Effect of dysprosium and lutetium metal buffer layers on the resistive switching characteristics of Cu-Sn alloy-based conductive-bridge random access memory.

The conductive-bridge random access memory (CBRAM) has become one of the most suitable candidates for non-volatile memory in next-generation information and communication technology. The resistive switching (RS) mechanism of CBRAM depends on the formation/annihilation of the conductive filament (CF) between the active metal electrode and the inert electrode. However, excessive ion injection from the active electrode into the solid electrolyte reduces the uniformity and reliability of the RS devices. To solve this problem, we investigated the RS characteristics of a CuSn alloy active electrode with different compositions of Cux-Sn1-x (0.13 < X < 0.55). The RS characteristics were further improved by inserting a dysprosium (Dy) or lutetium (Lu) buffer layer at the interface of Cux-Sn1-x/Al2O3. Electrical analysis of the optimal Cu0.4-Sn0.73/Lu-based CBRAM exhibited stable RS behavior with low operation voltage (SET: 0.7 V and RESET: -0.3 V), a high on state/off state resistive ratio (106), AC cyclic endurance (>104), and stable retention (85 °C/10 years). To achieve these performance parameters, CFs were locally formed inside the electrolyte using a modified CuSn active electrode, and the amount of Cu-ion injection was reduced by inserting the Dy or Lu buffer layer between the CuSn active electrode and the electrolyte. In particular, conductive-atomic force microscopy results at the Dy or Lu/Al2O3 interface directly showed and defined the diameter of the CF.

Enhancement of resistive switching properties in Al2O3 bilayer-based atomic switches: multilevel resistive switching.

Atomic switches are considered to be building blocks for future non-volatile data storage and internet of things. However, obtaining device structures capable of ultrahigh density data storage, high endurance, and long data retention, and more importantly, understanding the switching mechanisms are still a challenge for atomic switches. Here, we achieved improved resistive switching performance in a bilayer structure containing aluminum oxide, with an oxygen-deficient oxide as the top switching layer and stoichiometric oxide as the bottom switching layer, using atomic layer deposition. This bilayer device showed a high on/off ratio (105) with better endurance (∼2000 cycles) and longer data retention (104 s) than single-oxide layers. In addition, depending on the compliance current, the bilayer device could be operated in four different resistance states. Furthermore, the depth profiles of the hourglass-shaped conductive filament of the bilayer device was observed by conductive atomic force microscopy.

High-performance one-dimensional halide perovskite crossbar memristors and synapses for neuromorphic computing.

Despite impressive demonstrations of memristive behavior with halide perovskites, no clear pathway for material and device design exists for their applications in neuromorphic computing. Present approaches are limited to single element structures, fall behind in terms of switching reliability and scalability, and fail to map out the analog programming window of such devices. Here, we systematically design and evaluate robust pyridinium-templated one-dimensional halide perovskites as crossbar memristive materials for artificial neural networks. We compare two halide perovskite 1D inorganic lattices, namely (propyl)pyridinium and (benzyl)pyridinium lead iodide. The absence of conjugated, electron-rich substituents in PrPyr+ prevents edge-to-face type π-stacking, leading to enhanced electronic isolation of the 1D iodoplumbate chains in (PrPyr)[PbI3], and hence, superior resistive switching performance compared to (BnzPyr)[PbI3]. We report outstanding resistive switching behaviours in (PrPyr)[PbI3] on the largest flexible crossbar implementation (16 × 16) to date - on/off ratio (>105), long term retention (105 s) and high endurance (2000 cycles). Finally, we put forth a universal approach to comprehensively map the analog programming window of halide perovskite memristive devices - a critical prerequisite for weighted synaptic connections in artificial neural networks. This consequently facilitates the demonstration of accurate handwritten digit recognition from the MNIST database based on spike-timing-dependent plasticity of halide perovskite memristive synapses.

Halide perovskite memristors as flexible and reconfigurable physical unclonable functions.

Physical Unclonable Functions (PUFs) address the inherent limitations of conventional hardware security solutions in edge-computing devices. Despite impressive demonstrations with silicon circuits and crossbars of oxide memristors, realizing efficient roots of trust for resource-constrained hardware remains a significant challenge. Hybrid organic electronic materials with a rich reservoir of exotic switching physics offer an attractive, inexpensive alternative to design efficient cryptographic hardware, but have not been investigated till date. Here, we report a breakthrough security primitive exploiting the switching physics of one dimensional halide perovskite memristors as excellent sources of entropy for secure key generation and device authentication. Measurements of a prototypical 1 kb propyl pyridinium lead iodide (PrPyr[PbI3]) weak memristor PUF with a differential write-back strategy reveals near ideal uniformity, uniqueness and reliability without additional area and power overheads. Cycle-to-cycle write variability enables reconfigurability, while in-memory computing empowers a strong recurrent PUF construction to thwart machine learning attacks.

One-Pot Synthesis and Structural Evolution of Colloidal Cesium Lead Halide-Lead Sulfide Heterostructure Nanocrystals for Optoelectronic Applications.

Heterostructures, combining perovskite nanocrystals (PNC) and chalcogenide quantum dots, could pave a path to optoelectronic device applications by enabling absorption in the near-infrared region, tailorable electronic properties, and stable crystal structures. Ideally, the heterostructure host material requires a similar lattice constant as the guest which is also constrained by the synthesis protocol and materials selectivity. Herein, we present an efficient one-pot hot-injection method to synthesize colloidal all-inorganic cesium lead halide-lead sulfide (CsPbX3 (X = Cl, Br, I)-PbS) heterostructure nanocrystals (HNCs) via the epitaxial growth of the perovskite onto the presynthesized PbS nanocrystals (NCs). Optical and structural characterization evidenced the formation of heterostructures. The embedding of PbS NCs into CsPbX3 perovskite allows the tuning of the absorption and emission from 400 to 1100 nm by tuning the size and composition of perovskite HNCs. The CsPbI3-PbS HNCs show enhanced stability in ambient conditions. The stability, tunable optical properties, and variable band alignments accessible in this system would have implications in the design of novel optoelectronic applications such as light-emitting diodes, photodetectors, photocatalysis, and photovoltaics.

Self healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics.

Sensory information processing in robot skins currently rely on a centralized approach where signal transduction (on the body) is separated from centralized computation and decision-making, requiring the transfer of large amounts of data from periphery to central processors, at the cost of wiring, latency, fault tolerance and robustness. We envision a decentralized approach where intelligence is embedded in the sensing nodes, using a unique neuromorphic methodology to extract relevant information in robotic skins. Here we specifically address pain perception and the association of nociception with tactile perception to trigger the escape reflex in a sensorized robotic arm. The proposed system comprises self-healable materials and memtransistors as enabling technologies for the implementation of neuromorphic nociceptors, spiking local associative learning and communication. Configuring memtransistors as gated-threshold and -memristive switches, the demonstrated system features in-memory edge computing with minimal hardware circuitry and wiring, and enhanced fault tolerance and robustness.

Transparent and Flexible Mayan-Pyramid-based Pressure Sensor using Facile-Transferred Indium tin Oxide for Bimodal Sensor Applications.

Transparent and conducting flexible electrodes have been successfully developed over the last few decades due to their potential applications in optoelectronics. However, recent developments in smart electronics, such as a direct human-machine interface, health-monitoring devices, motion-tracking sensors, and artificially electronic skin also require materials with multifunctional properties such as transparency, flexibility and good portability. In such devices, there remains room to develop transparent and flexible devices such as pressure sensors or temperature sensors. Herein, we demonstrate a fully transparent and flexible bimodal sensor using indium tin oxide (ITO), which is embedded in a plastic substrate. For the proposed pressure sensor, the embedded ITO is detached from its Mayan-pyramid-structured silicon mold by an environmentally friendly method which utilizes water-soluble sacrificial layers. The Mayan-pyramid-based pressure sensor is capable of six different pressure sensations with excellent sensitivity in the range of 100 Pa-10 kPa, high endurance of 105 cycles, and good pulse detection and tactile sensing data processing capabilities through machine learning (ML) algorithms for different surface textures. A 5 × 5-pixel pressure-temperature-based bimodal sensor array with a zigzag-shaped ITO temperature sensor on top of it is also demonstrated without a noticeable interface effect. This work demonstrates the potential to develop transparent bimodal sensors that can be employed for electronic skin (E-skin) applications.

Excellent Resistive Switching Performance of Cu-Se-Based Atomic Switch Using Lanthanide Metal Nanolayer at the Cu-Se/Al2O3 Interface.

The next-generation electronic society is dependent on the performance of nonvolatile memory devices, which has been continuously improving. In the last few years, many memory devices have been introduced. However, atomic switches are considered to be a simple and reliable basis for next-generation nonvolatile devices. In general, atomic switch-based resistive switching is controlled by electrochemical metallization. However, excess ion injection from the entire area of the active electrode into the switching layer causes device nonuniformity and degradation of reliability. Here, we propose the fabrication of a high-performance atomic switch based on Cu x-Se1- x by inserting lanthanide (Ln) metal buffer layers such as neodymium (Nd), samarium (Sm), dysprosium (Dy), or lutetium (Lu) between the active metal layer and the electrolyte. Current-atomic force microscopy results confirm that Cu ions penetrate through the Ln-buffer layer and form thin conductive filaments inside the switching layer. Compared with the Pt/Cu x-Se1- x/Al2O3/Pt device, the optimized Pt/Cu x-Se1- x/Ln/Al2O3/Pt devices show improvement in the on/off resistance ratio (102-107), retention (10 years/85 °C), endurance (∼10 000 cycles), and uniform resistance state distribution.