The major focus of artificial intelligence (AI) research is made on biomimetic synaptic processes that are mimicked by functional memory devices in the computer industry [1]. It is urgent to find a memory technology for suiting with Brain-Inspired Computing to break the von Neumann bottleneck which limits the efficiency of conventional computer architectures [2].
Silicon-based flash memory, which currently dominates the market for data storage devices, is facing challenging issues to meet the needs of future data storage device development due to the limitations, such as high-power consumption, high operation voltage, and low retention capacity [1]. The emerging resistive random-access memory (RRAM) has elicited intense research as its simple sandwiched structure, including top electrode (TE) layer, bottom electrode (BE) layer, and an intermediate resistive switching (RS) layer, can store data using RS phenomenon between the high resistance state (HRS) and the low resistance state (LRS). This class of emerging devices is expected to outperform conventional memory devices [3]. Specifically, the advantages of RRAM include low-voltage operation, short programming time, great cyclic stability, and good scalability [4]. Among the materials for RS layer, indium gallium zinc oxide (IGZO) has attracted attention because of its abundance and high atomic diffusion property of oxygen atoms, transparency, and its easily modulated electrical properties by controlling the stoichiometric ratio of indium and gallium as well as oxygen potential in the sputter gas [5, 6]. Moreover, since the IGZO can be applied to both the thin-film transistor (TFT) channel and RS layer, the IGZO-based fully integrated transparent electronics are very promising [5].
In this work, we proposed transparent IGZO-based RRAMs. First, we chose ITO to serve as both TE and BE to achieve high transmittance in the visible regime of light. All three layers (TE, RS, BE layers) were deposited using a multi-target magnetron sputtering system on glass substrates to demonstrate fully transparent oxide-based devices. I-V characteristics were evaluated by a semiconductor parameter analyzer, and our devices showed typical butterfly curves indicating the bipolar RS property. And the IGZO-based RRAM can survive more than 50 continuous sweeping cycles. The optical transmission analysis was carried out via an UV-Vis spectrometer and the average transmittance around 80% out of entire devices in the visible-light wavelength range, implying high transparency. To investigate the thickness dependence on the properties of RS layer, 50nm, 100nm and 150nm RS layer of IGZO RRAM were fabricated. Also, the oxygen partial pressure during the sputtering of IGZO was varied to optimize the property because the oxygen vacancy concentration governs the RS and RRAM performance. Electrode selection is crucial and can impact the performance of the whole device [7]. Thus, Cu TE was chosen for our second type of device because the diffusion of Cu ions can be beneficial for the formation the conductive filament (CF). Finally, a ~5 nm SiO2 barrier layer was employed between TE and RS layers to confine the diffusion of Cu into the RS layer. At the same time, this SiO2 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.
In conclusion, the transparent IGZO-based RRAMs were established. To tune the property of RS layer, the thickness layer and sputtering conditions of RS were adjusted. In order to engineer the diffusion capability of the TE material to the RS layer and the BE, a set of TE materials and a barrier layer were integrated in IGZO-based RRAM and the performance was compared. Our encouraging results clearly demonstrate that IGZO is a promising material in RRAM applications and overcoming the bottleneck of current memory technologies.
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Influence of Oxygen Vacancy and Top Electrode on Switching Behavior of InGaZnO Based Resistive Random Access Memory
Biomimetic synaptic processes, which are imitated by functional memory devices in the computer industry, are a key focus of artificial intelligence (AI) research. It is critical to developing a memory technology that is compatible with Brain-Inspired Computing in order to eliminate the von Neumann bottleneck that restricts the efficiency of traditional computer designs. Due to restrictions such as high operation voltage, poor retention capacity, and high power consumption, silicon-based flash memory, which presently dominates the data storage devices market, is having difficulty meeting the requirements of future data storage device development. The developing resistive random-access memory (RRAM) has sparked intense investigation because of its simple two-terminal structure: two electrodes and a switching layer. RRAM has a resistive switching phenomenon which is a cycling behavior between the high resistance state and the low resistance state. This developing device type is projected to outperform traditional memory devices. Indium gallium zinc oxide (IGZO) has attracted great attention for the RRAM switching layer because of its high transparency and high atomic diffusion property of oxygen atoms. More importantly, by controlling the oxygen ratio in the sputter gas, its electrical properties can be easily tuned. The IGZO has been applied to the thin-film transistor (TFT), thus, it is very promising to integrate RRAM with TFT.
In this work, we proposed IGZO-based RRAMs. ITO was chosen as the bottom electrode towards achieving a fully transparent memristor. And for the IGZO switching layer, we varied the O2/Ar ratio during the deposition to modify the oxygen vacancy of IGZO. Through the XPS measurement, we confirmed that the higher O2/Ar ratio can lower the oxygen vacancy concentration. We also chose ITO as the top electrode, for the comparison, two active metals copper and silver were tested for the top electrode materials. For our IGZO layer, the best ratio of O2/Ar is the middle value. And copper top electrode device has the most stable cycling switching and the silver one is perfect for large memory window, however, it encounters a stability issue. The optical transmission examination was performed using a UV-Vis spectrometer, and the average transmittance
of the complete devices in the visible-light wavelength range was greater than 90%, indicating good transparency. 50nm, 100nm, and 150nm RS layers of IGZO RRAM were produced to explore the thickness dependency on the characteristics of the RS layer. Also, because the oxygen vacancy concentration influences the RS and RRAM performance, the oxygen partial pressure during IGZO sputtering was modified to maximize the property. Electrode selection is critical and can have a significant influence on the device's overall performance. As a result, Cu TE was chosen for our second type of device because Cu ion diffusion can aid in the development of conductive filaments (CF). Finally, between the TE and RS layers, a 5 nm SiO2 barrier layer was used to limit Cu penetration into the RS layer. Simultaneously, this SiO2 inserting layer can offer extra interfacial series resistance in the device, lowering the off current and, as a result, improving the on/off ratio and overall performance.
In conclusion, transparent IGZO-based RRAMs have been created. The thickness of the RS layer and the sputtering conditions of the RS layer were modified to tailor the property of the RS layer. A series of TE materials and a barrier layer were incorporated into an IGZO-based RRAM and the performance was evaluated in order to design the TE material's diffusion capabilities to the RS layer and the BE. Our positive findings show that IGZO is a potential material for RRAM applications and overcoming the existing memory
technology limitation.
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- Award ID(s):
- 1931088
- PAR ID:
- 10347756
- Date Published:
- Journal Name:
- 64th Electronic Materials Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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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
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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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SIGARCH Comput. Archit. News, vol. 23, no. 4, pp. 4–6, 1995.[8] Ielmini
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et al. , Physica Status Solidi (RRL) - Rapid Research Letters, pssr.202200075R1, In press, 2022. -
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Abstract Under varying growth and device processing conditions, ultrabroadband photoconduction (UBPC) reveals strongly evolving trends in the defect density of states (DoS) for amorphous oxide semiconductor thin‐film transistors (TFTs). Spanning the wide bandgap of amorphous InGaZnO
x (a‐IGZO), UBPC identifies seven oxygen deep donor vacancy peaks that are independently confirmed by energetically matching to photoluminescence emission peaks. The subgap DoS from 15 different types of a‐IGZO TFTs all yield similar DoS, except only back‐channel etch TFTs can have a deep acceptor peak seen at 2.2 eV below the conduction band mobility edge. This deep acceptor is likely a zinc vacancy, evidenced by trap density which becomes 5‐6× larger when TFT wet‐etch methods are employed. Certain DoS peaks are strongly enhanced for TFTs with active channel processing damage caused from plasma exposure. While Ar implantation and He plasma processing damage are similar, Ar plasma yields more disorder showing a ≈2 × larger valence‐band Urbach energy, and two orders of magnitude increase in the deep oxygen vacancy trap density. Changing the growth conditions of a‐IGZO also impacts the DoS, with zinc‐rich TFTs showing much poorer electrical performance compared to 1:1:1 molar ratio a‐IGZO TFTs owing to the former having a ∼10 × larger oxygen vacancy trap density. Finally, hydrogen is found to behave as a donor in amorphous indium tin gallium zinc oxide TFTs. -
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Abstract Resistive switching (RS) induced by electrical bias is observed in numerous materials, including 2D hexagonal boron nitride (hBN), which has been used in resistive random access memories (RRAMs) in recent years. For practical high‐density, cross‐point memory arrays, compared with bipolar memories, nonpolar (or unipolar) devices are preferable in terms of peripheral circuit design and storage density. The non‐volatile nonpolar RS phenomenon of hBN‐based RRAMs with Ti/hBN/Au structure as a prototype is reported. Stable manual DC switching for ≈103cycles with an average window over five orders of magnitude is demonstrated. After identifying a possible mechanism related to the Joule heat that contributes to the rupture of conductive filaments in nonpolar RS operations, this mechanism is validated by analyzing the occurrence of the “Re‐set” process. Though the intriguing physical origin still requires more comprehensive studies, the achievement of nonpolar RS should make it more feasible to use hBN in practical RRAM technology.
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