The morphology and dimension of the conductive filament formed in a memristive device are strongly influenced by the thickness of its switching medium layer. Aggressive scaling of this active layer thickness is critical toward reducing the operating current, voltage, and energy consumption in filamentary‐type memristors. Previously, the thickness of this filament layer has been limited to above a few nanometers due to processing constraints, making it challenging to further suppress the on‐state current and the switching voltage. Here, the formation of conductive filaments in a material medium with sub‐nanometer thickness formed through the oxidation of atomically thin two‐dimensional boron nitride is studied. The resulting memristive device exhibits sub‐nanometer filamentary switching with sub‐pA operation current and femtojoule per bit energy consumption. Furthermore, by confining the filament to the atomic scale, current switching characteristics are observed that are distinct from that in thicker medium due to the profoundly different atomic kinetics. The filament morphology in such an aggressively scaled memristive device is also theoretically explored. These ultralow energy devices are promising for realizing femtojoule and sub‐femtojoule electronic computation, which can be attractive for applications in a wide range of electronics systems that desire ultralow power operation.
Memristors have attracted increasing attention due to their tremendous potential to accelerate data-centric computing systems. The dynamic reconfiguration of memristive devices in response to external electrical stimuli can provide highly desirable novel functionalities for computing applications when compared with conventional complementary-metal–oxide–semiconductor (CMOS)-based devices. Those most intensively studied and extensively reviewed memristors in the literature so far have been filamentary type memristors, which typically exhibit a relatively large variability from device to device and from switching cycle to cycle. On the other hand, filament-free switching memristors have shown a better uniformity and attractive dynamical properties, which can enable a variety of new computing paradigms but have rarely been reviewed. In this article, a wide range of filament-free switching memristors and their corresponding computing applications are reviewed. Various junction structures, switching properties, and switching principles of filament-free memristors are surveyed and discussed. Furthermore, we introduce recent advances in different computing schemes and their demonstrations based on non-filamentary memristors. This Review aims to present valuable insights and guidelines regarding the key computational primitives and implementations enabled by these filament-free switching memristors.
more » « less- NSF-PAR ID:
- 10480492
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Nano Convergence
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2196-5404
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Interface‐type (IT) resistive switching (RS) memories are promising for next generation memory and computing technologies owing to the filament‐free switching, high on/off ratio, low power consumption, and low spatial variability. Although the switching mechanisms of memristors have been widely studied in filament‐type devices, they are largely unknown in IT memristors. In this work, using the simple Au/Nb:SrTiO3(Nb:STO) as a model Schottky system, it is identified that protons from moisture are key element in determining the RS characteristics in IT memristors. The Au/Nb:STO devices show typical Schottky interface controlled current–voltage (
I –V ) curves with a large on/off ratio under ambient conditions. Surprisingly, in a controlled environment without protons/moisture, the largeI –V hysteresis collapses with the disappearance of a high resistance state (HRS) and the Schottky barrier. Once the devices are re‐exposed to a humid environment, the typical largeI –V hysteresis can be recovered within hours as the HRS and Schottky interface are restored. The RS mechanism in Au/Nb:STO is attributed to the Schottky barrier modulation by a proton assisted electron trapping and detrapping process. This work highlights the important role of protons/moisture in the RS properties of IT memristors and provides fundamental insight for switching mechanisms in metal oxides‐based memory devices. -
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Abstract Memristors have emerged as transformative devices to enable neuromorphic and in‐memory computing, where success requires the identification and development of materials that can overcome challenges in retention and device variability. Here, high‐entropy oxide composed of Zr, Hf, Nb, Ta, Mo, and W oxides is first demonstrated as a switching material for valence change memory. This multielement oxide material provides uniform distribution and higher concentration of oxygen vacancies, limiting the stochastic behavior in resistive switching. (Zr, Hf, Nb, Ta, Mo, W) high‐entropy‐oxide‐based memristors manifest the “cocktail effect,” exhibiting comparable retention with HfO2‐ or Ta2O5‐based memristors while also demonstrating the gradual conductance modulation observed in WO3‐based memristors. The electrical characterization of these high‐entropy‐oxide‐based memristors demonstrates forming‐free operation, low device and cycle variability, gradual conductance modulation, 6‐bit operation, and long retention which are promising for neuromorphic applications.
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Interface‐type (IT) metal/oxide Schottky memristive devices have attracted considerable attention over filament‐type (FT) devices for neuromorphic computing because of their uniform, filament‐free, and analog resistive switching (RS) characteristics. The most recent IT devices are based on oxygen ions and vacancies movement to alter interfacial Schottky barrier parameters and thereby control RS properties. However, the reliability and stability of these devices have been significantly affected by the undesired diffusion of ionic species. Herein, a reliable interface‐dominated memristive device is demonstrated using a simple Au/Nb‐doped SrTiO3(Nb:STO) Schottky structure. The Au/Nb:STO Schottky barrier modulation by charge trapping and detrapping is responsible for the analog resistive switching characteristics. Because of its interface‐controlled RS, the proposed device shows low device‐to‐device, cell‐to‐cell, and cycle‐to‐cycle variability while maintaining high repeatability and stability during endurance and retention tests. Furthermore, the Au/Nb:STO IT memristive device exhibits versatile synaptic functions with an excellent uniformity, programmability, and reliability. A simulated artificial neural network with Au/Nb:STO synapses achieves a high recognition accuracy of 94.72% for large digit recognition from MNIST database. These results suggest that IT resistive switching can be potentially used for artificial synapses to build next‐generation neuromorphic computing.
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By mimicking biomimetic synaptic processes, the success of artificial intelligence (AI) has been astounding with various applications such as driving automation, big data analysis, and natural-language processing.[1-4] Due to a large quantity of data transmission between the separated memory unit and the logic unit, the classical computing system with von Neumann architecture consumes excessive energy and has a significant processing delay.[5] Furthermore, the speed difference between the two units also causes extra delay, which is referred to as the memory wall.[6, 7] To keep pace with the rapid growth of AI applications, enhanced hardware systems that particularly feature an energy-efficient and high-speed hardware system need to be secured. The novel neuromorphic computing system, an in-memory architecture with low power consumption, has been suggested as an alternative to the conventional system. Memristors with analog-type resistive switching behavior are a promising candidate for implementing the neuromorphic computing system since the devices can modulate the conductance with cycles that act as synaptic weights to process input signals and store information.[8, 9]
The memristor has sparked tremendous interest due to its simple two-terminal structure, including top electrode (TE), bottom electrode (BE), and an intermediate resistive switching (RS) layer. Many oxide materials, including HfO2, Ta2O5, and IGZO, have extensively been studied as an RS layer of memristors. Silicon dioxide (SiO2) features 3D structural conformity with the conventional CMOS technology and high wafer-scale homogeneity, which has benefited modern microelectronic devices as dielectric and/or passivation layers. Therefore, the use of SiO2as a memristor RS layer for neuromorphic computing is expected to be compatible with current Si technology with minimal processing and material-related complexities.
In this work, we proposed SiO2-based memristor and investigated switching behaviors metallized with different reduction potentials by applying pure Cu and Ag, and their alloys with varied ratios. Heavily doped p-type silicon was chosen as BE in order to exclude any effects of the BE ions on the memristor performance. We previously reported that the selection of TE is crucial for achieving a high memory window and stable switching performance. According to the study which compares the roles of Cu (switching stabilizer) and Ag (large switching window performer) TEs for oxide memristors, we have selected the TE materials and their alloys to engineer the SiO2-based memristor characteristics. The Ag TE leads to a larger memory window of the SiO2memristor, but the device shows relatively large variation and less reliability. On the other hand, the Cu TE device presents uniform gradual switching behavior which is in line with our previous report that Cu can be served as a stabilizer, but with small on/off ratio.[9] These distinct performances with Cu and Ag metallization leads us to utilize a Cu/Ag alloy as the TE. Various compositions of Cu/Ag were examined for the optimization of the memristor TEs. With a Cu/Ag alloying TE with optimized ratio, our SiO2based memristor demonstrates uniform switching behavior and memory window for analog switching applications. Also, it shows ideal potentiation and depression synaptic behavior under the positive/negative spikes (pulse train).
In conclusion, the SiO2memristors with different metallization were established. To tune the property of RS layer, the sputtering conditions of RS were varied. To investigate the influence of TE selections on switching performance of memristor, we integrated Cu, Ag and Cu/Ag alloy as TEs and compared the switch characteristics. Our encouraging results clearly demonstrate that SiO2with Cu/Ag is a promising memristor device with synaptic switching behavior in neuromorphic computing applications.
Acknowledgement This work was supported by the U.S. National Science Foundation (NSF) Award No. ECCS-1931088. S.L. and H.W.S. acknowledge the support from the Improvement of Measurement Standards and Technology for Mechanical Metrology (Grant No. 22011044) by KRISS.
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