Reservoir computing with a random memristor crossbar array.

Physical implementations of reservoir computing (RC) based on the emerging memristors have become promising candidates of unconventional computing paradigms. Traditionally, sequential approaches by time-multiplexing volatile memristors have been prevalent because of their low hardware overhead. However, they suffer from the problem of speed degradation and fall short of capturing the spatial relationship between the time-domain inputs.

Generative complex networks within a dynamic memristor with intrinsic variability.

Artificial neural networks (ANNs) have gained considerable momentum in the past decade. Although at first the main task of the ANN paradigm was to tune the connection weights in fixed-architecture networks, there has recently been growing interest in evolving network architectures toward the goal of creating artificial general intelligence. Lagging behind this trend, current ANN hardware struggles for a balance between flexibility and efficiency but cannot achieve both.

LiNbO dynamic memristors for reservoir computing.

Information in conventional digital computing platforms is encoded in the steady states of transistors and processed in a quasi-static way. Memristors are a class of emerging devices that naturally embody dynamics through their internal electrophyiscal processes, enabling nonconventional computing paradigms with enhanced capability and energy efficiency, such as reservoir computing. Here, we report on a dynamic memristor based on LiNbO.

A complementary resistive switching neuron.

The complementary resistive switching (CRS) memristor has originally been proposed for use as the storage element or artificial synapse in large-scale crossbar array with the capability of solving the sneak path problem, but its usage has mainly been hampered by the inherent destructiveness of the read operation (switching '1' state to 'ON' or '0' state). Taking a different perspective on this 'undesired' property, we here report on the inherent behavioral similarity between the CRS memristor and a leaky integrate-and-fire (LIF) neuron which is another basic neural computing element, in addition to synapse. In particular, the mechanism behind the undesired read destructiveness for storage element and artificial synapse can be exploited to naturally realize the LIF and the ensuing spontaneous repolarization processes, followed by a refractory period.

Twist-angle-controlled neutral exciton annihilation in WS homostructures.

Exciton-exciton annihilation (EEA), as typical nonradiative recombination, plays an unpopular role in semiconductors. The nonradiative process significantly reduces the quantum yield of photoluminescence, which substantially inhibits the maximum efficiency of optoelectronic devices. Recently, laser irradiation, introducing defects and applying strain have become effective means to restrain EEA in two-dimensional (2D) transition metal dichalcogenides (TMDCs).

A new opportunity for the emerging tellurium semiconductor: making resistive switching devices.

The development of the resistive switching cross-point array as the next-generation platform for high-density storage, in-memory computing and neuromorphic computing heavily relies on the improvement of the two component devices, volatile selector and nonvolatile memory, which have distinct operating current requirements. The perennial current-volatility dilemma that has been widely faced in various device implementations remains a major bottleneck. Here, we show that the device based on electrochemically active, low-thermal conductivity and low-melting temperature semiconducting tellurium filament can solve this dilemma, being able to function as either selector or memory in respective desired current ranges.

Grain-Boundary Engineering of Monolayer MoS for Energy-Efficient Lateral Synaptic Devices.

Synaptic devices based on 2D-layered materials have emerged as high-efficiency electronic synapses and neurons for neuromorphic computing. Lateral 2D synaptic devices have the advantages of multiple functionalities by responding to diverse stimuli, but they consume large amounts of energy, far more than the human brain. Moreover, current lateral devices employ several mechanisms based on conductive filaments and grain boundaries (GBs), but their formation is random and difficult to control, also hindering their practical applications.

MOF-Derived 2D/3D Hierarchical N-Doped Graphene as Support for Advanced Pt Utilization in Ethanol Fuel Cell.

Development of bifunctional catalysts with low platinum (Pt) content for the ethanol oxidation reaction (EOR) and the oxygen reduction reaction (ORR) is highly desirable, yet challenging. Herein, we present structural engineering of a series of two-dimensional/three-dimensional (2D/3D) hierarchical N-doped graphene-supported nanosized PtCo alloys and Co clusters (PtCo@N-GNSs) via a hydrolysis-pyrolysis route. For the ORR, the optimal PtCo@N-GNS exhibits a high mass activity of 3.

Ultrahigh drive current and large selectivity in GeS selector.

Selector devices are indispensable components of large-scale nonvolatile memory and neuromorphic array systems. Besides the conventional silicon transistor, two-terminal ovonic threshold switching device with much higher scalability is currently the most industrially favored selector technology. However, current ovonic threshold switching devices rely heavily on intricate control of material stoichiometry and generally suffer from toxic and complex dopants.

Semiconducting few-layer PdSe and PdSe: native point defects and contacts with native metallic PdSe.

PdSe2 is a unique layered two-dimensional (2D) material with pentagonal structural motif and anisotropic properties. In addition, its strong interlayer interaction leads to new 2D form of the exfoliated monolayer, that is, Pd2Se3. Despite the increasing interest in these emerging 2D materials, the landscape of the native point defects, as a fundamental materials property, has not been revealed.

Perovskite hetero-anionic-sublattice interfaces for optoelectronics and nonconventional electronics.

The perovskite structure provides a versatile framework for functional materials and their high-quality heteroepitaxial interfaces. Perovskite halides (PH) have attracted intense interest for their application in optoelectronics. Oxides are another major class of perovskites that are widely used in fuel cells, nonconventional electronics and electrochemistry.

A New Opportunity for 2D van der Waals Heterostructures: Making Steep-Slope Transistors.

The use of a foreign metallic cold source (CS) has recently been proposed as a promising approach toward the steep-slope field-effect-transistor (FET). In addition to the selection of source material with desired density of states-energy relation (D(E)), engineering the source:channel interface for gate-tunable channel-barrier is crucial to CS-FETs. However, conventional metal:semiconductor (MS) interfaces generally suffer from strong Fermi-level pinning due to the inevitable chemical disorder and defect-induced gap states, precluding the gate tunability of the barriers.

Nanoporous Al-Ni-Co-Ir-Mo High-Entropy Alloy for Record-High Water Splitting Activity in Acidic Environments.

Ir-based binary and ternary alloys are effective catalysts for the electrochemical oxygen evolution reaction (OER) in acidic solutions. Nevertheless, decreasing the Ir content to less than 50 at% while maintaining or even enhancing the overall electrocatalytic activity and durability remains a grand challenge. Herein, by dealloying predesigned Al-based precursor alloys, it is possible to controllably incorporate Ir with another four metal elements into one single nanostructured phase with merely ≈20 at% Ir.

Electronic Structures of GeSbTe/CoFeX (X: Al, Si) Interfaces for Phase Change Spintronics.

Phase change materials (PCMs), such as GeSbTe, are highly attractive in modern electronics and photonics. However, their spintronic applications remain largely unexplored. Here, we propose a tentative modality of phase change spintronic devices based on the ferromagnet/PCM/ferromagnet structure.

Towards artificial general intelligence with hybrid Tianjic chip architecture.

There are two general approaches to developing artificial general intelligence (AGI): computer-science-oriented and neuroscience-oriented. Because of the fundamental differences in their formulations and coding schemes, these two approaches rely on distinct and incompatible platforms, retarding the development of AGI. A general platform that could support the prevailing computer-science-based artificial neural networks as well as neuroscience-inspired models and algorithms is highly desirable.

Self-Doping Memristors with Equivalently Synaptic Ion Dynamics for Neuromorphic Computing.

The accumulation and extrusion of Ca ions in the pre- and post-synaptic terminals play crucial roles in initiating short- and long-term plasticity (STP and LTP) in biological synapses, respectively. Mimicking these synaptic behaviors by electronic devices represents a vital step toward realization of neuromorphic computing. However, the majority of reported synaptic devices usually focus on the emulation of qualitatively synaptic behaviors; devices that can truly emulate the physical behavior of the synaptic Ca ion dynamics in STP and LTP are rarely reported.

Enhanced Sulfur Transformation by Multifunctional FeS/FeS/S Composites for High-Volumetric Capacity Cathodes in Lithium-Sulfur Batteries.

Lithium-sulfur batteries are currently being explored as promising advanced energy storage systems due to the high theoretical specific capacity of sulfur. However, achieving a scalable synthesis for the sulfur electrode material whilst maintaining a high volumetric energy density remains a serious challenge. Here, a continuous ball-milling route is devised for synthesizing multifunctional FeS/FeS/S composites for use as high tap density electrodes.

Metal and Nonmetal Codoped 3D Nanoporous Graphene for Efficient Bifunctional Electrocatalysis and Rechargeable Zn-Air Batteries.

Developing bifunctional electrocatalysts with high activities and long durability for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is crucial toward the practical implementation of rechargeable metal-air batteries. Here, a 3D nanoporous graphene (np-graphene) doped with both N and Ni single atoms/clusters is reported. The predoping of N by chemical vapor deposition (CVD) dramatically increases the Ni doping amount and stability.

Materials Selection and Mechanism of Non-linear Conduction in Chalcogenide Selector Devices.

The electronic structure and conduction mechanism of chalcogenide-based Ovonic threshold switches (OTS) used as selectors in cross-point memory arrays is derived from density functional calculations and quasi-Fermi level models. The switching mechanism in OTS is primarily electronic. This uses a specific electronic structure, with a wide tail of localized states below the conduction band edge.

Truly Concomitant and Independently Expressed Short- and Long-Term Plasticity in a Bi O Se-Based Three-Terminal Memristor.

Concomitance of diverse synaptic plasticity across different timescales produces complex cognitive processes. To achieve comparable cognitive complexity in memristive neuromorphic systems, devices that are capable of emulating short-term (STP) and long-term plasticity (LTP) concomitantly are essential. In existing memristors, however, STP and LTP can only be induced selectively because of the inability to be decoupled using different loci and mechanisms.

Highly Compact Artificial Memristive Neuron with Low Energy Consumption.

Neuromorphic systems aim to implement large-scale artificial neural network on hardware to ultimately realize human-level intelligence. The recent development of nonsilicon nanodevices has opened the huge potential of full memristive neural networks (FMNN), consisting of memristive neurons and synapses, for neuromorphic applications. Unlike the widely reported memristive synapses, the development of artificial neurons on memristive devices has less progress.

Electrochemical metallization cell with anion supplying active electrode.

Electrochemical metallization (ECM) memories are among the various emerging non-volatile memory technologies, contending to replace DRAM and Flash and enabling novel neuromorphic computing applications. Typically, the operation of ECM cell is based on the electrochemical redox reactions of the cation supplying active electrode (e.g.

Electrochemical metallization cell with solid phase tunable GeSbTe electrolyte.

Electrochemical metallization (ECM) cell kinetics are strongly determined by the electrolyte and can hardly be altered after the cell has been fabricated. Solid-state property tunable electrolytes in response to external stimuli are therefore desirable to introduce additional operational degree of freedom to the ECM cells, enabling novel applications such as multistate memory and reconfigurable computation. In this work, we use GeSbTe(GST) as the electrolyte material whose solid state is switched from the amorphous(a) to the crystalline(c) phase thermally.

Native point defects of semiconducting layered BiOSe.

BiOSe is an emerging semiconducting, air-stable layered material (Nat. Nanotechnol. 2017, 12, 530; Nano Lett.