Evolution and modulation of Ag filament dynamics within memristive devices based on necklace-like Ag@TiO2 nanowire networks

Random nanowire networks (NWNs) are regarded as promising memristive materials for applications in information storage, selectors, and neuromorphic computing. The further insight to understand their resistive switching properties and conduction mechanisms is crucial to realize the full potential of random NWNs. Here, a novel planar memristive device based on necklace-like structure Ag@TiO2 NWN is reported, in which a strategy only using water to tailor the TiO2 shell on Ag core for necklace-like core-shell structure is developed to achieve uniform topology connectivity. With analyzing the influence of compliance current on resistive switching characteristics and further tracing evolution trends of resistance state during the repetitive switching cycles, two distinctive evolution trends of low resistance state failure and high resistance state failure are revealed, which bear resemblance to memory loss and consolidation in biological systems. The underlying conduction mechanisms are related to the modulation of the Ag accumulation dynamics inside the filaments at cross-point junctions within conductive paths of NWNs. An optimizing principle is then proposed to design reproducible and reliable threshold switching devices by tuning the NWN density and electrical stimulation. The optimized threshold switching devices have a high ON/OFF ratio of ~107 with threshold voltage as low as 0.35 V. This work will provide insights into engineering random NWNs for diverse functions by modulating external excitation and optimizing NWN parameters to satisfy specific applications, transforming from neuromorphic systems to threshold switching devices as selectors.

Self-selective ferroelectric memory realized with semimetalic graphene channel

A new concept of read-out method for ferroelectric random-access memory (FeRAM) using a graphene layer as the channel material of bottom-gated field effect transistor structure is demonstrated experimentally. The transconductance of the graphene channel is found to change its sign depending on the direction of spontaneous polarization (SP) in the underlying ferroelectric layer. This indicates that the memory state of FeRAM, specified by the SP direction of the ferroelectric layer, can be sensed unambiguously with transconductance measurements. With the proposed read-out method, it is possible to construct an array of ferroelectric memory cells in the form of a cross-point structure where the transconductance of a crossing cell can be measured selectively without any additional selector. This type of FeRAM can be a plausible solution for fabricating high speed, ultra-low power, long lifetime, and high density 3D stackable non-volatile memory.

Two-terminal vertical thyristor using Schottky contact emitter to improve thermal instability

In a two-terminal-electrode vertical thyristor, the latch-up and latch-down voltages are decreased when the memory operation temperature of the memory cells increases, resulting in a severe reliability issue (i.e., thermal instability). This study fundamentally solves the thermal instability of a vertical-thyristor by achieving a cross-point memory-cell array using a vertical-thyristor with a structure of vertical n++-emitter, p+-base, n+-base, and p++-emitter. The vertical-thyristor using a Schottky contact metal emitter instead of an n++-Si emitter significantly improves the thermal stability between 293 and 373 K. Particularly, the improvement degree of the thermal stability is increased significantly with the use of the Schottky contact metal work function. Because the thermal instability (i.e., degree of latch-up voltage decrement vs. memory operation temperature) decreases with an increase in the Schottky contact metal work function, the dependency of the forward current density between the Schottky contact metal and p+-Si based on the memory operation temperature reduces with increase in the Schottky contact metal work function. Consequently, a higher Schottky contact metal work function produces a higher degree of improvement in the thermal stability, i.e., W (4.50 eV), Ti (4.33 eV), Ta (4.25 eV), and Al (4.12 eV). Further research on the fabrication process of a Schottky contact metal emitter vertical-thyristor is essential for the fabrication of a 3-D cross-point memory-cell.

Fenton Reaction for Enhancing Polishing Rate and Protonated Amine Functional Group Polymer for Inhibiting Corrosion in Ge1Sb4Te5 Film Surface Chemical–Mechanical-Planarization

A Fenton reaction and a corrosion inhibition strategy were designed for enhancing the polishing rate and achieving a corrosion-free Ge1Sb4Te5 film surface during chemical–mechanical planarization (CMP) of three-dimensional (3D) cross-point phase-change random-access memory (PCRAM) cells and 3D cross-point synaptic arrays. The Fenton reaction was conducted with 1,3-propylenediamine tetraacetic acid, ferric ammonium salt (PDTA–Fe) and H2O2. The chemical oxidation degree of GeO2, Sb2O3, and TeO2 evidently increased with the PDTA–Fe concentration in the CMP slurry, such that the polishing rate of the Ge1Sb4Te5 film surface linearly increased with the PDTA–Fe concentration. The addition of a corrosion inhibitor having protonated amine functional groups in the CMP slurry remarkably suppressed the corrosion degree of the Ge1Sb4Te5 film surface after CMP; i.e., the corrosion current of the Ge1Sb4Te5 film surface linearly decreased as the corrosion inhibitor concentration increased. Thus, the proposed Fenton reaction and corrosion inhibitor in the Ge1Sb4Te5 film surface CMP slurry could achieve an almost recess-free Ge1Sb4Te5 film surface of the confined-PCRAM cells, having an aspect ratio of 60-nm-height to 4-nm-diameter after CMP.

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. Furthermore, we demonstrate one-selector-one-resistor behavior in a tandem of two identical Te-based devices, indicating the potential of Te-based device as a universal array building block. These nonconventional phenomena can be understood from a combination of unique electrical-thermal properties in Te. Preliminary device optimization efforts also indicate large and unique design space for Te-based resistive switching devices.

Assessment and Improvement of the Pattern Recognition Performance of Memdiode-Based Cross-Point Arrays with Randomly Distributed Stuck-at-Faults

In this work, the effect of randomly distributed stuck-at faults (SAFs) in memristive cross-point array (CPA)-based single and multi-layer perceptrons (SLPs and MLPs, respectively) intended for pattern recognition tasks is investigated by means of realistic SPICE simulations. The quasi-static memdiode model (QMM) is considered here for the modelling of the synaptic weights implemented with memristors. Following the standard memristive approach, the QMM comprises two coupled equations, one for the electron transport based on the double-diode equation with a single series resistance and a second equation for the internal memory state of the device based on the so-called logistic hysteron. By modifying the state parameter in the current-voltage characteristic, SAFs of different severeness are simulated and the final outcome is analysed. Supervised ex-situ training and two well-known image datasets involving hand-written digits and human faces are employed to assess the inference accuracy of the SLP as a function of the faulty device ratio. The roles played by the memristor’s electrical parameters, line resistance, mapping strategy, image pixelation, and fault type (stuck-at-ON or stuck-at-OFF) on the CPA performance are statistically analysed following a Monte-Carlo approach. Three different re-mapping schemes to help mitigate the effect of the SAFs in the SLP inference phase are thoroughly investigated.

Highly Reliable Memory Operation of High Density Three-Terminal Thyristor Random Access Memory

Three-terminal (3-T) thyristor random-access memory is explored for a next generation high-density nanoscale vertical cross-point array. The effects of standby voltages on the device are thoroughly investigated in terms of gate-cathode voltage (VGC,ST) and anode- cathode voltage (VAC,ST) in the standby state for superior data retention characteristics and low-power operation. The device with the optimized VGC,ST of -0.4 V and VAC,ST of 0.6 V shows the continuous data retention capability without refresh operation with a low standby current of 1.14 pA. In addition, a memory array operation scheme of 3-T TRAM is proposed to address array disturbance issues. The presented array operation scheme can efficiently minimize program, erase and read disturbances on unselected cells by adjusting gate-cathode voltage. The standby voltage turns out to be beneficial to improve retention characteristics: over 10 s. With the proposed memory array operation, 3-T TRAM can provide excellent data retention characteristics and high-density memory configurations comparable with or surpass conventional dynamic random-access memory (DRAM) technology.

SPICE Simulation of RRAM-Based Cross-Point Arrays Using the Dynamic Memdiode Model

We thoroughly investigate the performance of the Dynamic Memdiode Model (DMM) when used for simulating the synaptic weights in large RRAM-based cross-point arrays (CPA) intended for neuromorphic computing. The DMM is in line with Prof. Chua’s memristive devices theory, in which the hysteresis phenomenon in electroformed metal-insulator-metal structures is represented by means of two coupled equations: one equation for the current-voltage characteristic of the device based on an extension of the quantum point-contact (QPC) model for dielectric breakdown and a second equation for the memory state, responsible for keeping track of the previous history of the device. By considering ex-situ training of the CPA aimed at classifying the handwritten characters of the MNIST database, we evaluate the performance of a Write-Verify iterative scheme for setting the crosspoint conductances to their target values. The total programming time, the programming error, and the inference accuracy obtained with such writing scheme are investigated in depth. The role played by parasitic components such as the line resistance as well as some CPA’s particular features like the dynamical range of the memdiodes are discussed. The interrelationship between the frequency and amplitude values of the write pulses is explored in detail. In addition, the effect of the resistance shift for the case of a CPA programmed with no errors is studied for a variety of input signals, providing a design guideline for selecting the appropriate pulse’s amplitude and frequency.