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Atomic View of Filament Growth in Electrochemical Memristive Elements.

Lv H, Xu X, Sun P, Liu H, Luo Q, Liu Q, Banerjee W, Sun H, Long S, Li L, Liu M - Sci Rep (2015)

Bottom Line: The physical nature of the formed filament was characterized by high resolution transmission electron microscopy.Copper rich conical filament with decreasing concentration from center to edge was identified.Based on these results, a clear picture of filament growth from atomic view could be drawn to account for the resistance modulation of oxide electrolyte based electrochemical memristive elements.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China.

ABSTRACT
Memristive devices, with a fusion of memory and logic functions, provide good opportunities for configuring new concepts computing. However, progress towards paradigm evolution has been delayed due to the limited understanding of the underlying operating mechanism. The stochastic nature and fast growth of localized conductive filament bring difficulties to capture the detailed information on its growth kinetics. In this work, refined programming scheme with real-time current regulation was proposed to study the detailed information on the filament growth. By such, discrete tunneling and quantized conduction were observed. The filament was found to grow with a unit length, matching with the hopping conduction of Cu ions between interstitial sites of HfO2 lattice. The physical nature of the formed filament was characterized by high resolution transmission electron microscopy. Copper rich conical filament with decreasing concentration from center to edge was identified. Based on these results, a clear picture of filament growth from atomic view could be drawn to account for the resistance modulation of oxide electrolyte based electrochemical memristive elements.

No MeSH data available.


The refined history of the resistance change during programming.(a) The resistance of cell as a function of VG in the Fig. 1(c) test. A discrete change in resistance is observed. The insert is the magnification of the red solid dots region. (b) Histogram of the resistance states measured from 13360 points in 100 SET curves for VG < 1.1 V. The peaks are fitted with Gaussian distributions as a guide to the eye. (c) The fitting results of the red dots region in (a) after taking into account the series resistance (RS). (d) Histogram of the conductance from 20 SET curves of 10 cells after reducing the serial resistance to 700 Ω. The distribution peaks are positioned at integer or half-integer multiples of G0, which are fitted with Gaussian distributions as a guide to the eye.
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f2: The refined history of the resistance change during programming.(a) The resistance of cell as a function of VG in the Fig. 1(c) test. A discrete change in resistance is observed. The insert is the magnification of the red solid dots region. (b) Histogram of the resistance states measured from 13360 points in 100 SET curves for VG < 1.1 V. The peaks are fitted with Gaussian distributions as a guide to the eye. (c) The fitting results of the red dots region in (a) after taking into account the series resistance (RS). (d) Histogram of the conductance from 20 SET curves of 10 cells after reducing the serial resistance to 700 Ω. The distribution peaks are positioned at integer or half-integer multiples of G0, which are fitted with Gaussian distributions as a guide to the eye.

Mentions: The precise control of the resistance change by real-time regulating the compliance current provided a good platform for studying the growth kinetics of the filament. Figure 2a plots the resistance of cell in the Fig. 1c as a function of VG. The voltage of the bottom electrode (VB, equal to VC) was output to the tester through a detecting point. The cell resistance during programming could then be directly obtained from IDS/VB. The discrete change in the cell resistance can be clearly observed in Fig. 2a. This trend is more clearly shown in the histogram of the resistance states (Fig. 2b) collected from 13360 measured points in 100 SET curves with VG < 1.1 V. It should be noted that the cell resistance was highly dependent on the VG, with a wide range from GΩ to kΩ. Multi-level storage can easily be achieved by controlling different VG (as shown in Figure S2). This large-range resistance distribution cannot be explained by the width variation of the filament or multi-filaments, because the upper limit resistance of atomic-scale filament is only around 12.9 kΩ (1/G0). In the tunneling model or the quantum point contact model272829, incomplete filament with a spatial gap spacing from the counter electrode was used to account for the situation of R >>1/G0. The gap provides a potential barrier for electron transmission and the resistance exponentially increases with the gap length. A small change of the gap would result in large variation of the tunnel resistance. The temperature dependence measurement is an effective approach to identify the tunneling conduction. Figure S3 shows the measurement of temperature dependence on the cell resistance programmed by VG < 1.1 V. Very week dependence was detected, indicating the tunneling was the dominant conduction of the cell when VG was less than 1.1 V.


Atomic View of Filament Growth in Electrochemical Memristive Elements.

Lv H, Xu X, Sun P, Liu H, Luo Q, Liu Q, Banerjee W, Sun H, Long S, Li L, Liu M - Sci Rep (2015)

The refined history of the resistance change during programming.(a) The resistance of cell as a function of VG in the Fig. 1(c) test. A discrete change in resistance is observed. The insert is the magnification of the red solid dots region. (b) Histogram of the resistance states measured from 13360 points in 100 SET curves for VG < 1.1 V. The peaks are fitted with Gaussian distributions as a guide to the eye. (c) The fitting results of the red dots region in (a) after taking into account the series resistance (RS). (d) Histogram of the conductance from 20 SET curves of 10 cells after reducing the serial resistance to 700 Ω. The distribution peaks are positioned at integer or half-integer multiples of G0, which are fitted with Gaussian distributions as a guide to the eye.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4543950&req=5

f2: The refined history of the resistance change during programming.(a) The resistance of cell as a function of VG in the Fig. 1(c) test. A discrete change in resistance is observed. The insert is the magnification of the red solid dots region. (b) Histogram of the resistance states measured from 13360 points in 100 SET curves for VG < 1.1 V. The peaks are fitted with Gaussian distributions as a guide to the eye. (c) The fitting results of the red dots region in (a) after taking into account the series resistance (RS). (d) Histogram of the conductance from 20 SET curves of 10 cells after reducing the serial resistance to 700 Ω. The distribution peaks are positioned at integer or half-integer multiples of G0, which are fitted with Gaussian distributions as a guide to the eye.
Mentions: The precise control of the resistance change by real-time regulating the compliance current provided a good platform for studying the growth kinetics of the filament. Figure 2a plots the resistance of cell in the Fig. 1c as a function of VG. The voltage of the bottom electrode (VB, equal to VC) was output to the tester through a detecting point. The cell resistance during programming could then be directly obtained from IDS/VB. The discrete change in the cell resistance can be clearly observed in Fig. 2a. This trend is more clearly shown in the histogram of the resistance states (Fig. 2b) collected from 13360 measured points in 100 SET curves with VG < 1.1 V. It should be noted that the cell resistance was highly dependent on the VG, with a wide range from GΩ to kΩ. Multi-level storage can easily be achieved by controlling different VG (as shown in Figure S2). This large-range resistance distribution cannot be explained by the width variation of the filament or multi-filaments, because the upper limit resistance of atomic-scale filament is only around 12.9 kΩ (1/G0). In the tunneling model or the quantum point contact model272829, incomplete filament with a spatial gap spacing from the counter electrode was used to account for the situation of R >>1/G0. The gap provides a potential barrier for electron transmission and the resistance exponentially increases with the gap length. A small change of the gap would result in large variation of the tunnel resistance. The temperature dependence measurement is an effective approach to identify the tunneling conduction. Figure S3 shows the measurement of temperature dependence on the cell resistance programmed by VG < 1.1 V. Very week dependence was detected, indicating the tunneling was the dominant conduction of the cell when VG was less than 1.1 V.

Bottom Line: The physical nature of the formed filament was characterized by high resolution transmission electron microscopy.Copper rich conical filament with decreasing concentration from center to edge was identified.Based on these results, a clear picture of filament growth from atomic view could be drawn to account for the resistance modulation of oxide electrolyte based electrochemical memristive elements.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory of Microelectronics Devices and Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, Beijing, 100029, China.

ABSTRACT
Memristive devices, with a fusion of memory and logic functions, provide good opportunities for configuring new concepts computing. However, progress towards paradigm evolution has been delayed due to the limited understanding of the underlying operating mechanism. The stochastic nature and fast growth of localized conductive filament bring difficulties to capture the detailed information on its growth kinetics. In this work, refined programming scheme with real-time current regulation was proposed to study the detailed information on the filament growth. By such, discrete tunneling and quantized conduction were observed. The filament was found to grow with a unit length, matching with the hopping conduction of Cu ions between interstitial sites of HfO2 lattice. The physical nature of the formed filament was characterized by high resolution transmission electron microscopy. Copper rich conical filament with decreasing concentration from center to edge was identified. Based on these results, a clear picture of filament growth from atomic view could be drawn to account for the resistance modulation of oxide electrolyte based electrochemical memristive elements.

No MeSH data available.