Exploring the Cutting-Edge Frontiers of Electrochemical Random Access Memories (ECRAMs) for Neuromorphic Computing: Revolutionary Advances in Material-to-Device Engineering.

Advanced materials and device engineering has played a crucial role in improving the performance of electrochemical random access memory (ECRAM) devices. ECRAM technology has been identified as a promising candidate for implementing artificial synapses in neuromorphic computing systems due to its ability to store analog values and its ease of programmability. ECRAM devices consist of an electrolyte and a channel material sandwiched between two electrodes, and the performance of these devices depends on the properties of the materials used. This review provides a comprehensive overview of material engineering strategies to optimize the electrolyte and channel materials' ionic conductivity, stability, and ionic diffusivity to improve the performance and reliability of ECRAM devices. Device engineering and scaling strategies are further discussed to enhance ECRAM performance. Last, perspectives on the current challenges and future directions in developing ECRAM-based artificial synapses in neuromorphic computing systems are provided.

On-Chip Integrated Atomically Thin 2D Material Heater as a Training Accelerator for an Electrochemical Random-Access Memory Synapse for Neuromorphic Computing Application.

An artificial synapse based on oxygen-ion-driven electrochemical random-access memory (O-ECRAM) devices is a promising candidate for building neural networks embodied in neuromorphic hardware. However, achieving commercial-level learning accuracy in O-ECRAM synapses, analog conductance tuning at fast speed, and multibit storage capacity is challenging because of the lack of Joule heating, which restricts O2- ionic transport. Here, we propose the use of an atomically thin heater of monolayer graphene as a low-power heating source for O-ECRAM to increase thermally activated O2- migration within channel-electrolyte layers. Heating from graphene manipulates the electrolyte activation energy to establish and maintain discrete analog states in the O-ECRAM channel. Benefiting from the integrated graphene heater, the O-ECRAM features long retention (>104 s), good stability (switching accuracy <98% for >103 training pulses), multilevel analog states for 6-bit analog weight storage with near-ideal linear switching, and 95% pattern-identification accuracy. The findings demonstrate the usefulness of 2D materials as integrated heating elements in artificial synapse chips to accelerate neuromorphic computation.

Strategies to Improve the Synaptic Characteristics of Oxygen-Based Electrochemical Random-Access Memory Based on Material Parameters Optimization.

Oxygen-based electrochemical random-access memories (O-ECRAMs) are promising synaptic devices for neuromorphic applications because of their near-ideal synaptic characteristics and compatibility with complementary metal-oxide-semiconductor processes. However, the correlation between material parameters and synaptic properties of O-ECRAM devices has not yet been elucidated. Here, we propose the critical design parameters to fabricate an ideal ECRAM device. Based on the experimental data and simulation results, it is revealed that consistent ion supply from the electrolyte and rapid ion diffusion in the channel are critical factors for ideal synaptic characteristics. To optimize these parameters, crystalline WO2.7 exhibiting fast ion diffusivity and ZrO1.7 exhibiting an appropriate ion conduction energy barrier (1.1 eV) are used as a channel and an electrolyte, respectively. As a result, synaptic characteristics with near-ideal weight-update linearity in the nanosiemens conductance range are achieved. Finally, a selector-less O-ECRAM device is integrated into a 2 × 2 array, and high recognition accuracy (94.83%) of the Modified National Institute of Standards and Technology pattern is evaluated.

High polarization and wake-up free ferroelectric characteristics in ultrathin Hf0.5Zr0.5O2devices by control of oxygen-deficient layer.

The formation of an interfacial layer is believed to affect the ferroelectric properties in HfO2based ferroelectric devices. The atomic layer deposited devices continue suffering from a poor bottom interfacial condition, since the formation of bottom interface is severely affected by atomic layer deposition and annealing process. Herein, the formation of bottom interfacial layer was controlled through deposition of different bottom electrodes (BE) in device structure W/HZO/BE. The transmission electron microscopy (TEM) and x-ray photoelectron spectroscopy analyses done on devices W/HZO/W and W/HZO/IrOxsuggest the strong effect of IrOxin controlling bottom interfacial layer formation while W/HZO/W badly suffers from interfacial layer formation. W/HZO/IrOxdevices show high remnant polarization (2Pr) âˆ¼ 53µC cm-2, wake-up free endurance cycling characteristics, low leakage current with demonstration of low annealing temperature requirement as low as 350 °C, valuable for back-end-of-line integration. Further, sub-5 nm HZO thicknesses-based W/HZO/IrOxdevices demonstrate high 2Prand wake-up free ferroelectric characteristics, which can be promising for low power and high-density memory applications. 2.2 nm, 3 nm, and 4 nm HZO based W/HZO/IrOxdevices show 2Prvalues 13.54, 22.4, 38.23µC cm-2at 4 MV cm-1and 19.96, 30.17, 48.34µC cm-2at 5 MV cm-1, respectively, with demonstration of wake-up free ferroelectric characteristics.

Ionic Sieving Through One-Atom-Thick 2D Material Enables Analog Nonvolatile Memory for Neuromorphic Computing.

The first report on ion transport through atomic sieves of atomically thin 2D material is provided to solve critical limitations of electrochemical random-access memory (ECRAM) devices. Conventional ECRAMs have random and localized ion migration paths; as a result, the analog switching efficiency is inadequate to perform in-memory logic operations. Herein ion transport path scaled down to the one-atom-thick (≈0.33 nm) hexagonal boron nitride (hBN), and the ionic transport area is confined to a small pore (≈0.3 nm2 ) at the single-hexagonal ring. One-atom-thick hBN has ion-permeable pores at the center of each hexagonal ring due to weakened electron cloud and highly polarized B-N bond. The experimental evidence indicates that the activation energy barrier for H+ ion transport through single-layer hBN is ≈0.51 eV. Benefiting from the controlled ionic sieving through single-layer hBN, the ECRAMs exhibit superior nonvolatile analog switching with good memory retention and high endurance. The proposed approach enables atomically thin 2D material as an ion transport layer to regulate the switching of various ECRAM devices for artificial synaptic electronics.

Surface Diffusion and Epitaxial Self-Planarization for Wafer-Scale Single-Grain Metal Chalcogenide Thin Films.

Although wafer-scale single-grain thin films of 2D metal chalcogenides (MCs) have been extensively sought after during the last decade, the grain size of the MC thin films is still limited in the sub-millimeter scale. A general strategy of synthesizing wafer-scale single-grain MC thin films by using commercial wafers (Si, Ge, GaAs) both as metal source and epitaxial collimator is presented. A new mechanism of single-grain thin-film formation, surface diffusion, and epitaxial self-planarization is proposed, where chalcogen elements migrate preferentially along substrate surface and the epitaxial crystal domains flow to form an atomically smooth thin film. Through synchrotron X-ray diffraction and high-resolution scanning transmission electron microscopy, the formation of single-grain Si2 Te3 , GeTe, GeSe, and GaTe thin films on (111) Si, Ge, and (100) GaAs is verified. The Si2 Te3 thin film is used to achieve transfer-free fabrication of a high-performance bipolar memristive electrical-switching device.

Single-Atom Quantum-Point Contact Switch Using Atomically Thin Hexagonal Boron Nitride.

The first report of a quantized conductance atomic threshold switch (QCATS) using an atomically-thin hexagonal boron nitride (hBN) layer is provided. This QCATS has applications in memory and logic devices. The QCATS device shows a stable and reproducible conductance quantization state at 1·G0 by forming single-atom point contact through a monoatomic boron defect in an hBN layer. An atomistic switching mechanism in hBN-QCATS is confirmed by in situ visualization of mono-atomic conductive filaments. Atomic defects in hBN are the key factor that affects the switching characteristic. The hBN-QCATS has excellent switching characteristics such as low operation voltage of 0.3 V, low "off" current of 1 pA, fast switching of 50 ns, and high endurance > 107 cycles. The variability of switching characteristics, which are the major problems of switching device, can be solved by reducing the area and thickness of the switching region to form single-atom point contact. The switching layer thickness is scaled down to the single-atom (≈0.33 nm) h-BN layer, and the switching area is limited to single-atom defects. By implementing excellent switching characteristics using single-layer hBN, the possibility of implementing stable and uniform atomic-switching devices for future memory and logic applications is confirmed.

Sodium-based nano-ionic synaptic transistor with improved retention characteristics.

We propose an all-solid-state Na ion-based synaptic transistor (NST) to overcome the low retention problem of the Li ion-based synaptic transistor (LST). Through our analysis, it was found that the retention instability in an ionic synaptic transistor originated from its high ionic diffusivity. As confirmed by cyclic voltammetry analysis, Na ions have a lower ionic diffusivity than Li ions in the WOx layer. The state retention of NST was found to be improved to 20 times that of LST. Furthermore, near-ideal synaptic behaviors, such as linear weight update and linear I-V characteristics, were also obtained by material engineering.

Excellent synaptic behavior of lithium-based nano-ionic transistor based on optimal WO2.7 stoichiometry with high ion diffusivity.

In this study, we introduce a lithium (Li) ion-based three-terminal (3-T) synapse device using WO x as a channel. Our study reveals a key stoichiometry of WO2.7 for excellent synaptic characteristics that is related to Li-ion diffusivity. The open-lattice structure formed by oxygen deficiency promoted Li-ion injection and diffusion. The optimized stoichiometry and improved Li-ion diffusivity were confirmed by x-ray photoelectron spectroscopy analysis and cyclic voltammetry, respectively. Furthermore, the transient conductance change that inevitably occurs in ion-based synaptic transistors was resolved by applying a two-step voltage pulse scheme. As a result, we achieved a symmetric and linear weight-update characteristic with reduced program/erase operation time.

Near ideal synaptic functionalities in Li ion synaptic transistor using Li3POxSex electrolyte with high ionic conductivity.

All solid-state lithium-ion transistors are considered as promising synaptic devices for building artificial neural networks for neuromorphic computing. However, the slow ionic conduction in existing electrolytes hinders the performance of lithium-ion-based synaptic transistors. In this study, we systematically explore the influence of ionic conductivity of electrolytes on the synaptic performance of ionic transistors. Isovalent chalcogenide substitution such as Se in Li3PO4 significantly reduces the activation energy for Li ion migration from 0.35 to 0.253 eV, leading to a fast ionic conduction. This high ionic conductivity allows linear conductance switching in the LiCoO2 channel with several discrete nonvolatile states and good retention for both potentiation and depression steps. Consequently, optimized devices demonstrate the smallest nonlinearity ratio of 0.12 and high on/off ratio of 19. However, Li3PO4 electrolyte (with lower ionic conductivity) shows asymmetric and nonlinear weight-update characteristics. Our findings show that the facilitation of Li ionic conduction in solid-state electrolyte suggests potential application in artificial synapse device development.

Three-Dimensional Heterostructures of MoS2 Nanosheets on Conducting MoO2 as an Efficient Electrocatalyst To Enhance Hydrogen Evolution Reaction.

Molybdenum disulfide (MoS2) is a promising catalyst for hydrogen evolution reaction (HER) because of its unique nature to supply active sites in the reaction. However, the low density of active sites and their poor electrical conductivity have limited the performance of MoS2 in HER. In this work, we synthesized MoS2 nanosheets on three-dimensional (3D) conductive MoO2 via a two-step chemical vapor deposition (CVD) reaction. The 3D MoO2 structure can create structural disorders in MoS2 nanosheets (referred to as 3D MoS2/MoO2), which are responsible for providing the superior HER activity by exposing tremendous active sites of terminal disulfur of S2(-2) (in MoS2) as well as the backbone conductive oxide layer (of MoO2) to facilitate an interfacial charge transport for the proton reduction. In addition, the MoS2 nanosheets could protect the inner MoO2 core from the acidic electrolyte in the HER. The high activity of the as-synthesized 3D MoS2/MoO2 hybrid material in HER is attributed to the small onset overpotential of 142 mV, a largest cathodic current density of 85 mA cm(-2), a low Tafel slope of 35.6 mV dec(-1), and robust electrochemical durability.