Quantum Conductance in Memristive Devices: Fundamentals, Developments, and Applications

Solid polymer electrolyte-based atomic switches: from materials to mechanisms and applications

As miniaturization of semiconductor memory devices is reaching its physical and technological limits, there is a demand for memory technologies that operate on new principles. Atomic switches are nanoionic devices that show repeatable resistive switching between high-resistance and low-resistance states under bias voltage applications, based on the transport of metal ions and redox reactions in solids. Their essential structure consists of an ion conductor sandwiched between electrochemically active and inert electrodes. This review focuses on the resistive switching mechanism of atomic switches that utilize a solid polymer electrolyte (SPE) as the ion conductor. Owing to the superior properties of polymer materials such as mechanical flexibility, compatibility with various substrates, and low fabrication costs, SPE-based atomic switches are a promising candidate for the next-generation of volatile and nonvolatile memories. Herein, we describe their operating mechanisms and key factors for controlling the device performance with different polymer matrices. In particular, the effects of moisture absorption in the polymer matrix on the resistive switching behavior are addressed in detail. As potential applications, atomic switches with inkjet-printed SPE and quantum conductance behavior are described. SPE-based atomic switches also have great potential in use for neuromorphic devices. The development of these devices will be enhanced using nanoarchitectonics concepts, which integrate functional materials and devices.

Neuromorphic Nanoionics for Human-Machine Interaction: From Materials to Applications

Human-machine interaction (HMI) technology has undergone significant advancements in recent years, enabling seamless communication between humans and machines. Its expansion has extended into various emerging domains, including human healthcare, machine perception, and biointerfaces, thereby magnifying the demand for advanced intelligent technologies. Neuromorphic computing, a paradigm rooted in nanoionic devices that emulate the operations and architecture of the human brain, has emerged as a powerful tool for highly efficient information processing. This paper delivers a comprehensive review of recent developments in nanoionic device-based neuromorphic computing technologies and their pivotal role in shaping the next-generation of HMI. Through a detailed examination of fundamental mechanisms and behaviors, the paper explores the ability of nanoionic memristors and ion-gated transistors to emulate the intricate functions of neurons and synapses. Crucial performance metrics, such as reliability, energy efficiency, flexibility, and biocompatibility, are rigorously evaluated. Potential applications, challenges, and opportunities of using the neuromorphic computing technologies in emerging HMI technologies, are discussed and outlooked, shedding light on the fusion of humans with machines.

Quantum Conductance in Vertical Hexagonal Boron Nitride Memristors with Graphene-Edge Contacts

Two-dimensional materials (2DMs) have gained significant interest for resistive-switching memory toward neuromorphic and in-memory computing (IMC). To achieve atomic-level miniaturization, we introduce vertical hexagonal boron nitride (h-BN) memristors with graphene edge contacts. In addition to enabling three-dimensional (3D) integration (i.e., vertical stacking) for ultimate scalability, the proposed structure delivers ultralow power by isolating single conductive nanofilaments (CNFs) in ultrasmall active areas with negligible leakage thanks to atomically thin (∼0.3 nm) graphene edge contacts. Moreover, it facilitates studying fundamental resistive-switching behavior of single CNFs in CVD-grown 2DMs that was previously unattainable with planar devices. This way, we studied their programming characteristics and observed a consistent single quantum step in conductance attributed to unique atomically constrained nanofilament behavior in CVD-grown 2DMs. This resistive-switching property was previously suggested for h-BN memristors and linked to potential improvements in stability (robustness of CNFs), and now we show experimental evidence including superior retention of quantized conductance.

Electrochemical rewiring through quantum conductance effects in single metallic memristive nanowires

Memristive devices have been demonstrated to exhibit quantum conductance effects at room temperature. In these devices, a detailed understanding of the relationship between electrochemical processes and ionic dynamic underlying the formation of atomic-sized conductive filaments and corresponding electronic transport properties in the quantum regime still represents a challenge. In this work, we report on quantum conductance effects in single memristive Ag nanowires (NWs) through a combined experimental and simulation approach that combines advanced classical molecular dynamics (MD) algorithms and quantum transport simulations (DFT). This approach provides new insights on quantum conductance effects in memristive devices by unravelling the intrinsic relationship between electronic transport and atomic dynamic reconfiguration of the nanofilment, by shedding light on deviations from integer multiples of the fundamental quantum of conductance depending on peculiar dynamic trajectories of nanofilament reconfiguration and on conductance fluctuations relying on atomic rearrangement due to thermal fluctuations.

Reliable Memristor Crossbar Array Based on 2D Layered Nickel Phosphorus Trisulfide for Energy-Efficient Neuromorphic Hardware

Designing reliable and energy-efficient memristors for artificial synaptic arrays in neuromorphic computing beyond von Neumann architecture remains a challenge. Here, memristors based on emerging layered nickel phosphorus trisulfide (NiPS3 ) are reported that exhibit several favorable characteristics, including uniform bipolar nonvolatile switching with small operating voltage (<1 V), fast switching speed (< 20 ns), high On/Off ratio (>102 ), and the ability to achieve programmable multilevel resistance states. Through direct experimental evidence using transmission electron microscopy and energy dispersive X-ray spectroscopy, it is revealed that the resistive switching mechanism in the Ti/NiPS3 /Au device is related to the formation and dissolution of Ti conductive filaments. Intriguingly, further investigation into the microstructural and chemical properties of NiPS3 suggests that the penetration of Ti ions is accompanied by the drift of phosphorus-sulfur ions, leading to induced P/S vacancies that facilitate the formation of conductive filaments. Furthermore, it is demonstrated that the memristor, when operating in quasi-reset mode, effectively emulates long-term synaptic weight plasticity. By utilizing a crossbar array, multipattern memorization and multiply-and-accumulate (MAC) operations are successfully implemented. Moreover, owing to the highly linear and symmetric multiple conductance states, a high pattern recognition accuracy of ≈96.4% is demonstrated in artificial neural network simulation for neuromorphic systems.

Magnetic-ferroelectric synergic control of multilevel conducting states in van der Waals multiferroic tunnel junctions towards in-memory computing

van der Waals (vdW) multiferroic tunnel junctions (MFTJs) based on two-dimensional materials have gained significant interest due to their potential applications in next-generation data storage and in-memory computing devices. In this study, we construct vdW MFTJs by employing monolayer Mn2Se3 as the spin-filter tunnel barrier, TiTe2 as the electrodes and In2S3 as the tunnel barrier to investigate the spin transport properties based on first-principles quantum transport calculations. It is highlighted that apparent tunneling magnetoresistance (TMR) and tunneling electroresistance (TER) effects with a maximum TMR ratio of 6237% and TER ratio of 1771% can be realized by using bilayer In2S3 as the tunnel barrier under finite bias. Furthermore, the physical origin of the distinguished TMR and TER effects is unraveled from the k||-resolved transmission spectra and spin-dependent projected local density of states analysis. Interestingly, four distinguishable conductance states reveal the implementation of four-state nonvolatile data storage using one MFTJ unit. More importantly, in-memory logic computing and multilevel data storage can be achieved at the same time by magnetic switching and electrical control, respectively. These results shed light on vdW MFTJs in the applications of in-memory computing as well as multilevel data storage devices.

Revealing the quantum nature of the voltage-induced conductance changes in oxygen engineered yttrium oxide-based RRAM devices

In this work, the quasi-analog to discrete transition occurring in the current-voltage characteristic of oxygen engineered yttrium oxide-based resistive random-access memory (RRAM) devices is investigated in detail. In particular, the focus of our research is not on the absolute conductance values of this characteristic but on the magnitude of its conductance changes occurring during the reset process of the device. It is found that the detected changes correspond to conductance values predominantly of the order of the quantum unit of conductance G0 = 2e2/h, where e is the electron charge and h the Planck constant. This feature is observed even at conductance levels far above G0, i.e. where electron transport is seemingly diffusive. It is also observed that such behavior is reproducible across devices comprising yttrium oxide layers with different oxygen concentrations and measured under different voltage sweep rates. While the oxygen deficiency affects the total number of quantized conductance states, the magnitude of the changes in conductance, close to 1 G0, is invariant to the oxygen content of the functional layer.

Spike rate dependent synaptic characteristics in lamellar, multilayered alpha-MoO3 based two-terminal devices - efficient way to control the synaptic amplification

Brain-inspired computing systems require a rich variety of neuromorphic devices using multi-functional materials operating at room temperature. Artificial synapses which can be operated using optical and electrical stimuli are in high demand. In this regard, layered materials have attracted a lot of attention due to their tunable energy gap and exotic properties. In the current study, we report the growth of layered MoO3 using the chemical vapor deposition (CVD) technique. MoO3 has an energy gap of 3.22 eV and grows with a large aspect ratio, as seen through optical and scanning electron microscopy. We used transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy for complete characterisation. The two-terminal devices using platinum (Pt/MoO3/Pt) exhibit superior memory with the high-resistance state (HRS) and low-resistance state (LRS) differing by a large resistance (∼MΩ). The devices also show excellent synaptic characteristics. Both optical and electrical pulses can be utilised to stimulate the synapse. Consistent learning (potentiation) and forgetting (depression) curves are measured. Transition from long term depression to long term potentiation can be achieved using the spike frequency dependent pulsing scheme. We have found that the amplification of postsynaptic current can be tuned using such frequency dependent spikes. This will help us to design neuromorphic devices with the required synaptic amplification.

Coherent Phonon Manipulation via Electron-Phonon Interaction for Facilitated Relaxation of Metastable Centers in ZnO

Methods that allow versatile manipulation of metastable centers in semiconductors are highly important owing to their potential for quantum information processing and computations. In this study, we demonstrate that the electron-phonon interaction enables phonon participation to promote relaxation of metastable centers in ZnO, which is known for its persistent photoconductivity (PPC) effect. Experimentally, we show that continuous infrared (IR) radiation (1064 nm, ∼30 mW/cm2) promotes longitudinal optical phonons via the Fröhlich interaction and increases the PPC relaxation rate by ∼4 folds. More importantly, we discover that coherent phonons activated by an ultrashort pulse IR laser of the same power increased the relaxation rate by ∼1200-fold, as confirmed by ultrafast transient spectroscopy to be correlated to the excitation of coherent acoustic phonons via the inverse piezoelectric effect. We expect this study to provide valuable guidance for the development of novel quantum and photoactive devices.

Single-Gate In-Transistor Readout of Current Superposition and Collapse Utilizing Quantum Tunneling and Ferroelectric Switching

In nanostructure assemblies, the superposition of current paths forms microscopic electric circuits, and different circuit networks produce varying results, particularly when utilized as transistor channels for computing applications. However, the intricate nature of assembly networks and the winding paths of commensurate currents hinder standard circuit modeling. Inspired by the quantum collapse of superposition states for information decoding in quantum circuits, the implementation of analogous current path collapse to facilitate the detection of microscopic circuits by modifying their network topology is explored. Here, the superposition and collapse of current paths in gate-all-around polysilicon nanosheet arrays are demonstrated to enrich the computational resources within transistors by engineering the channel length and quantity. Switching the ferroelectric polarization of Hf0.5 Zr0.5 O2 gate dielectric, which drives these transistors out-of-equilibrium, decodes the output polymorphism through circuit topological modifications. Furthermore, a protocol for the single-electron readout of ferroelectric polarization is presented with tailoring the channel coherence. The introduction of lateral path superposition results into intriguing metal-to-insulator transitions due to transient behavior of ferroelectric switching. This ability to adjust the current networks within transistors and their interaction with ferroelectric polarization in polycrystalline nanostructures lays the groundwork for generating diverse current characteristics as potential physical databases for optimization-based computing.

Resistive switching and role of interfaces in memristive devices based on amorphous NbOx grown by anodic oxidation

Memristive devices based on the resistive switching mechanism are continuously attracting attention in the framework of neuromorphic computing and next-generation memory devices. Here, we report on a comprehensive analysis of the resistive switching properties of amorphous NbO_x grown by anodic oxidation. Besides a detailed chemical, structural and morphological analysis of the involved materials and interfaces, the mechanism of switching in Nb/NbO_x/Au resistive switching cells is discussed by investigating the role of metal-metal oxide interfaces in regulating electronic and ionic transport mechanisms. The resistive switching was found to be related to the formation/rupture of conductive nanofilaments in the NbO_x layer under the action of an applied electric field, facilitated by the presence of an oxygen scavenger layer at the Nb/NbO_x interface. Electrical characterization including device-to-device variability revealed an endurance >10³ full-sweep cycles, retention >10⁴ s, and multilevel capabilities. Furthermore, the observation of quantized conductance supports the physical mechanism of switching based on the formation of atomic-scale conductive filaments. Besides providing new insights into the switching properties of NbO_x, this work also highlights the perspective of anodic oxidation as a promising method for the realization of resistive switching cells.

Molecular nanoarchitectonics: unification of nanotechnology and molecular/materials science

The development of nanotechnology has provided an opportunity to integrate a wide range of phenomena and disciplines from the atomic scale, the molecular scale, and the nanoscale into materials. Nanoarchitectonics as a post-nanotechnology concept is a methodology for developing functional material systems using units such as atoms, molecules, and nanomaterials. Especially, molecular nanoarchitectonics has been strongly promoted recently by incorporating nanotechnological methods into organic synthesis. Examples of research that have attracted attention include the direct observation of organic synthesis processes at the molecular level with high resolution, and the control of organic syntheses with probe microscope tips. These can also be considered as starting points for nanoarchitectonics. In this review, these examples of molecular nanoarchitectonics are introduced, and future prospects of nanoarchitectonics are discussed. The fusion of basic science and the application of practical functional materials will complete materials chemistry for everything.

Thermal Characterization of Conductive Filaments in Unipolar Resistive Memories

A methodology to estimate the device temperature in resistive random access memories (RRAMs) is presented. Unipolar devices, which are known to be highly influenced by thermal effects in their resistive switching operation, are employed to develop the technique. A 3D RRAM simulator is used to fit experimental data and obtain the maximum and average temperatures of the conductive filaments (CFs) that are responsible for the switching behavior. It is found that the experimental CFs temperature corresponds to the maximum simulated temperatures obtained at the narrowest sections of the CFs. These temperature values can be used to improve compact models for circuit simulation purposes.

Transfer-free graphene passivation of sub 100 nm thin Pt and Pt–Cu electrodes for memristive devices

Memristive switches are among the most promising building blocks for future neuromorphic computing. These devices are based on a complex interplay of redox reactions on the nanoscale. Nanoionic phenomena enable non-linear and low-power resistance transition in ultra-short programming times. However, when not controlled, the same electrochemical reactions can result in device degradation and instability over time. Two-dimensional barriers have been suggested to precisely manipulate the nanoionic processes. But fabrication-friendly integration of these materials in memristive devices is challenging.Here we report on a novel process for graphene passivation of thin platinum and platinum/copper electrodes. We also studied the level of defects of graphene after deposition of selected oxides that are relevant for memristive switching.

Experimental and Modeling Study of Metal-Insulator Interfaces to Control the Electronic Transport in Single Nanowire Memristive Devices

Memristive devices relying on redox-based resistive switching mechanisms represent promising candidates for the development of novel computing paradigms beyond von Neumann architecture. Recent advancements in understanding physicochemical phenomena underlying resistive switching have shed new light on the importance of an appropriate selection of material properties required to optimize the performance of devices. However, despite great attention has been devoted to unveiling the role of doping concentration, impurity type, adsorbed moisture, and catalytic activity at the interfaces, specific studies concerning the effect of the counter electrode in regulating the electronic flow in memristive cells are scarce. In this work, the influence of the metal-insulator Schottky interfaces in electrochemical metallization memory (ECM) memristive cell model systems based on single-crystalline ZnO nanowires (NWs) is investigated following a combined experimental and modeling approach. By comparing and simulating the electrical characteristics of single NW devices with different contact configurations and by considering Ag and Pt electrodes as representative of electrochemically active and inert electrodes, respectively, we highlight the importance of an appropriate choice of electrode materials by taking into account the Schottky barrier height and interface chemistry at the metal-insulator interfaces. In particular, we show that a clever choice of metal-insulator interfaces allows to reshape the hysteretic conduction characteristics of the device and to increase the device performance by tuning its resistance window. These results obtained from single NW-based devices provide new insights into the selection criteria for materials and interfaces in connection with the design of advanced ECM cells.

Multi-level Cells and Quantized Conductance Characteristics of Al2O3-Based RRAM Device for Neuromorphic System

Recently, various resistance-based memory devices are being studied to replace charge-based memory devices to satisfy high-performance memory requirements. Resistance random access memory (RRAM) shows superior performances such as fast switching speed, structural scalability, and long retention. This work presented the different filament control by the DC voltages and verified its characteristics as a synaptic device by pulse measurement. Firstly, two current-voltage (I-V) curves are characterized by controlling a range of DC voltages. The retention and endurance for each different I-V curve were measured to prove the reliability of the RRAM device. The detailed voltage manipulation confirmed the characteristics of multi-level cell (MLC) and conductance quantization. Lastly, synaptic functions such as potentiation and depression, paired-pulse depression, excitatory post-synaptic current, and spike-timing-dependent plasticity were verified. Collectively, we concluded that Pt/Al₂O₃/TaN is appropriate for the neuromorphic device.