Quantized Conductance States Research Articles

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.

Two-dimensional topological insulators: past, present and future

Two-dimensional (2D) topological insulators (TIs) are special quantum conductors that possess an insulating bulk but metallic edge with quantized charge and spin conductance protected by electron band topology. The concept of topology and TI has not only renewed our fundamental understanding of electronic properties of solid materials, but also opened an exciting avenue towards potential applications of topological quantum devices with minimized heat dissipation and robustness against disorder. In this video article, I will first introduce and review the concept of TIs within the context of transport properties of solid-state materials. I will then use two examples, the organic 2D TIs and the surface-based 2D topological states, to recap the rapid theoretical and experimental developments made in this emerging field. The existence of quantized edge conductance and topological edge states of 2D TIs has been so far confirmed experimentally in several systems, such as semiconductor quantum wells, 2D transition metal dichalcogenides, metallic overlayer of bismuth on a semiconductor surface. However, discovery of high-temperature 2D TIs and construction of functional TI-based quantum devices remain largely elusive. At the end of this video article, I will offer briefly my personal perspective and possible future directions in low-dimensional topological materials.

Quantized synaptic characteristics in HfO2-nanocrystal based resistive switching memory

We demonstrate the reliable resistive switching performance of nanocrystalline-HfO2 inside amorphous-HfOx in TaN/nc-HfO2/ITO memristor structure. Transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) were utilized to confirm the presence of nc-HfO2 and non-stoichiometric HfOx in the switching layer. In presence of nc-HfO2, quantized conductance was controlled by the narrowing of conductive filaments in an atomic scale applying a very slow voltage sweep. Conductance change under DC voltage shows the quantized conductance states with integer and half-integer multiples of G0 (77.5 μS). Enhanced resistive switching performances with multilevel resistance states behavior were investigated under different current compliance and RESET stop voltages. Short-term plasticity and long-term potentiation, pulse number, and spike rate-dependent plasticity by controlling the magnitude and duration of the input stimulus play a critical role in modulating the post-synaptic conductivity. The combination of nc-HfO2 and amorphous-HfOx in the memristor structure provide promising scope for neuromorphic system applications.

Improved Resistive Switching with Low-Power Synaptic Behaviors of ZnO/Al2O3 Bilayer Structure.

In this work, the resistive switching behavior of bilayer ZnO/Al2O3-based resistive-switching random access memory (RRAM) devices is demonstrated. The polycrystalline nature of the ZnO layer confirms the grain boundary, which helps easy oxygen ion diffusion. Multilevel resistance states were modulated under DC bias by varying the current compliance from 0.1 mA to 0.8 mA, the SET operations where the low resistance state of the memristor device was reduced from 25 kΩ to 2.4 kΩ. The presence of Al2O3 acts as a redox layer and facilitates oxygen vacancy exchange that demonstrates stable gradual conductance change. Stepwise disruption of conductive filaments was monitored depending on the slow DC voltage sweep rate. This is attributed to the atomic scale modulation of oxygen vacancies with four distinct reproducible quantized conductance states, which shows multilevel data storage capability. Moreover, several crucial synaptic properties such as potentiation/depression under identical presynaptic pulses and the spike-rate-dependent plasticity were implemented on ITO/ZnO/Al2O3/TaN memristor. The postsynaptic current change was monitored defining the long-term potentiation by increasing the presynaptic stimulus frequency from 5 Hz to 100 Hz. Moreover, the repetitive pulse voltage stimulation transformed the short-term plasticity to long-term plasticity during spike-number-dependent plasticity.

Synaptic Plasticity and Quantized Conductance States in TiN-Nanoparticles-Based Memristor for Neuromorphic System

Controlled conductive filament formation in the resistive random access memory device is an essential requirement for analog resistive switching to develop artificial synapses. In this work, we have studied Au/Ti/HfAlOx/TiN-NP/HfAlOx/ITO RRAM device to demonstrate conductance quantization behavior to achieve the high-density memory application. Stepwise change in conductance under DC and pulse voltage confirms the quantized conductance states with integer and half-integer multiples of G0. Reactive TiN-NPs inside the switching layer helps to form and rupture the atomic scale conductive filaments due to enhancing the local electric field inside. Bipolar resistive switching characteristics at low SET/RESET voltage were obtained with memory window > 10 and stable endurance of 103 cycles. Short-term and long-term plasticities are successfully demonstrated by modulating the pre-spike number, magnitude, and frequency. The quantized conductance behavior with promising synaptic properties obtained in the experiments suggests HfAlOx/TiN-NP/HfAlOx switching layer is suitable for multilevel high-density storage RRAM devices.

Natural Acidic Polysaccharide‐Based Memristors for Transient Electronics: Highly Controllable Quantized Conductance for Integrated Memory and Nonvolatile Logic Applications (Adv. Mater. 52/2021)

Transient Electronics In article number 2104023, Haiyang Xu, Yichun Liu, and co-workers report the development of transient memristors with acidic polysaccharides for green electronics. The ion-confinement capability of the acidic polysaccharides enables atomic manipulation of conductive filaments in the memristors, which can produce highly controllable quantized conductance states. These memristors are promising for integrated memory and computing applications.

Natural Acidic Polysaccharide‐Based Memristors for Transient Electronics: Highly Controllable Quantized Conductance for Integrated Memory and Nonvolatile Logic Applications

AbstractAs a leading candidate for further memory and computing applications, memristors are being developed in an important direction of transient electronics. Herein, wafer‐scale acidic polysaccharide thin films are reported as promising materials for memristors with remarkable transient characteristics. The memristor shows freestanding and lightweight features, and can be fully dissolved in deionized water within 3.5 s. More importantly, the ion‐confinement capability of acidic polysaccharides where the cations can interact with the ionizable acid groups enables atomic manipulation of conductive filament. As a result, (i) a single device can produce 16 highly controllable and independent quantized conductance (QC) states with quasi‐nonvolatile and nonvolatile characteristics and (ii) QC switching can be performed with ultrafast speed (2–5 ns) and low energy consumption (0.6–16 pJ). These remarkable features make the memristor promising for fast, low‐power, and high‐density memory and computing applications. Based on QC switching, the encoding/decoding and nonvolatile basic Boolean logic are designed and implemented. More importantly, “stateful” material implication logic which is promising for future in‐memory computing is demonstrated with QC switching. These results significantly advance acidic polysaccharides to develop nanodevices with quantum effects.

Dynamic Behaviors and Training Effects in TiN/Ti/HfOx/TiN-Nanolayered Memristors with Controllable Quantized Conductance States: Implications for Quantum and Neuromorphic Computing Devices

Controllable quantized conductance states of TiN/Ti/HfO$_x$/TiN memristors are realized with great precision through a pulse-mode reset procedure, assisted with analytical differentiation of the condition of the set procedure, which involves critical monitoring of the measured bias voltage. An intriguing training effect that leads to faster switching of the states is also observed during the operation. Detailed analyses on the low- and high-resistance states under different compliance currents reveal a complete picture of the structural evolution and dynamic behaviors of the conductive filament in the HfO$_x$ layer. This study provides a closer inspection on the quantum-level manipulation of nanoscale atomic configurations in the memristors, which helps to develop essential knowledge about the design and fabrication of the future memristor-based quantum devices and neuromorphic computing devices.

Improving the Recognition Accuracy of Memristive Neural Networks via Homogenized Analog Type Conductance Quantization.

Conductance quantization (QC) phenomena occurring in metal oxide based memristors demonstrate great potential for high-density data storage through multilevel switching, and analog synaptic weight update for effective training of the artificial neural networks. Continuous, linear and symmetrical modulation of the device conductance is a critical issue in QC behavior of memristors. In this contribution, we employ the scanning probe microscope (SPM) assisted electrode engineering strategy to control the ion migration process to construct single conductive filaments in Pt/HfOx/Pt devices. Upon deliberate tuning and evolution of the filament, 32 half integer quantized conductance states in the 16 G0 to 0.5 G0 range with enhanced distribution uniformity was achieved. Simulation results revealed that the numbers of the available QC states and fluctuation of the conductance at each state play an important role in determining the overall performance of the neural networks. The 32-state QC behavior of the hafnium oxide device shows improved recognition accuracy approaching 90% for handwritten digits, based on analog type operation of the multilayer perception (MLP) neural network.

Magnetism modulation and conductance quantization in a gadolinium oxide memristor.

The requests for higher information storage density, greater data processing power, and memory-centric computing capability in the current big data era are motivating global research interests in novel solid-state electronic devices that can unite the electron charge and spin degrees of freedom. Herein, the simultaneous realization of magnetism modulation and conductance quantization in a single gadolinium oxide memristor is reported. A remarkable enhancement of >170% in saturation magnetization at room temperature, accompanied by the emergence of a clear magnetoresistance behavior at low temperature, was obtained after setting the memristor from the initial high resistance state (HRS) into the low resistance state (LRS). By carefully resetting the memristor from the LRS into the HRS, up to 32 quantized conductance states with good repeatability and stability were observed, which could possibly allow achieving 5 bit storage in a single memory cell in the future. Moreover, the resistive switching mechanism of the memristor was thoroughly investigated with the help of temperature-dependent resistance tests and high-resolution transmission electron microscopy examination. This work could provide a powerful approach to design future multi-field modulated, high-performance information devices with integrated data storage, sensing, as well as processing functions.

Controllable and Stable Quantized Conductance States in a Pt/HfOx/ITO Memristor

AbstractQuantum‐level manipulation of atomic configuration offers a excellent platform for the construction of exotic nanostructures that exhibit unusual solid‐state physics and electronic properties. One particular example is the memristor, in which the elaborate evolution of atomic point contact via local ionic processes and consequent stepwise device conductance quantization enable bottom‐up design of in‐memory computing with greatly increased data storage density and more efficient multi‐value logic algorithm. In‐depth understanding on the physics of atomic reconfiguration is achieved through comprehensive consideration of the thermodynamics and kinetics of nanoionics in memristors, based on which a general protocol of constructing atomic point contact structure with desired quantized conductance is established. Through energy‐driven single‐atom level oxygen manipulation in the reset process of a Pt/HfOx/ITO structure, up to 32 consecutive quantized conductance states with an interval of half conductance quantum that can be sustained for over 7000 s and tuned 500 times are demonstrated for the first time, not only allowing the physical implementation of ternary logic‐in‐memory functions, but also providing a universal methodology for building next‐generation quantum electronic devices.

Controlled Construction of Atomic Point Contact with 16 Quantized Conductance States in Oxide Resistive Switching Memory

A resistive switching device with controlled formation and evolution of conductive filament possesses great capability of being miniaturized to atomic scale for the construction of high-density mem...

Polymer Analog Memristive Synapse with Atomic-Scale Conductive Filament for Flexible Neuromorphic Computing System.

With the advent of artificial intelligence (AI), memristors have received significant interest as a synaptic building block for neuromorphic systems, where each synaptic memristor should operate in an analog fashion, exhibiting multilevel accessible conductance states. Here, we demonstrate that the transition of the operation mode in poly(1,3,5-trivinyl-1,3,5-trimethyl cyclotrisiloxane) (pV3D3)-based flexible memristor from conventional binary to synaptic analog switching can be achieved simply by reducing the size of the formed filament. With the quantized conductance states observed in the flexible pV3D3 memristor, analog potentiation and depression characteristics of the memristive synapse are obtained through the growth of atomically thin Cu filament and lateral dissolution of the filament via dominant electric field effect, respectively. The face classification capability of our memristor is evaluated via simulation using an artificial neural network consisting of pV3D3 memristor synapses. These results will encourage the development of soft neuromorphic intelligent systems.

Controlled inter-state switching between quantized conductance states in resistive devices for multilevel memory.

A detailed understanding of quantization conductance (QC), the correlation with resistive switching phenomena and controlled manipulation of quantized states is crucial for realizing atomic-scale multilevel memory elements. Here, we demonstrate highly stable and reproducible quantized conductance states (QC-states) in Al/niobium oxide/Pt resistive switching devices. Three levels of control over the QC-states, required for multilevel quantized state memories, like, switching ON to different quantized states, switching OFF from quantized states, and controlled inter-state switching among one QC state to another has been demonstrated by imposing limiting conditions of stop-voltage and current compliance. The well-defined multiple QC states along with a working principle for switching among various states show promise for implementation of multilevel memory devices.

(Invited) Synaptic Plasticity in a Memristive Device below 500mV

Neuromorphic engineering aims to develop intelligent systems by mimicking the key computational architecture of biological neural networks [1]. Neurons or nerve cells are the functional units of information processing in the brain. They are interconnected with each other via junctions called synapses to form parallel networks; it is estimated that there can be as many as ten thousand synapses per neuron in certain regions of the human brain. The plasticity of the junction conductance based on neuronal activity leads to memory, learning, and adaptation. Thus, the neuron processor together with local synaptic storage makes brain a highly parallel computing system. Human brain consumes only about 20 W, whereas the today's best supercomputers consume millions of Watts. The processing power of the brain is attributed to its parallel architecture and local learning. Implementing a scalable high connectivity network with local adaptive storage is an important step in realizing neuromorphic computing systems. Memristive devices integrated in cross-bar arrays, with neuronal circuitry in periphery, can mimic the architecture of the brain efficiently. Memristive devices show non-volatile conductance modulation which is a function of the current that has passed through it [2]. Such devices exhibit an analog hysteresis in their IV responses and has been suggested for neuromorphic engineering applications. Even though the current state of research suggests that the challenges related to reliability and repeatability have to be overcome, these devices offer significant advantages in terms of scalability and power consumption. We recently demonstrated half-integer quantized conductance in Cu/SiO2/W devices which have switching threshold less than 250mV [3]. The conductance quantization suggests the presence of nano-filaments whose effective radius was estimated to be in the range of 2-6 nm. This corresponds to the total average area involved in resistive switching; it is indeed possible that multiple filaments are active in parallel in the device. A multi-state memory device is essential for compact local storage and learning in neuromorphic engineering. However, the quantized conductance states, which are multiples of 2e2/h (G0), allow currents in the micro-ampere range for read voltages as low as 50 mV, which is large for a high-density memory array. It might be possible to engineer a selector device in series with the RRAM structure which can avoid both the sneak path problem in a cross-bar array structure and at the same time act as a series resistance to lower the read current. Hence, we explored the possibility of utilizing the off-state device conductance of our device to mimic synaptic plasticity, by programming it with waveforms that do not exceed the switching threshold for a sufficiently long time. We chose the waveforms to be approximations of neuronal actions potentials and their amplitudes are chosen to be below device switching threshold. Pre and post-synaptic waveforms were used and their different time shifted versions were applied across the device. In the actual experiment, the W electrode was grounded and the difference of two waveforms was applied to the Cu electrode. When we plotted the normalized device conductance change as a function of the time shifts, the response approximated the biologically observed STDP behavior. The observed behavior might be the result of partial filament formation and metal ion doping of SiO2. Similar gradual conductance change behavior has been observed earlier in oxide based RRAMs [4], which operates at higher voltages than our device. The programming waveform we used has a peak amplitude of 0.5V during the maximum conductance change. The bio-mimetic behavior we demonstrated here from a two terminal, low voltage, CMOS-technology compatible device structure takes us closer to the goal of builind an intelligent system at the energy budget of the human brain. The reduction in programming voltage amplitude can result in significant energy savings in large array implementations which is vital to bio-inspired computing platforms.

Controllable quantized conductance for multilevel data storage applications using conductive bridge random access memory

In this paper, we investigate the quantized conduction behavior of conductive bridge random access memory (CBRAM) with varied materials and ramping rates. We report stable and reproducible quantized conductance states with integer multiples of fundamental conductance obtained by optimizing the voltage ramping rate and the Ti-diffusion barrier (DB) at the Cu/HfO2 interface. Owing to controlled diffusion of Cu ions by the Ti-DB and the optimized ramping rate, through which it was possible to control the time delay of Cu ion reduction, more than seven levels of discrete conductance states were clearly observed. Analytical modeling was performed to determine the rate-limiting step in filament growth based on an electrochemical redox reaction. Our understanding of the fundamental mechanisms of quantized conductance behaviors provide a promising future for the multi-bit CBRAM device.

Highly Reproducible and Regulated Conductance Quantization in a Polymer‐Based Atomic Switch

A detailed understanding of the conductance quantization and resistive switching phenomena in redox‐based memories is crucial for realizing atomic‐scale memory devices and for finding the adequate design principles on which they can be based. Here, the emergence of quantized conductance states and their correlation with resistive switching characteristics in polymer‐based atomic switches are investigated using combinations of current–voltage measurements and first‐principles density functional theory (DFT) simulations. Various conductance states, including integer and half‐integer multiples of a single atomic point contact and fractional conductance variations, are observed in an Ag/polyethylene oxide/Pt device under sweeping of bias voltage. Moreover, highly controllable and reproducible quantized conductance behaviors by tuning the voltage sweep rate and the sweep voltage range, suggesting well‐controlled formation of the atomic point contact, are demonstrated. The device also exhibits longer retention times for higher conductance states. The DFT simulations reveal the transmission eigenstate of geometrically optimized atomic point contact structures and the impact of the atomic configurations and structural stability on the conductance state, which also explains their resistive switching behaviors. The well‐defined, multiple quantized conductance states observed in these polymer‐based atomic switches show promise for the development of new multilevel memory devices.

Quantized conductance coincides with state instability and excess noise in tantalum oxide memristors.

Tantalum oxide memristors can switch continuously from a low-conductance semiconducting to a high-conductance metallic state. At the boundary between these two regimes are quantized conductance states, which indicate the formation of a point contact within the oxide characterized by multistable conductance fluctuations and enlarged electronic noise. Here, we observe diverse conductance-dependent noise spectra, including a transition from 1/f2 (activated transport) to 1/f (flicker noise) as a function of the frequency f, and a large peak in the noise amplitude at the conductance quantum GQ=2e2/h, in contrast to suppressed noise at the conductance quantum observed in other systems. We model the stochastic behaviour near the point contact regime using Molecular Dynamics–Langevin simulations and understand the observed frequency-dependent noise behaviour in terms of thermally activated atomic-scale fluctuations that make and break a quantum conductance channel. These results provide insights into switching mechanisms and guidance to device operating ranges for different applications.

Voltage sweep modulated conductance quantization in oxide nanocomposites

Bipolar resistive switching characteristics and conductance quantization behaviour as a function of voltage sweep have been demonstrated in a nanocomposite based device comprising of SnO2 nanoparticles residing over CeO2 nanorod arrays. The voltage sweep rate has been found to greatly influence the device performance. The stepwise conductance behaviour in the nanocomposite device emerged at a low voltage sweep rate and this behaviour can be attributed to the formation and disruption of atomic scale conducting filaments. In AC pulse mode, the quantized conductance states with integer or half integer multiples of Go were also observed. Furthermore, the impact of varying the SnO2 concentration on the resistive switching performance of the nanocomposite based device was also studied. The present study reveals that the conductance quantization behaviors can be well modulated by controlling the voltage sweep rate and in turn could offer the prospective of multi-level data storage capability.