocrystals (NCs) were uniformly decorated on the CdS nanoribbon (NR) surface via a facile dip-coating process, forming a CdS NR/CH₃NH₃PbBr₃ NC core-shell structure. Significantly, owing to the existence of sufficient carrier trapping states in CH₃NH₃PbBr₃ NCs, the hybrid device possessed an ultralarge memory window up to 77.4 V, a long retention time of 12 000 s, a high current ON/OFF ratio of 7 × 10⁷, and a long-term air stability for 50 days. The memory window of the device is among the highest for the low-dimensional nanostructure-based NFGMs. Also, this strategy shows good universality and can be extended to other perovskite nanostructures for the construction of high-performance NFGMs. This work paves the way toward the fabrication of new-generation, high-capacity nonvolatile memories using lead halide perovskite nanostructures.

A Highly Transparent Artificial Photonic Nociceptor

A nociceptor is an essential element in the human body, alerting us to potential damage from extremes in temperature, pressure, etc. Realizing nociceptive behavior in an electronics device remains a central issue for researchers, designing neuromorphic devices. This study proposes and demonstrates an all-oxide-based highly transparent ultraviolet-triggered artificial nociceptor, which responds in a very similar way to the human eye. The device shows a high transmittance (>65%) and very low absorbance in the visible region. The current-voltage characteristics show loop opening, which is attributed to the charge trapping/detrapping. Further, the ultraviolet-stimuli-induced versatile criteria of a nociceptor such as a threshold, relaxation, allodynia, and hyperalgesia are demonstrated under self-biased condition, providing an energy-efficient approach for the neuromorphic device operation. The reported optically controlled features open a new avenue for the development of transparent optoelectronic nociceptors, artificial eyes, and memory storage applications.

Time-Resolved Electrical Scanning Probe Microscopy of Layered Perovskites Reveals Spatial Variations in Photoinduced Ionic and Electronic Carrier Motion

We study light-induced dynamics in thin films comprising Ruddlesden-Popper phases of the layered 2D perovskite (C₄H₉NH₃)₂PbI₄. We probe ionic and electronic carrier dynamics using two complementary scanning probe methods, time-resolved G-mode Kelvin probe force microscopy and fast free time-resolved electrostatic force microscopy, as a function of position, time, and illumination. We show that the average surface photovoltage sign is dominated by the band bending at the buried perovskite-substrate interface. However, the film exhibits substantial variations in the spatial and temporal response of the photovoltage. Under illumination, the photovoltage equilibrates over hundreds of microseconds, a time scale associated with ionic motion and trapped electronic carriers. Surprisingly, we observe that the surface photovoltage of the 2D grain centers evolves more rapidly in time than at the grain boundaries. We propose that the slower evolution at grain boundaries is due to a combination of ion migration occurring between PbI₄ planes, as well as electronic carriers traversing grain boundary traps, thereby changing the time-dependent band unbending at grain boundaries. These results provide a model for the photoinduced dynamics in 2D perovskites and are a useful basis for interpreting photovoltage dynamics on hybrid 2D/3D structures.

A non-volatile "programmable" transparent multilevel ultra-violet perovskite photodetector

Due to their outstanding physical properties, perovskite materials are considered to be promising semiconductors for next-generation optoelectronics. However, these materials are often unstable under an ambient atmosphere and ultra-violet illumination. Therefore, the construction of an air-stable visible light transparent perovskite-based ultra-violet photodetector is still highly challenging. In this study, we go beyond the conventional operation of photodetectors by utilizing the undesired hysteresis loop in the typical current-voltage characteristics of perovskites and design a (C4H9NH3)2PbBr4-based high-performance visible transparent programmable ultra-violet photodetector. The photodetector shows multiple operating levels and can switch from one level to another with a short electric pulse. The photodetector exhibits a fast response time of ∼2 ms, good responsivity of ∼32 mA W-1 and detectivity of 8.5 × 108 Jones with a low working voltage of 0.5 V. Moreover, the photodetector shows long-term stability, and the optoelectronic performance is retained under ambient conditions. This breakthrough in the controlled tunable features opens a new avenue for the development of multipurpose transparent optoelectronic devices.