Electro-Thermal Model of Threshold Switching in TaO x -Based Devices

standard von Neumann architecture. [1][2][3][4][5] Among the different materials that have been developed, the study of synaptic devices based on 1D semiconductor nanomaterials is still very limited, with notable reports on carbon nanotubes, [6] Bi 1−x Sb x nanowires, [7] TiO 2 nanowires, [8] organic P 3 HT-polyethylene oxide coresheath nanowires, [9] etc. These studies form a solid foundation to the integration and assembly of 1D nanomaterials for large-scale neuromorphic computing application. However, due to their high surface-to-volume ratio, the electrical performance of semiconductor nanowire devices is strongly influenced by the nature of their surface. [10,11] Surface states of semiconductor nanowires, which are closely related to the morphology and sizes of nanowires, naturally exist due to dangling bonds or surface reconstruction of nanowires. Some surface defects or adsorbates can also lead to surface states on the nanowires. These surface states can produce randomly localized charges, which significantly affect the charge transport behavior, potentially causing band-bending between an electrode and the semiconductor nanowire or even pinning of the Fermi level. [10,12] These surface defects can cause variations of the contact behavior (i.e., Ohmic or Schottky), even for the same type of nanowire-electrode configuration. As a typical example, ZnO nanowires, which have been widely used in field effect transistors, [10,13,14] sensors, [15,16] photodetectors, [17,18] mersistors, [19][20][21] etc., have demonstrated contradictory contact behaviors on Au [22][23][24][25] and Ti [26,27] electrodes. Eliminating the effect of surface defects on semiconductor nanowire devices, especially the contact between electrodes and the nanowire is a major obstacle to achieving improved performance in these devices.In this research, we propose the introduction of an ultrathin metal oxide interfacial layer between Au electrodes and ZnO nanowires to minimize the electrical effect of surface defects on ZnO nanowires. An improved and symmetrical volatile threshold memristive behavior [28] is obtained which was further used to mimic some basic shortterm synaptic functionalities such as excitatory current response, paired-pulse facilitation and depression, and short-term plasticity, promising for neuromorphic computing applications. [29][30][31][32][33] One-dimensional semiconductor nanowires have been widely used as important building blocks in a number of devices. However, the performance of these devices is seriously hindered by the surface states/defects on the nanowires, which is a great obstacle to the realization of controllable and predictable characteristics. The introduction of an ultrathin metal oxide layer between Au electrodes and a ZnO nanowire is used to eliminate the surface effects of the nanowires, leading to improved volatile threshold switching performance. Study of the conduction mechanism demonstrates that the TiO x interfacial layer functions as a barrier between the electrodes and the nanowire, wherein th...

Section: Resultssupporting

confidence: 72%

Ultrathin TiO_x Interface‐Mediated ZnO‐Nanowire Memristive Devices Emulating Synaptic Behaviors

Xiao

Yeow

Nguyễn

et al. 2019

“…The input parameters of the simulation are the material properties (density, specific heat capacity, thermal conductivity, electrical conductivity, and the relative dielectric constant) and the circuit parameters including source voltage and load resistance. The materials properties are the same as in a previous work . The devices had a square 150 × 150 nm 2 active area, which in the simulation was approximated with axisymmetric 2D device with a radius of 170 nm.…”

Section: Methodsmentioning

confidence: 99%

Stable Metallic Enrichment in Conductive Filaments in TaO_x‐Based Resistive Switches Arising from Competing Diffusive Fluxes

Goodwill

et al. 2019

Self Cite

Oxide‐based resistive‐switching devices hold promise for solid‐state memory technology. Information encoding is accomplished by electrically switching the device between two nonvolatile states with low and high resistance states (LRS/HRS). It is generally accepted that the change between these states is due to the motion of oxygen vacancies forming a continuous (LRS) or gapped (HRS) filament between the electrodes. Direct assessments of filaments are rare due to their small size and the difficulty of locating the filament. Electron microscopy experiments reveal the filament structure and chemistry in TaO2.0 ± 0.2‐based 150 × 150 nm2 devices with cross‐sectional geometry after forming with power dissipation lower than 1 mW. The filaments appear to be roughly hourglass‐shaped with a diameter of less than 10 nm and are composed of Ta‐rich and O‐poor mostly amorphous material with local compositions as Ta‐rich as TaO0.4. The as‐formed HRS has a gap up to 10 nm wide located next to the anode and composed of nearly stoichiometric TaO2.5. The tantalum and oxygen distribution is consistent with filaments formed by the motion of both Ta and O driven by temperature gradients (Soret effect) and an electric field. This interpretation points towards a new compact model of resistive‐switching devices.

“…Under a bias voltage, the neutral V O s in the V O -rich layer lose electrons and become positively charged, and then migrate into the switching layer. For example, a few studies [37][38][39][40] have pointed out that in memristive devices based on such as TaO x [40] and NbO x [38] films, the applied bias can generate pronounced Joule heating through electron conduction (e.g., via the Poole-Frenkel process) that increases the device's internal temperature. Analysis of V O -based conducting filaments has been carried out by transmission electron microscopy (TEM) studies.…”

Section: Anion-driven Rs Effectsmentioning

confidence: 99%

“…These charged V O s can be reduced and eventually form V O -rich regions that increase the device's conductance. [40] Note that when the device resistance is reduced, the Joule heating effect is also suppressed which will induce the negative differential resistance behavior and restores the device to the HRS, showing threshold RS effect. For example, for TiO 2 -based devices (Figure 2a), the conducting filaments may be composed of a metallic phase (Ti 4 O 7 ) that has an increased Ti/O atom ratio (Figure 2b).…”

Section: Anion-driven Rs Effectsmentioning

confidence: 99%

“…Analysis of V O -based conducting filaments has been carried out by transmission electron microscopy (TEM) studies. [40] As such, this volatile behavior can be used as an indication that distinguishes the electronic process-induced switching effects from that caused by ionic process. [32] In contrast, for Ta 2 O 5 -based devices (Figure 2c), the conducting filaments were found to be an oxygen-deficient amorphous Ta (O) solid solution (Figure 2d,e).…”

Section: Anion-driven Rs Effectsmentioning

confidence: 99%

See 1 more Smart Citation

Nanoionic Resistive‐Switching Devices

Zhu

Lee

Lü

2019

devices have opened up promising opportunities for electronic circuit applications beyond energy storage. One representative example is ionic resistive-switching (RS) devices (also called memristive devices or memristors), [3][4][5] which can be used as a nonvolatile memory element due to its excellent performance such as high switching speed (<1 ns), [6] good retention (>10 years), [7] good endurance (>10 9 ), [8] as well as high device scalability. [9] The RS effect refers to the phenomenon that the resistance of a dielectric thin film, typically sandwiched between two electrodes, can be reversibly modulated by an electric field. [2] In ionic RS devices, the mechanism originates from the rearrangement of atoms/ions in the dielectric thin film through ionic drift/ diffusion and electrochemical processes that lead to the formation/rupture of nanoscale conductive paths (filaments) between the two electrodes. [10] Controlling these internal ionic processes will enable the design and implementation of better engineered devices with improved performance and reliability. Additionally, recent studies show that the internal ionic processes during RS can be used to faithfully emulate many biological effects that are critical for learning and memory, allowing efficient neuromorphic systems to be implemented using solid-state devices and networks. [11][12][13] Controlled ionic processes can also be used to directly modify the composition and/or structure of the material itself at the atomic scale, allowing new nanostructures to be built on the fly, in a reconfigurable fashion.In this review, we will first discuss the switching mechanism of ion-induced RS (memristive) effects in nanoscale solid-state thin films, followed by discussions on controlling and utilization of the ionic effects to implement biological synaptic functions, and to reduce device variation and improve device stability. New concepts of material tuning enabled by controlled ionic process will be introduced at the end. Ion-Induced RS EffectSo far, ion-driven RS effects have been observed in a large variety of materials, ranging from oxides, halides, to chalcogenides, etc. [2,[13][14][15] Based on the types of ions involved during the RS process, the switching mechanism can be divided to three categories: cation-driven RS effects, anion-driven RS effects, and cation and anion jointly driven RS effects.Advances in the understanding of nanoscale ionic processes in solid-state thin films have led to the rapid development of devices based on coupled ionic-electronic effects. For example, ion-driven resistive-switching (RS) devices have been extensively studied for future memory applications due to their excellent performance in terms of switching speed, endurance, retention, and scalability. Recent studies further suggest that RS devices are more than just resistors with tunable resistance; instead, they exhibit rich and complex internal ionic dynamics that equip them with native information-processing capabilities, particularly in the temporal domain. RS effec...