Non-volatile resistive switching based on zirconium dioxide: poly (4-vinylphenol) nano-composite

Khan, Muhammad Umair; Hassan, Gul; Bae, Jinho

doi:10.1007/s00339-019-2659-9

Cited by 23 publications

(18 citation statements)

References 39 publications

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“…While the type 1 curve (Figure a) shows very nonlinear (exponential), asymmetric I–V characteristics with respect to the voltage polarity, the type 2 curve is rather symmetric and much more linear. Examples for such a strong nonlinear conduction of type 1 are reported frequently in the literature. ,− In the second type of conduction, the nonlinearity in the same voltage range (≈0.1–1 V) is clearly weaker and example I–V curves are reported as well. ,− …”

Section: Memristive Switching In Vcm Cellsmentioning

confidence: 90%

Comprehensive Model of Electron Conduction in Oxide-Based Memristive Devices

Funck

Menzel

2021

ACS Appl. Electron. Mater.

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Memristive devices are two-terminal devices that can change their resistance state upon application of appropriate voltage stimuli. The resistance can be tuned over a wide resistance range enabling applications such as multibit data storage or analog computing-in-memory concepts. One of the most promising classes of memristive devices is based on the valence change mechanism in oxide-based devices. In these devices, a configurational change of oxygen defects, i.e. oxygen vacancies, leads to the change of the device resistance. A microscopic understanding of the conduction is necessary in order to design memristive devices with specific resistance properties. In this paper, we discuss the conduction mechanism proposed in the literature and propose a comprehensive, microscopic model of the conduction mechanism in this class of devices. To develop this microscopic picture of the conduction, ab initio simulation models are developed. These simulations suggest two different types of conduction, which are both limited by a tunneling through the Schottky barrier at the metal electrode contact. The difference between the two conduction mechanisms is the following: for the first type, the electrons tunnel into the conduction band and, in the second type, into the vacancy defect states. These two types of conduction differ in their current voltage relation, which has been detected experimentally. The origin of the resistive switching is identical for the two types of conduction and is based on a modification of the tunneling distance due to the oxygen vacancy induced screening of the Schottky barrier. This understanding may help to design optimized devices in terms of the dynamic resistance range for specific applications.

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Section: Memristive Switching In Vcm Cellsmentioning

confidence: 90%

Comprehensive Model of Electron Conduction in Oxide-Based Memristive Devices

Funck

Menzel

2021

ACS Appl. Electron. Mater.

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“…It is clear from Figure 6 that, for a low resistive state, all the J(E) dependencies in double logarithmic coordinates are linear with the slope tangent  1 (JOhm  E), which corresponds to Ohm's law. Such a behavior is also typical of memristor structures based on continuous ZrO2 layers in LRS (see Table 1) [16,17,20,22,25,34]. In addition, the I-V curves have a region of switching at U = 0.4 -1 V during the LRS → HRS transition.…”

Section: Lrsmentioning

confidence: 61%

“…An analysis of the J(E) curves accounts for the geometric dimensions of the memristor structures and compares their resistive switching characteristics with those in other papers. Table 1 summarizes the switching mode parameters and morphological features of the Zr/ZrO2-nt/Au structure in comparison with independent data for memristors based on amorphous [22,23,24,26,36], polycrystalline [16,17,20,29,31,33,53] and nanocomposite [34] ZrO2 layers.…”

Section: Discussionmentioning

confidence: 99%

“…It is known that the resistive switching in the oxide layer of MDM structures underlying the memory device operation is usually provided by the mobility of anionic (VO) vacancies [20,25,27,28,29,31,32,33], ions of impurity metals [18,19,20,24,26,33,34,35] or Zr + [16,28,36] in the active layer under an external electric field. The electrical resistance of the memristor in lowresistance (LRS), high-resistance (HRS) and intermediate states are governed by the thickness and imperfection of the dioxide layer [23,24,28,31,32,37].…”

Section: Introductionmentioning

confidence: 99%

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Quantum conductors formation and resistive switching memory effects in zirconia nanotubes

et al. 2021

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The prospects of the development of non-volatile memory elements that involve memristive metal-dielectric-metal sandwich structures are due to the possibility of reliably implementing sustained functional states with quantized conductance. In the present paper, we have explored the properties of Zr/ZrO2/Au memristors fabricated based on an anodic zirconia layer that consists of an ordered array of vertically oriented non-stoichiometric nanotubes with an outer diameter of 30 nm. The operational stability of the designed memory devices has been analyzed in unipolar and bipolar resistive switching modes. The resistance ratio ≥105 between high-resistance (HRS) and low-resistance (LRS) states has been evaluated. It has been found that the LRS conductivity is quantized over a wide range with a fundamental minimum of 0.5G 0 = 38.74 μS due to the formation of quantum conductors based on oxygen vacancies (VO). For Zr/ZrO2/Au memristors, resistive switching mechanisms to be sensitive to the migration of VO in an applied electric field have been proposed. It has been shown that the ohmic type and space-charge-limited conductivities are realized in the LRS and HRS, respectively. Besides, we have offered a brief review of parameters for functional metal/zirconia/metal nanolayered structures to create effective memristors with multiple resistive states and a high resistance ratio.

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“…Recently, novel designed devices have shown promise for realizing the synaptic dynamics in the learning process through various mechanisms of ferroelectric effects [14,15], spintronic effect [16], phase transitions [17,18], and ionic transfer [19,20]. Among these, research on memristive devices employing the connection phenomenon of ion filaments or oxygen vacancy has been conducted by storing information with their conductance states and exhibiting conductivity modulation based on the programming electric field [21][22][23]. Rapid diffusive ions, such as Ag + and Cu 2+ , or oxygen vacancy migrate into the insulating medium materials to form a filamentary structure, and silicone-based compounds are also implemented as a conductive bridge to effectively devise short-term memory (STM) and long-term memory (LTM) [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Short-Term to Long-Term Plasticity Transition Behavior of Memristive Devices with Low Power Consumption via Facilitating Ionic Drift of Implanted Lithium

et al. 2021

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Recent innovations in information technology have encouraged extensive research into the development of future generation memory and computing technologies. Memristive devices based on resistance switching are not only attractive because of their multi-level information storage, but they also display fascinating neuromorphic behaviors. We investigated the basic human brain’s learning and memory algorithm for “memorizing” as a feature for memristive devices based on Li-implanted structures with low power consumption. A topographical and surface chemical functionality analysis of an Li:ITO substrate was conducted to observe its characterization. In addition, a switching mechanism of a memristive device was theoretically studied and associated with ion migrations into a polymeric insulating layer. Biological short-term and long-term memory properties were imitated with the memristive device using low power consumption.

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Non-volatile resistive switching based on zirconium dioxide: poly (4-vinylphenol) nano-composite

Cited by 23 publications

References 39 publications

Comprehensive Model of Electron Conduction in Oxide-Based Memristive Devices

Comprehensive Model of Electron Conduction in Oxide-Based Memristive Devices

Quantum conductors formation and resistive switching memory effects in zirconia nanotubes

Short-Term to Long-Term Plasticity Transition Behavior of Memristive Devices with Low Power Consumption via Facilitating Ionic Drift of Implanted Lithium

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