Down-Scalable and Ultra-fast Memristors with Ultra-high Density Three-Dimensional Arrays of Perovskite Quantum Wires

Self-Assembly of Delta-Formamidinium Lead Iodide Nanoparticles to Nanorods: Study of Memristor Properties and Resistive Switching Mechanism

In the quest for advanced memristor technologies, this study introduces the synthesis of delta-formamidinium lead iodide (δ-FAPbI3) nanoparticles (NPs) and their self-assembly into nanorods (NRs). The formation of these NRs is facilitated by iodide vacancies, promoting the fusion of individual NPs at higher concentrations. Notably, these NRs exhibit robust stability under ambient conditions, a distinctive advantage attributed to the presence of capping ligands and a crystal lattice structured around face-sharing octahedra. When employed as the active layer in resistive random-access memory devices, these NRs demonstrate exceptional bipolar switching properties. A remarkable on/off ratio (105) is achieved, surpassing the performances of previously reported low-dimensional perovskite derivatives and α-FAPbI3 NP-based devices. This enhanced performance is attributed to the low off-state current owing to the reduced number of halide vacancies, intrinsic low dimensionality, and the parallel alignment of NRs on the FTO substrate. This study not only provides significant insights into the development of superior materials for memristor applications but also opens new avenues for exploring low-dimensional perovskite derivatives in advanced electronic devices.

In Situ Unveiling of the Resistive Switching Mechanism of Halide Perovskite-Based Memristors

The organic-inorganic halide perovskite has become one of the most promising candidates for next-generation memory devices, i.e. memristors, with excellent performance and solution-processable preparation. Yet, the mechanism of resistive switching in perovskite-based memristors remains ambiguous due to a lack of in situ visualized characterization methods. Here, we directly observe the switching process of perovskite memristors with in situ photoluminescence (PL) imaging microscopy under an external electric field. Furthermore, the corresponding element composition of conductive filaments (CFs) is studied, indicating that the metallic CFs with respect to the activity of the top electrode are essential for device performance. Finally, electrochemical impedance spectroscopy (EIS) is conducted to reveal that the transition of ion states is associated with the formation of metallic CFs. This study provides in-depth insights into the switching mechanism of perovskite memristors, paving a pathway to develop and optimize high-performance perovskite memristors for large-scale applications.

Solution Sequential Deposition Pseudo-Planar Heterojunction: An Efficient Strategy for State-of-Art Organic Solar Cells

Organic solar cells (OSCs) are considered as a promising new generation of clean energy. Bulk heterojunction (BHJ) structure has been widely employed in the active layer of efficient OSCs. However, precise regulation of morphology in BHJ is still challenging due to the competitive coupling between crystallization and phase separation. Recently, a novel pseudo-planar heterojunction (PPHJ) structure, prepared through solution sequential deposition, has attracted much attention. It is an easy-to-prepare structure in which the phase separation structures, interfaces, and molecular packing can be separately controlled. Employing PPHJ structure, the properties of OSCs, such as power conversion efficiency, stability, transparency, flexibility, and so on, are usually better than its BHJ counterpart. Hence, a comprehensive understanding of the film-forming process, morphology control, and device performance of PPHJ structure should be considered. In terms of the representative works about PPHJ, this review first introduces the fabrication process of active layers based on PPHJ structure. Second, the widely applied morphology control methods in PPHJ structure are summarized. Then, the influences of PPHJ structure on device performance and other property are reviewed, which largely expand its application. Finally, a brief prospect and development tendency of PPHJ devices are discussed with the consideration of their challenges.

Geometric Shape Recognition with an Ultra-High Density Perovskite Nanowire Array-Based Artificial Vision System

Artificial vision systems (AVS) have potential applications in visual prosthetics and artificially intelligent robotics, and they require a preprocessor and a processor to mimic human vision. Halide perovskite (HP) is a promising preprocessor and processor due to its excellent photoresponse, ubiquitous charge migration pathways, and innate hysteresis. However, the material instability associated with HP thin films hinders their utilization in physical AVSs. Herein, we have developed ultrahigh-density arrays of robust HP nanowires (NWs) rooted in a porous alumina membrane (PAM) as the active layer for an AVS. The NW devices exhibit gradual photocurrent change, responding to changes in light pulse duration, intensity, and number, and allow contrast enhancement of visual inputs with a device lifetime of over 5 months. The NW-based processor possesses temporally stable conductance states with retention >105 s and jitter <10%. The physical AVS demonstrated 100% accuracy in recognizing different shapes, establishing HP as a reliable material for neuromorphic vision systems.

Attaining inhibition of sneak current and versatile logic operations in a singular halide perovskite memristive device by introducing appropriate interface barriers

Emerging resistive switching devices hold the potential to realize densely packed passive nanocrossbar arrays, suitable for deployment as random access memory devices (ReRAMs) in both embedded and high-capacity storage applications. In this study, we have engineered ReRAMs comprising ITO/(UVO-treated) amorphous ZnO (a-ZnO)/MAPbI3/Ag which effectively mitigate cross-talk currents without additional components. Significantly, we successfully executed a comprehensive set of 12 distinct 2-input sequential logic functions in a single halide perovskite ReRAM unit for the first time. Furthermore, these logic functions are devoid of any dependency on external light sources, entail merely 1 or 2 logic steps, and showcase symmetrical operability. A superior resistive switching behavior was achieved by harmonizing the charge transport within the bulk MAPbI3 and the tunneling barriers at the interfaces. The outcomes indicate progress in mitigating cross-talk and executing multiple logic functions within a single halide perovskite ReRAM unit, offering a new perspective for the advancement of halide perovskite ReRAMs.

Effect of growth temperature on self-rectifying BaTiO3/ZnO heterojunction for high-density crossbar arrays and neuromorphic computing

In the quest for high-density integration and massive scalability, ferroelectric-based devices provide an achievable approach for nonvolatile crossbar array (CBA) architecture and neuromorphic computing. In this report, ferroelectric-semiconductor (Pt/BaTiO3/ZnO/Au) heterojunction-based devices are demonstrated to exhibit nonvolatile and synaptic characteristics. In this study, the ferroelectric (BaTiO3) layer was modulated at various growth temperatures of 350 °C, 450 °C, 550 °C and 650 °C. Growing temperature in the ferroelectric layer has a significant impact on resistive switching. The ferroelectricity of the BaTiO3 thin film enhanced by increasing temperature causes a substantial shift in the interface state density at heterojunction interface, which is crucial for self-rectification. Furthermore, this self-rectifying property advances to reduce the crosstalk problem without any selector device. Enhanced resistive switching and neuromorphic applications have been demonstrated using BaTiO3 heterostructure devices at 550 °C. The dynamic ferroelectric polarization switching in this heterojunction demonstrated linear conductance change in artificial synapses with 91 % recognition accuracy. Ferroelectric polarization reversal with a depletion region at the heterojunction interface is the responsible mechanism for the switching in these devices. Thus, these findings pave the way for designing low power high-density crossbar arrays and neuromorphic application based on ferroelectric-semiconductor heterostructures.

Resistive switching modulation by incorporating thermally enhanced layer in HfO2-based memristor

Oxide-based memristors by incorporating thermally enhanced layer (TEL) have showed great potential in electronic devices for high-efficient and high-density neuromorphic computing owing to the improvement of multilevel resistive switching. However, research on the mechanism of resistive switching regulation is still lacking. In this work, based on the method of finite element numerical simulation analysis, a bilayer oxide-based memristor Pt/HfO2(5 nm)/Ta2O5(5 nm)/Pt with the Ta2O5TEL was proposed. The oxygen vacancy concentrates distribution shows that the fracture of conductive filaments (CF) is at the interface where the local temperature is the highest during the reset process. The multilevel resistive switching properties were also obtained by applying different stop voltages. The fracture gap of CF can be enlarged with the increase of the stopping voltage, which is attributed to the heat-gathering ability of the TEL. Moreover, it was found that the fracture position of oxygen CF is dependent on the thickness of TEL, which exhibits a modulation of device RS performance. These results provide a theoretical guidance on the suitability of memristor devices for use in high-density memory and brain-actuated computer systems.

Digital image processing realized by memristor-based technologies

Today performance and operational efficiency of computer systems on digital image processing are exacerbated owing to the increased complexity of image processing. It is also difficult for image processors based on complementary metal-oxide-semiconductor (CMOS) transistors to continuously increase the integration density, causing by their underlying physical restriction and economic costs. However, such obstacles can be eliminated by non-volatile resistive memory technologies (known as memristors), arising from their compacted area, speed, power consumption high efficiency, and in-memory computing capability. This review begins with presenting the image processing methods based on pure algorithm and conventional CMOS-based digital image processing strategies. Subsequently, current issues faced by digital image processing and the strategies adopted for overcoming these issues, are discussed. The state-of-the-art memristor technologies and their challenges in digital image processing applications are also introduced, such as memristor-based image compression, memristor-based edge and line detections, and voice and image recognition using memristors. This review finally envisages the prospects for successful implementation of memristor devices in digital image processing.

Advancing Thermoelectric Materials: A Comprehensive Review Exploring the Significance of One-Dimensional Nano Structuring

Amidst the global challenges posed by pollution, escalating energy expenses, and the imminent threat of global warming, the pursuit of sustainable energy solutions has become increasingly imperative. Thermoelectricity, a promising form of green energy, can harness waste heat and directly convert it into electricity. This technology has captivated attention for centuries due to its environmentally friendly characteristics, mechanical stability, versatility in size and substrate, and absence of moving components. Its applications span diverse domains, encompassing heat recovery, cooling, sensing, and operating at low and high temperatures. However, developing thermoelectric materials with high-performance efficiency faces obstacles such as high cost, toxicity, and reliance on rare-earth elements. To address these challenges, this comprehensive review encompasses pivotal aspects of thermoelectricity, including its historical context, fundamental operating principles, cutting-edge materials, and innovative strategies. In particular, the potential of one-dimensional nanostructuring is explored as a promising avenue for advancing thermoelectric technology. The concept of one-dimensional nanostructuring is extensively examined, encompassing various configurations and their impact on the thermoelectric properties of materials. The profound influence of one-dimensional nanostructuring on thermoelectric parameters is also thoroughly discussed. The review also provides a comprehensive overview of large-scale synthesis methods for one-dimensional thermoelectric materials, delving into the measurement of thermoelectric properties specific to such materials. Finally, the review concludes by outlining prospects and identifying potential directions for further advancements in the field.

Recent progress in bio-voltage memristors working with ultralow voltage of biological amplitude

Neuromorphic systems built from memristors that emulate bioelectrical information processing in the brain may overcome the limitations of traditional computing architectures. However, functional emulation alone may still not attain all the merits of bio-computation, which uses action potentials of 50-120 mV at least 10 times lower than signal amplitude in conventional electronics to achieve extraordinary power efficiency and effective functional integration. Reducing the functional voltage in memristors to this biological amplitude can thus advance neuromorphic engineering and bio-emulated integration. This review aims to provide a timely update on the effort and progress in this burgeoning research direction, covering the aspects of device material composition, performance, working mechanism, and potential application.

A review of memristor: material and structure design, device performance, applications and prospects

With the booming growth of artificial intelligence (AI), the traditional von Neumann computing architecture based on complementary metal oxide semiconductor devices are facing memory wall and power wall. Memristor based in-memory computing can potentially overcome the current bottleneck of computer and achieve hardware breakthrough. In this review, the recent progress of memory devices in material and structure design, device performance and applications are summarized. Various resistive switching materials, including electrodes, binary oxides, perovskites, organics, and two-dimensional materials, are presented and their role in the memristor are discussed. Subsequently, the construction of shaped electrodes, the design of functional layer and other factors influencing the device performance are analyzed. We focus on the modulation of the resistances and the effective methods to enhance the performance. Furthermore, synaptic plasticity, optical-electrical properties, the fashionable applications in logic operation and analog calculation are introduced. Finally, some critical issues such as the resistive switching mechanism, multi-sensory fusion, system-level optimization are discussed.

On-device synaptic memory consolidation using Fowler-Nordheim quantum-tunneling

Introduction

For artificial synapses whose strengths are assumed to be bounded and can only be updated with finite precision, achieving optimal memory consolidation using primitives from classical physics leads to synaptic models that are too complex to be scaled in-silico. Here we report that a relatively simple differential device that operates using the physics of Fowler-Nordheim (FN) quantum-mechanical tunneling can achieve tunable memory consolidation characteristics with different plasticity-stability trade-offs.

Methods

A prototype FN-synapse array was fabricated in a standard silicon process and was used to verify the optimal memory consolidation characteristics and used for estimating the parameters of an FN-synapse analytical model. The analytical model was then used for large-scale memory consolidation and continual learning experiments.

Results

We show that compared to other physical implementations of synapses for memory consolidation, the operation of the FN-synapse is near-optimal in terms of the synaptic lifetime and the consolidation properties. We also demonstrate that a network comprising FN-synapses outperforms a comparable elastic weight consolidation (EWC) network for some benchmark continual learning tasks.

Discussions

With an energy footprint of femtojoules per synaptic update, we believe that the proposed FN-synapse provides an ultra-energy-efficient approach for implementing both synaptic memory consolidation and continual learning on a physical device.

Metal Halide Perovskite/Electrode Contacts in Charge-Transporting-Layer-Free Devices

Metal halide perovskites have drawn substantial interest in optoelectronic devices in the past decade. Perovskite/electrode contacts are crucial for constructing high-performance charge-transporting-layer-free perovskite devices, such as solar cells, field-effect transistors, artificial synapses, memories, etc. Many studies have evidenced that the perovskite layer can directly contact the electrodes, showing abundant physicochemical, electronic, and photoelectric properties in charge-transporting-layer-free perovskite devices. Meanwhile, for perovskite/metal contacts, some critical interfacial physical and chemical processes are reported, including band bending, interface dipoles, metal halogenation, and perovskite decomposition induced by metal electrodes. Thus, a systematic summary of the role of metal halide perovskite/electrode contacts on device performance is essential. This review summarizes and discusses charge carrier dynamics, electronic band engineering, electrode corrosion, electrochemical metallization and dissolution, perovskite decomposition, and interface engineering in perovskite/electrode contacts-based electronic devices for a comprehensive understanding of the contacts. The physicochemical, electronic, and morphological properties of various perovskite/electrode contacts, as well as relevant engineering techniques, are presented. Finally, the current challenges are analyzed, and appropriate recommendations are put forward. It can be expected that further research will lead to significant breakthroughs in their application and promote reforms and innovations in future solid-state physics and materials science.

Assessing the Drawbacks and Benefits of Ion Migration in Lead Halide Perovskites

Since the inception of the unprecedented rise of halide perovskites for photovoltaic research, ion migration has shadowed this material class with undesirable hysteresis and degradation effects, limiting its practical implementations. Unfortunately, the localized doping and electrochemical reactions triggered by ion migration cause many more undesirable effects that are often unreported or misinterpreted because they deviate from classical semiconductor behavior. In this Perspective, we provide a concise overview of such effects in halide perovskites, such as operational instability in photovoltaics, polarization-induced abnormal external quantum efficiency in light-emitting diodes, and energy channel shift and anomalous sensitivities in hard radiation detection. Finally, we highlight a unique use case of exploiting ion migration as a boon to design emerging memory technologies such as memristors for information storage and computing.

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.

Nanomicelles Array for Ultrahigh-Density Data Storage

High-density data storage devices based on organic and polymer materials are currently restricted by two key issues, size limitations and uniformity of memory cells. Herein, one triblock polymer is synthesized by ring-opening metathesis polymerization, where the polymer contains an electron-donor-acceptor (A₁ D) segment, an electron-acceptor (A₂ ) segment, and a hydrophilic segment, that shows ternary memory behavior in a conventional sandwich-type device. The polymers that have monodisperse molecular weight dispersity self-assemble into nanomicelles with a uniform size of 80 nm. Each nanomicelle is composed of an A₁ DA₂ -type hydrophobic core stabilized with a hydrophilic shell. Nanobowls based on conductive oxide are prepared via the template method, wherein the nanomicelles are present as independent nanoscale memory units to produce an array of micelle matrices. Investigations of the resulting nanomemory device using conductive atomic force microscopy show that the micelles exhibit a predominant semiconductor memory behavior. Compared to traditional ternary devices with a memory unit size of ≈1 mm, this innovative fabrication method based on arrayed uniform nanomicelles downscales the size of storage cells to 80 nm. Furthermore, the described system leads to a greatly enhanced storage density (>10⁸ times over the same area), which opens up new paths for further development of ultrahigh-density data storage devices.

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.

Metal Halide Perovskite-Based Memristors for Emerging Memory Applications

There is an increased demand for next-generation memory devices with high density and fast operation speed to replace conventional memory devices. Memristors are promising candidates for next-generation memory devices because of their scalability, stable data retention, low power consumption, and fast operation. Among the various types of memristors, halide perovskites exhibit potential as emerging materials for memristors by using hysteresis based on the movement of defects or ions in halide perovskites. However, research on the implementation of perovskite materials as memristors is in its early stages; some challenges and problems must be solved to enable the practical application of halide perovskites for next-generation memory devices. From this perspective, we highlight the recent progress in memristors that use halide perovskites. Moreover, we introduce a strategy to enhance the performance and analyze the operation mechanism of memory devices that use halide perovskites. Finally, we summarize the challenges in the development of device technology to use halide perovskites in next-generation memory devices.

Multifunctional and Transformative Metaphotonics with Emerging Materials

Future technologies underpinning multifunctional physical and chemical systems and compact biological sensors will rely on densely packed transformative and tunable circuitry employing nanophotonics. For many years, plasmonics was considered as the only available platform for subwavelength optics, but the recently emerged field of resonant metaphotonics may provide a versatile practical platform for nanoscale science by employing resonances in high-index dielectric nanoparticles and metasurfaces. Here, we discuss the recently emerged field of metaphotonics and describe its connection to material science and chemistry. For tunabilty, metaphotonics employs a variety of the recently highlighted materials such as polymers, perovskites, transition metal dichalcogenides, and phase change materials. This allows to achieve diverse functionalities of metasystems and metasurfaces for efficient spatial and temporal control of light by employing multipolar resonances and the physics of bound states in the continuum. We anticipate expanding applications of these concepts in nanolasers, tunable metadevices, metachemistry, as well as a design of a new generation of chemical and biological ultracompact sensing devices.

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.

Controlling the Grain Size of Dion-Jacobson-Phase Two-Dimensional Layered Perovskite for Memory Application

Organic-inorganic halide perovskites (OIHPs) have emerged as an active layer for resistive switching memory (RSM). Among various OIHPs, two-dimensional OIHPs are advantageous in RSMs because of their stability. This stability can be further improved using two-dimensional Dion-Jacobson OIHPs. Moreover, OIHP-based RSMs operated by the formation of halide-ion filaments are affected by grain boundaries because they can act as a shortcut for ion migration. Therefore, it is essential to control the grains in OIHPs for reliable memory operation. Here, we present RSMs using Dion-Jacobson OIHP with controlled grain sizes. The grain sizes of the OIHP are effectively controlled by adjusting the ratio of the N,N-dimethylformamide and dimethyl sulfoxide. The controlled grain sizes can modulate the paths for halide ion migration, which enables the change of the on/off ratio in RSM. In addition, cross-point array structure is essential for high-density memory applications. However, in the cross-point array structure, unwanted current flow through unselected memory cells can happen due to sneak-current paths, so it is necessary to suppress leakage current from neighboring cells by adopting selector devices. We demonstrate the application of selector devices to OIHP-based RSMs to prevent sneak current paths. These results provide the potential of OIHP for use in high-density memory applications.

Halide Perovskites for Resistive Switching Memory

Resistive switching random access memory (RRAM), also known as memristor, is regarded as an emerging nonvolatile memory and computing-in-memory technology to address the intrinsic physical limitations of conventional memory and the bottleneck of von Neumann architecture. In particular, halide perovskite RRAMs have attracted widespread attention in recent years because of their ionic migration nature and excellent photoelectric properties. This Perspective first provides a condensed overview of halide perovskite RRAMs based on materials, device performance, switching mechanism, and potential applications. Moreover, this Perspective attempts to detail the challenges, such as the quality of halide perovskite films, the compatible processing of device fabrication, the reliability of memory performance, and clarification of the switching mechanism, and further discusses how the outstanding challenges of halide perovskite RRAMs could be met in future research.

Halide Perovskites for Memristive Data Storage and Artificial Synapses

Halide perovskites have been noted for their exotic properties such as fast ion migration, tunable composition, facile synthetic routes, and flexibility in addition to large light absorption coefficients, long carrier diffusion lengths, and high defect tolerance. These properties have made halide perovskites promising materials for memristors. Applications in the field of resistive switching memory devices and artificial synapses for neuromorphic computing are especially noteworthy. This Perspective covers state-of-the-art perovskite-based memristive devices. Moreover, the fundamental mechanisms and characteristics of perovskite-based memristors are elucidated. Interesting opportunities to improve the performance of perovskite-based memristors for commercialization are provided, including improving film uniformity and air stability, controlling the stoichiometry, finding new all-inorganic and lead-free halide perovskites, and making perovskites into single crystals or quantum dots. We expect our Perspective to be the foundation of realizing next-generation halide perovskite-based memristors.