Performance Improvement of Conductive Bridging Random Access Memory by Electrode Alloying

Zinc oxide (ZnO) is an amorphous oxide semiconductor (AOS) material valued for its high carrier mobility, transparency to visible light, and low-temperature manufacturing process compared to silicon-based semiconductors. These desired features make ZnO-based AOSs widely popular as the channel layer in TFTs and as key dielectric layers in electronic devices like light sensors, gas detectors, resistive random-access memory (RRAM), and more. Among them, Conductive Bridge Random Access Memory (CBRAM) with a dielectric switching layer sandwiched between the electrochemically active metal (Ag, Cu) top electrode and the inert bottom electrode, is of a class of RRAM that offers low-voltage operation, high-density storage device, non-volatile, and compatibility with standard CMOS processes [1]. The CBRAM operates based on the principle of conductive filament formation and rupture. During operation, conductive filaments will be formed in switching layer by connecting metal ions which diffuse from the electrode after applying a positive bias. The device will switch to a low resistance state (LRS) after the conductive filaments were formed. After this, applying a negative bias will break the conductive filaments and switch the device back to a high resistance state (HRS). The HRS and LRS are the 0 or1 state of the memory operation. Studies and works have shown that controlling the distribution and diffusion of electrode metal ions in the switching layer is challenging because the conductive filaments formed can vary significantly in strength, ranging from robust to fragile [2]. This leads to instability in the operation of memory devices and encountering difficulties in the integration with TFT pixel array for memory-in-pixel (MiP) power-saving displays [3] or CMOS-integrated compute-in-memory applications [4].In this work, we proposed a novel CBRAM device featuring ZnO nanostructures as the resistive switching layer. The combination of a sputter-deposited seed layer with the water bath method enables the production of high-quality ZnO nanostructures at temperatures below 90°C. These nanostructures play a crucial role in constraining metal ion diffusion and filament formation, leading to the formation of uniform conductive filaments. This improvement significantly enhances the operational stability of the CBRAM device. The experimental results have demonstrated superior memory characteristics with a highly uniform distribution achieved successfully in the ZnO nanostructure-embedded CBRAM, compared to its counterpart lacking ZnO nanostructures. Furthermore, post-treatments are implemented in this study to further promote electrical performance of the nanostructure-embedded CBRAM, like operation voltage, memory window, retention, and endurance. Reference: [1] C. Gopalan, Y. Ma, T. Gallo, J. Wang, E. Runnion, J. Saenz, F. Koushan, P. Blanchard, S. Hollmer, “Demonstration of Conductive Bridging Random Access Memory (CBRAM) in logic CMOS process”, Solid-State Electronics, vol. 58 (1), p. 54-61, 2011.[2] C. C. Hsu, P. T. Liu, K. J. Gan, D. B. Ruan, Simon M. Sze, “Investigation of deposition technique and thickness effect of HfO2 film in bilayer InWZnO-based conductive bridge random access memory”, Vacuum, vol. 201, 111123, 2022.[3] S. H. Lee, B. C. Yu, H. J. Chung, and S. W. Lee, “Memory-in-pixel circuit for low-power liquid crystal displays comprising oxide thin-filmtransistors,” IEEE Electron Device Lett., vol. 11 (11), pp. 1551–1554, 2017.[4] W. Wan, R. Kubendran, C. Schaefer, et al., “A compute-in-memory chip based on resistive random-access memory”, Nature, vol. 608, p. 504–512, 2022.

In resistive random access memory devices (RRAM), materials selection plays a critical role in the tuning of properties like switching voltages, retention, and endurance. Aside from choosing between transition metal-oxide matrices like HfOx, TiOx, TaOx, NiOx, and AlOx, doping in the oxide can also be a powerful tool for device optimization. However, only a handful of dopants have been studied in detail [1-3], and it is currently not known which will offer the greatest benefit for device performance. The filamentary switching mechanism in RRAM devices, in which charged oxygen vacancies (VO’s) coalesce into conductive filaments during switching, has been widely documented [4-9]. Dopants have been shown to affect the switching characteristics of RRAM devices by decreasing the formation energy of VO’s and potentially stabilizing conductive filaments [1-3]. In this investigation, first principles modeling is used to characterize 42 possible dopants in HfOx. In addition to quantifying their effects on HfOx devices, trends are extracted which can serve as general guidelines for doping in any transition metal-oxide, and which are applicable to conductive bridge random access memories (CBRAM) as well. This work identifies a critical new metric for predicting dopant behavior in RRAM and CBRAM: the relative favorability of the dopant forming on substitutional or interstitial sites in the oxide lattice. Dopants that form on interstitial sites, such as Ag, Cu, and Ni, also tend to form cation filaments and thus CBRAM devices. Conversely, dopants that strongly prefer to substitute onto the Hf lattice site are unlikely to produce competing cation filaments, leaving the VO-based switching mechanism intact. The relative favorability is also independent of dopant chemical potential, allowing a direct one-to-one comparison of different dopant species in HfOx. In this work, the quantity of relative stability is formulated and quantified over all 42 cation dopants. The results are shown in Fig. 1. The impact of these dopants on VO formation energy is also analyzed, as shown in Fig. 2. The effect of dopants on device properties is strongly dependent upon dopant species, and Fig.’s 2 and 3 clearly show that these effects follow predictable trends. Finally, the trends underlying dopant behavior are explored, and a model is developed to predict dopant behavior in the oxide system. The behavior of the dopant was found to vary predictably as a function of six key quantities: (1) the valence difference between the dopant and Hf, (2) the dopant atomic radius, (3) the dopant oxide enthalpy of formation, (4) the change in dopant coordination from native oxide to HfOx, (5) the magnetization of the doped system, and (6) the perturbation of neighboring ion charge states by the dopant. The derived composite function predicts the relative dopant site favorability with 95% accuracy. Since these quantities can all be calculated for different oxides, it is expected that these trends can be used as guidelines for doping in any transition metal-oxide for both RRAM and CBRAM applications. [1] D. Duncan, B. Magyari-Köpe, and Y. Nishi, Appl. Phys. Lett. 108, 043501, 2016. [2] L. Zhao, S. W. Ryu, A. Hazeghi, D. Duncan, B. Magyari-Köpe, and Y. Nishi, Tech. Digest VLSI Tech. Symp., T106-T107, 2013. [3] D. Ning, P. Hua, and W. Wei, Chin. Phys. B 23(10), 107306, 2014. [4] D. Duncan, B. Magyari-Köpe, and Y. Nishi, Elec. Dev. Lett. 37 (4), 400-403, 2016. [5] B. Magyari-Köpe, S.G. Park, H.-D. Lee, and Y. Nishi, J. Mater. Sci. 47, pp. 7498-7514, 2012. [6] S.G. Park, B. Magyari-Köpe, and Y. Nishi, Phys. Rev. B, 82, 115109, 2010. [7] H.-D. Lee, B. Magyari-Köpe, and Y. Nishi, Phys. Rev. B 81, 193202, 2010. [8] S.G. Park, B. Magyari-Köpe, and Y. Nishi, Tech. Digest VLSI Tech. Symp., 2011. [9] B. Magyari-Köpe, M. Tendulkar, S.G. Park, H.-D. Lee, and Y. Nishi, Nanotechnology 22, 254029, 2011. Figure 1

Conductive-bridging random access memory (CBRAM) using a cobalt (Co) electrode has recently featured a CMOS-compatible process, excellent data retention, and a sub-μA operating current level, which are difficult to achieve by conventional CBRAM. However, the resistive switching (RS) mechanism of Co CBRAM has not been extensively explored compared to that of the conventional CBRAM cells using Ag, Cu, or Ni as active metal electrodes. Because only implicit inferences based on electrical measurements have been made, the formation of Co filaments is not yet clearly understood. This study presents evidence of Co filament formation in Co/10 nm SiOx/TiN resistive random access memory (RRAM) using direct transmission electron microscopy (TEM) observations. Co protrusions larger than 5 nm are observed, and their exact atomic composition is investigated by spectroscopy. We explain the RS operation of Co/SiOx/TiN cells based on the Co electromigration-mediated filament development process through Co electrode deformation, protrusion, and subsequent Co conductive bridge formation. An asymmetric RS operation and negative temperature correlation of the resistance are found in low resistance state (LRS) cells, which further supports the Co-involved RS operation in Co/SiOx/TiN devices.

In this paper, we investigate the quantized conduction behavior of conductive bridge random access memory (CBRAM) with varied materials and ramping rates. We report stable and reproducible quantized conductance states with integer multiples of fundamental conductance obtained by optimizing the voltage ramping rate and the Ti-diffusion barrier (DB) at the Cu/HfO2 interface. Owing to controlled diffusion of Cu ions by the Ti-DB and the optimized ramping rate, through which it was possible to control the time delay of Cu ion reduction, more than seven levels of discrete conductance states were clearly observed. Analytical modeling was performed to determine the rate-limiting step in filament growth based on an electrochemical redox reaction. Our understanding of the fundamental mechanisms of quantized conductance behaviors provide a promising future for the multi-bit CBRAM device.

Here, we present the synaptic characteristics of AlN-based conductive bridge random access memory (CBRAM) as a synaptic device for neuromorphic systems. Both non-volatile and volatile memory are observed by simply controlling the strength of the Cu filament inside the AlN film. For non-volatile switching induced by high compliance current (CC), good retention with a strong Cu metallic filament is verified. Low-resistance state (LRS) and high-resistance state (HRS) conduction follow metallic Ohmic and trap-assisted tunneling (TAT), respectively, which are supported by I–V fitting and temperature dependence. The transition from long-term plasticity (LTP) to short-term plasticity (STP) is demonstrated by increasing the pulse interval time for synaptic device application. Also, paired-pulse facilitation (PPF) in the nervous system is mimicked by sending two identical pulses to the CBRAM device to induce STP. Finally, potentiation and depression are achieved by gradually increasing the set and reset voltage in pulse transient mode.

Uniformity and retention are crucial aspects for application of conductive bridge random access memory. In this letter, a self-aligned CuSiN interfacial layer was inserted into Cu/TaO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> /Ru device to obtain a Cu/CuSiN/ TaO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> /Ru structure. Compared with the Cu/TaO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> /Ru device, the Cu/CuSiN/TaO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> /Ru device shows much improved uniformity of resistance and programming voltage. Higher ON/ OFF ratio of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1000\times $ </tex-math></inline-formula> was observed, benefiting from the tight distribution of resistance. The standard deviation of set voltage was minimized from 0.635 to 0.187. Moreover, the low-resistance-state retention was also greatly improved. The uniformity and retention improvement could be well explained by the good controlment of cation injection and localization induced by CuSiN interfacial layer.

In this letter, we demonstrate a self-limited conductive-bridging random access memory (CBRAM) that removes the necessity for external current compliance in a one selector–one resistor (1S1R) architecture. The standard Ge2Sb2Te5 (GST) is used as a CBRAM switching layer. In addition, Te-rich GST is also considered. Their performance is then compared. Both samples exhibit self-limited on-current characteristics, and the on-currents of the standard GST and Te-rich GST are ~300 and $\sim 20~\mu \text{A}$ , respectively. The observed self-limited characteristics are caused by the Te in the GST layer because in the presence of Te, Cu tends to form a more stable CuTe phase that restrict Cu filament growth. Furthermore, to confirm the feasibility of crossbar array applications, the 1S1R device is evaluated using a Ag/TiO2-based threshold selector device reported in our previous work. Hence, we confirm leakage current reduction, a uniform resistance distribution, and stable retention characteristics in the 1S1R configuration with no external current compliance.

Ferromagnetic conductive filaments (CFs) were formed in a conductive-bridge random access memory (CBRAM) with a Ni electrode using high current compliances during a set process. We investigated CFs in a Ni/HfO2/Pt CBRAM using the current compliance dependences of the set process, low-temperature characteristics, and anisotropic magnetoresistance (AMR). Set processes occurred when a positive bias was applied to the Ni electrode only; therefore, the switching phenomena showed polarity. The resistance of the ON state (low resistance state) was dependent on the current compliance between 2 and 5 mA. The ON state of the device showed a metallic conduction property, suggested by the temperature dependence of resistance. When a high current compliance (5 mA) was used for programming, the ON state showed AMR, which was direct evidence of ferromagnetic CF formation. This suggests that the formation of a ferromagnetic CF is associated with the accumulation of Ni ions that diffused from the Ni electrode. The OFF-state (high resistance state) resistance slightly increased with decreasing temperature and AMR was not observed.

Resistive random access memory (RRAM) is a prime candidate to replace Flash memory. Of the two classes of RRAM, conductive bridge RAM (CBRAM) is favored over that based on filaments of oxygen vacancies because of its larger on/off resistance ratio. The nature of the filament in Cu/Al2O3-based CBRAM is analyzed using density functional theory. The defect and binding energies of Cu interstitials and clusters in Al2O3 are calculated. The binding energy per Cu interstitial is shown to significantly increase with increasing Cu coordination, whereas the binding per oxygen vacancy only slightly increases with vacancy concentration. This explains why metal filaments in CBRAM devices tend to be denser than oxygen vacancy filaments. Using three different filament models, we discover that the strong binding between Cu interstitials drives filament formation, resulting in Al ions being driven out of the Cu-rich environment. This leads to the formation of densely packed metallic Cu filaments with bonding similar to Cu...

The threshold switching effect is considered of outmost importance for a variety of applications ranging from the reliable operation of crossbar architectures to emulating neuromorphic properties with artificial neural networks. This property is strongly believed to be associated with the rich inherit dynamics of a metallic conductive filament (CF) formation and its respective relaxation processes. Understanding the origin of these dynamics is very important in order to control the degree of volatility and design novel electronic devices. Here, we present a synergistic numerical and experimental approach in order to deal with that issue. The distribution of relaxation time is addressed through time-resolved pulse measurements whereas the entire switching behavior is modeled through a 2D dynamical model by taking into account the destructive interference of the drift/diffusion transport mechanisms and the Soret diffusion flux due to the intense local Joule heating. The proposed mechanism interprets successfully both the threshold to bipolar switching transition as well as the self-rectifying effects in SiO2-based memories. The model incorporates the effect of electrode materials on the switching pattern and provides a different perception of the ionic transport processes, shading light into the ultra-small lifetimes of the CF and explaining the different behavior of the silver or copper active materials in a conductive bridge random access memory architecture.

The variation of resistive switching (RS) parameters is one of the major challenges to push resistive random access memory (RRAM) into application. In this paper, with a statistical methodology, for the first time we study the statistical distributions of set parameters of the Cu/HfO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> /Pt based conductive bridge random access memory (CBRAM). The distributions of the set parameters in each off resistance range are shown to nicely fit a Weibull model. The Weibull slope and scale factor of the set voltage increase logarithmically with the geometric mean of off resistance in different ranges, which can be well explained by the cell-based percolation model of set statistics. And also for the first time, we revel that the Weibull slope of the set current decreases logarithmically with the off resistance. Our study is of significance to reduce the fluctuation of the resistive switching parameters.

CBRAMs (Conductive Bridging Random Access Memory) are a kind of Resistive Random Access Memories (RRAMs) fabricated in the BEOL (Back-End-Of-Line). They are a promising breakthrough for including permanent retention mechanisms (non-volatility) in embedded systems at low cost. Thus, they are becoming very interesting for the designers community as well. To use this device to design innovative circuits, a compact model is mandatory. In this paper, we propose a continuous physical compact model, written in Verilog-A. Main advantage of this approach is its robustness compared to macromodel approach. Moreover, our approach provides more flexibility compared to a behavioural model for adding multilevel aspect. The model is calibrated with the characterization results and integrated in Cadence design flow using Eldo simulator.

The electrochemical metallization cell, also referred to as conductive bridge random access memory, is considered to be a promising candidate or complementary component to the traditional charge based memory. As such, it is receiving additional focus to accelerate the commercialization process. To create a successful mass product, reliability issues must first be rigorously solved. In-depth understanding of the failure behavior of the ECM is essential for performance optimization. Here, we reveal the degradation of high resistance state behaves as the majority cases of the endurance failure of the HfO2 electrolyte based ECM cell. High resolution transmission electron microscopy was used to characterize the change in filament nature after repetitive switching cycles. The result showed that Cu accumulation inside the filament played a dominant role in switching failure, which was further supported by measuring the retention of cycle dependent high resistance state and low resistance state. The clarified physical picture of filament evolution provides a basic understanding of the mechanisms of endurance and retention failure, and the relationship between them. Based on these results, applicable approaches for performance optimization can be implicatively developed, ranging from material tailoring to structure engineering and algorithm design.

The filament operation of resistive random-access memory was studied via in-situ transmission electron microscopy, and the contribution of the conductive filament to the resistance switching was experimentally confirmed. In addition to the operation principles, the device degradation mechanism was studied through repeated write/erase operations. The importance of controlling Cu movement in the switching layer was confirmed for stable CBRAM (conductive bridge random access memory) operations. A device structure with double switching layers and device miniaturization was effective in restricting over accumulation of Cu in the switching layer and localizing the filament. This may improve the robustness of the device against performance degradation.

Ag/GeS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> /W conductive-bridge random access memory (CBRAM) cells are shown to program at room temperature to conductance levels near multiples of the fundamental conductance G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> = 2e <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /h. This behavior is not accounted for in the traditional view that the conductance of a CBRAM cell is a continuous variable proportional to the maximum current allowed to flow during programming. For on -state resistances on the order of 1/G <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> = 12.9 kΩ or less, quantization implies that the Ag "conductive bridge" typically contains a constriction, or even an extended chain, that can be as narrow as a single atom. Implications for device modeling and commercial applications are discussed.