skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: (Digital Presentation) Oxide Memristors Based on SiO 2 with Cu/Ag Alloy Metallization for Neuromorphic Computing
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. References [1] Younget al.,IEEE Computational Intelligence Magazine,vol. 13, no. 3, pp. 55-75, 2018. [2] Hadsellet al.,Journal of Field Robotics,vol. 26, no. 2, pp. 120-144, 2009. [3] Najafabadiet al.,Journal of Big Data,vol. 2, no. 1, p. 1, 2015. [4] Zhaoet al.,Applied Physics Reviews,vol. 7, no. 1, 2020. [5] Zidanet al.,Nature Electronics,vol. 1, no. 1, pp. 22-29, 2018. [6] Wulfet al.,SIGARCH Comput. Archit. News,vol. 23, no. 1, pp. 20–24, 1995. [7] Wilkes,SIGARCH Comput. Archit. News,vol. 23, no. 4, pp. 4–6, 1995. [8] Ielminiet al.,Nature Electronics,vol. 1, no. 6, pp. 333-343, 2018. [9] Changet al.,Nano Letters,vol. 10, no. 4, pp. 1297-1301, 2010. [10] Qinet al., Physica Status Solidi (RRL) - Rapid Research Letters, pssr.202200075R1, In press, 2022.  more » « less
Award ID(s):
1931088
PAR ID:
10482458
Author(s) / Creator(s):
; ;
Publisher / Repository:
Institue of Physics
Date Published:
Journal Name:
ECS Meeting Abstracts
Volume:
MA2022-02
Issue:
15
ISSN:
2151-2043
Page Range / eLocation ID:
808 to 808
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; ; ; ; ; ; ; et al (, Advanced Electronic Materials)
    Abstract Different from nonvolatile memory applications, neuromorphic computing applications utilize not only the static conductance states but also the switching dynamics for computing, which calls for compact dynamical models of memristive devices. In this work, a generalized model to simulate diffusive and drift memristors with the same set of equations is presented, which have been used to reproduce experimental results faithfully. The diffusive memristor is chosen as the basis for the generalized model because it possesses complex dynamical properties that are difficult to model efficiently. A data set from statistical measurements on SiO2:Ag diffusive memristors is collected to verify the validity of the general model. As an application example, spike‐timing‐dependent plasticity is demonstrated with an artificial synapse consisting of a diffusive memristor and a drift memristor, both modeled with this comprehensive compact model. 
    more » « less
  2. ; ; ; ; ; ; ; ; ; ; et al (, Advanced Electronic Materials)
    Abstract 2D materials have been of considerable interest as new materials for device applications. Non‐volatile resistive switching applications of MoS2and WS2have been previously demonstrated; however, these applications are dramatically limited by high temperatures and extended times needed for the large‐area synthesis of 2D materials on crystalline substrates. The experimental results demonstrate a one‐step sulfurization method to synthesize MoS2and WS2at 550 °C in 15 min on sapphire wafers. Furthermore, a large area transfer of the synthesized thin films to SiO2/Si substrates is achieved. Following this, MoS2and WS2memristors are fabricated that exhibit stable non‐volatile switching and a satisfactory large on/off current ratio (103–105) with good uniformity. Tuning the sulfurization parameters (temperature and metal precursor thickness) is found to be a straightforward and effective strategy to improve the performance of the memristors. The demonstration of large‐scale MoS2and WS2memristors with a one‐step low‐temperature sulfurization method with simple strategy to tuning can lead to potential applications such as flexible memory and neuromorphic computing. 
    more » « less
  3. ; (, ECS Meeting Abstracts)
    The traditional von Neumann architecture limits the increase in computing efficiency and results in massive power consumption in modern computers due to the separation of storage and processing units. The novel neuromorphic computation system, an in-memory computing architecture with low power consumption, is aimed to break the bottleneck and meet the needs of the next generation of artificial intelligence (AI) systems. Thus, it is urgent to find a memory technology to implement the neuromorphic computing nanosystem. Nowadays, the silicon-based flash memory dominates non-volatile memory market, however, it is facing challenging issues to achieve the requirements of future data storage device development due to the drawbacks, such as scaling issue, relatively slow operation speed, and high voltage for program/erase operations. The emerging resistive random-access memory (RRAM) has prompted extensive research as its simple two-terminal structure, including top electrode (TE) layer, bottom electrode (BE) layer, and an intermediate resistive switching (RS) layer. It can utilize a temporary and reversible dielectric breakdown to cause the RS phenomenon between the high resistance state (HRS) and the low resistance state (LRS). RRAM is expected to outperform conventional memory device with the advantages, notably its low-voltage operation, short programming time, great cyclic stability, and good scalability. Among the materials for RS layer, indium gallium zinc oxide (IGZO) has shown attractive prospects in abundance and high atomic diffusion property of oxygen atoms, transparency. Additionally, its electrical properties can be easily modulated by controlling the stoichiometric ratio of indium and gallium as well as oxygen potential in the sputter gas. Moreover, since the IGZO can be applied to both the thin-film transistor (TFT) channel and RS layer, it has a great potential for fully integrated transparent electronics application. In this work, we proposed amorphous transparent IGZO-based RRAMs and investigated switching behaviors of the memory cells prepared with different top electrodes. First, ITO was choosing to serve as both TE and BE to achieve high transmittance. A multi-target magnetron sputtering system was employed to deposit all three layers (TE, RS, BE layers) on glass substrate. I-V characteristics were evaluated by a semiconductor parameter analyzer, and the bipolar RS feature of our RRAM devices was demonstrated by typical butterfly curves. The optical transmission analysis was carried out via a UV-Vis spectrometer and the average transmittance was around 80% out of entire devices in the visible-light wavelength range, implying high transparency. We adjusted the oxygen partial pressure during the sputtering of IGZO to optimize the property because the oxygen vacancy concentration governs the RS performance. Electrode selection is crucial and can impact the performance of the whole device. Thus, Cu TE was chosen for our second type of device because the diffusion of Cu ions can be beneficial for the formation of the conductive filament (CF). A ~5 nm SiO 2 barrier layer was employed between TE and RS layers to confine the diffusion of Cu into the RS layer. At the same time, this SiO 2 inserting layer can provide an additional interfacial series resistance in the device to lower the off current, consequently, improve the on/off ratio and whole performance. Finally, an oxygen affinity metal Ti was selected as the TE for our third type of device because the concentration of the oxygen atoms can be shifted towards the Ti electrode, which provides an oxygengettering activity near the Ti metal. This process may in turn lead to the formation of a sub-stoichiometric region in the neighboring oxide that is believed to be the origin of better performance. In conclusion, the transparent amorphous IGZO-based RRAMs 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 RRAMs, we integrated a set of TE materials, and a barrier layer on IGZO-based RRAM and compared the switch characteristics. Our encouraging results clearly demonstrate that IGZO is a promising material in RRAM applications and breaking the bottleneck of current memory technologies. 
    more » « less
  4. ; ; ; ; ; ; ; (, Nano Express)
    Abstract Ultrathin (sub-2 nm) Al2O3/MgO memristors were recently developed using anin vacuoatomic layer deposition (ALD) process that minimizes unintended defects and prevents undesirable leakage current. These memristors provide a unique platform that allows oxygen vacancies (VO) to be inserted into the memristor with atomic precision and study how this affects the formation and rupture of conductive filaments (CFs) during memristive switching. Herein, we present a systematic study on three sets of ultrathin Al2O3/MgO memristors with VO-doping via modular MgO atomic layer insertion into an otherwise pristine insulating Al2O3atomic layer stack (ALS) using anin vacuoALD. At a fixed memristor thickness of 17 Al2O3/MgO atomic layers (∼1.9 nm), the properties of the memristors were found to be affected by the number and stacking pattern of the MgO atomic layers in the Al2O3/MgO ALS. Importantly, the trend of reduced low-state resistance and the increasing appearance of multi-step switches with an increasing number of MgO atomic layers suggests a direct correlation between the dimension and dynamic evolution of the conducting filaments and the VOconcentration and distribution. Understanding such a correlation is critical to an atomic-scale control of the switching behavior of ultrathin memristors. 
    more » « less
  5. ; ; ; ; ; ; ; ; ; ; et al (, Advanced Materials)
    Abstract Non‐volatile resistive switching (NVRS) is a widely available effect in transitional metal oxides, colloquially known as memristors, and of broad interest for memory technology and neuromorphic computing. Until recently, NVRS was not known in other transitional metal dichalcogenides (TMDs), an important material class owing to their atomic thinness enabling the ultimate dimensional scaling. Here, various monolayer or few‐layer 2D materials are presented in the conventional vertical structure that exhibit NVRS, including TMDs (MX2, M=transitional metal, e.g., Mo, W, Re, Sn, or Pt; X=chalcogen, e.g., S, Se, or Te), TMD heterostructure (WS2/MoS2), and an atomically thin insulator (h‐BN). These results indicate the universality of the phenomenon in 2D non‐conductive materials, and feature low switching voltage, large ON/OFF ratio, and forming‐free characteristic. A dissociation–diffusion–adsorption model is proposed, attributing the enhanced conductance to metal atoms/ions adsorption into intrinsic vacancies, a conductive‐point mechanism supported by first‐principle calculations and scanning tunneling microscopy characterizations. The results motivate further research in the understanding and applications of defects in 2D materials. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email