Microscopic origin of random telegraph noise fluctuations in aggressively scaled RRAM and its impact on read disturb variability

Random telegraph noise (RTN) is an important intrinsic phenomenon of any logic or memory device that is indicative of the reliability and stochastic variability in its performance. In the context of the resistive random access memory (RRAM), RTN becomes a key criterion that determines the read disturb immunity and memory window between the low (LRS) and high resistance states (HRS). With the drive towards ultra-low power memory (low reset current) and aggressive scaling to 10 × 10 nm2 area, contribution of RTN is significantly enhanced by every trap (vacancy) in the dielectric. The underlying mechanisms governing RTN in RRAM are yet to be fully understood. In this study, we aim to decode the role of conductance fluctuations caused by oxygen vacancy transport and inelastic electron trapping and detrapping processes. The influence of resistance state (LRS, shallow and deep HRS), reset depth and reset stop voltage (VRESET-STOP) on the conductance variability is also investigated. © 2013 IEEE

The Efficacy of Programming Energy Controlled Switching in Resistive Random Access Memory (RRAM)

Current state-of-the-art memory technologies such as FLASH, Static Random Access Memory (SRAM) and Dynamic RAM (DRAM) are based on charge storage. The semiconductor industry has relied on cell miniaturization to increase the performance and density of memory technology, while simultaneously decreasing the cost per bit. However, this approach is not sustainable because the charge-storage mechanism is reaching a fundamental scaling limit. Although stack engineering and 3D integration solutions can delay this limit, alternate strategies based on non-charge storage mechanisms for memory have been introduced and are being actively pursued. Resistive Random Access Memory (RRAM) has emerged as one of the leading candidates for future high density non-volatile memory. The superior scalability of RRAMs is based on the highly localized active switching region and filamentary conductive path. Coupled with its simple structure and compatibility with complementary metal oxide semiconductor (CMOS) processes; RRAM cells have demonstrated switching performance comparable to volatile memory technologies such as DRAMs and SRAMs. However, there are two serious barriers to RRAM commercialization. The first is the variability of the resistance state which is associated with the inherent randomness of the resistive switching mechanism. The second is the filamentary nature of the conductive path which makes it susceptible to noise. In this experimental thesis, a novel program-verify (P-V) technique was developed with the objective to specifically address the programming errors and to provide solutions to the most challenging issues associated with these intrinsic failures in current RRAM technology. The technique, called Compliance-free Ultra-short Smart Pulse Programming (CUSPP), utilizes sub-nanosecond pulses in a compliance-free setup to minimize the programming energy delivered per pulse. In order to demonstrate CUSPP, a custom-built picosecond pulse generator and feedback control circuit was designed. We achieved high (108 cycles) endurance with state verification for each cycle and established high-speed performance, such as 100 ps write/erase speed and 500 kHz cycling rate of HfO2-based RRAM cells. We also investigate switching failure and the short-term instability of the RRAM using CUSPP

Factorial Hidden Markov Model analysis of Random Telegraph Noise in Resistive Random Access Memories

This paper presents a new technique to analyze the characteristics of multi-level random telegraph noise (RTN). RTN is dened as an abrupt switching of ei- ther the current or the voltage between discrete values as a result of trapping/de-trapping activity. RTN sig- nal properties are deduced exploiting a factorial hid- den Markov model (FHMM). The proposed method considers the measured multi-level RTN as a super- position of many two-levels RTNs, each represented by a Markov chain and associated to a single trap, and it is used to retrieve the statistical properties of each chain. These properties (i.e. dwell times and amplitude) are directly related to physical properties of each trap

True random number generator based on the variability of the high resistance state of RRAMs

Hardware-based security primitives like True Random Number Generators (TRNG) have become a crucial part in protecting data over communication channels. With the growth of internet and cloud storage, TRNGs are required in numerous cryptographic operations. On the other hand, the inherently dense structure and low power characteristics of emerging nanoelectronic technologies such as resistive-switching memories (RRAM) make them suitable elements in designing hardware security modules integrated in CMOS ICs. In this paper, a memristor based TRNG is presented by leveraging the high stochasticity of RRAM resistance value in OFF (High Resistive) state. In the proposal, one or two devices can be used depending on whether the objective is focused on saving area or obtaining a higher random bit frequency generation. The generated bits, based on a combination of experimental measurements and SPICE simulations, passed all 15 National Institute of Standards and Technology (NIST) tests and achieved a throughput of tens of MHz.Postprint (published version

Spatially Controlled Generation and Probing of Random Telegraph Noise in Metal Nanocrystal Embedded HfO2Using Defect Nanospectroscopy

Random telegraph noise (RTN) is often considered a nuisance or, more critically, a key reliability challenge for miniaturized semiconductor devices. However, this picture is gradually changing as recent works have shown emerging applications based on the inherent randomness of the RTN signals in state-of-The-Art technologies, including true random number generator and IoT hardware security. Suitable material platforms and device architectures are now actively explored to bring these technologies from an embryonic stage to practical application. A key challenge is to devise material systems, which can be reliably used for the deterministic creation of localized defects to be used for RTN generation. Toward this goal, we have investigated RTN in Au nanocrystal (Au-NC) embedded HfO2stacks at the nanoscale by combining conduction atomic force microscopy defect spectroscopy and a statistical factorial hidden Markov model analysis. With a voltage applied across the stack, there is an enhanced asymmetric electric field surrounding the Au-NC. This in turn leads to the preferential generation of atomic defects in the HfO2near the Au-NC when voltage is applied to the stack to induce dielectric breakdown. Since RTN arises from various electrostatic interactions between closely spaced atomic defects, the Au-NC HfO2material system exhibits an intrinsic ability to generate RTN signals. Our results also highlight that the spatial confinement of multiple defects and the resulting electrostatic interactions between the defects provides a dynamic environment leading to many complex RTN patterns in addition to the presence of the standard two-level RTN signals. The insights obtained at the nanoscale are useful to optimize metal nanocrystal embedded high-κ stacks and circuits for on-demand generation of RTN for emerging random number applications

Stochastic Memory Devices for Security and Computing

With the widespread use of mobile computing and internet of things, secured communication and chip authentication have become extremely important. Hardware-based security concepts generally provide the best performance in terms of a good standard of security, low power consumption, and large-area density. In these concepts, the stochastic properties of nanoscale devices, such as the physical and geometrical variations of the process, are harnessed for true random number generators (TRNGs) and physical unclonable functions (PUFs). Emerging memory devices, such as resistive-switching memory (RRAM), phase-change memory (PCM), and spin-transfer torque magnetic memory (STT-MRAM), rely on a unique combination of physical mechanisms for transport and switching, thus appear to be an ideal source of entropy for TRNGs and PUFs. An overview of stochastic phenomena in memory devices and their use for developing security and computing primitives is provided. First, a broad classification of methods to generate true random numbers via the stochastic properties of nanoscale devices is presented. Then, practical implementations of stochastic TRNGs, such as hardware security and stochastic computing, are shown. Finally, future challenges to stochastic memory development are discussed

Electrical characterization and modeling of random telegraph noise in MIM-like resistive switching devices

Metal-insulator-metal (MIM-like) resistive switching (RS) devices have been increasingly studied for several modern and traditional applications, such as information storage, stochastic computing, and bio-inspired computing. The Random Telegraph Noise (RTN) phenomenon is an important metric regarding the robustness of MIM-like RS devices, and it is intrinsic to any dielectric with defects (traps). In this work, a novel model for anomalous RTN (aRTN) is presented, accounting for the existence of coupling effect between multiple traps regarding current amplitude deviation. It was determined that the contribution of one defect to the current deviation leading to RTN is dependent on the state (i.e., occupied or vacant) of other defects, indicating the presence of coupling effects. A model is proposed to the describe the behavior at low reading voltages (∼ 0.1 V) for both low-resistance state (LRS) and high-resistance state (HRS). The model can be applied to help understanding the dynamics of filament distribution and trapping/de-trapping activity. Additionally, a novel observation of trap acitivity is presented, which results in giant random conductance fluctuations, up to 3 orders of mangnitude, resembling RTN in RS devices based on TiO2, HfO2 and hexagonal boron nitride (h-BN) under reading voltages. Considering this behavior, presented for three different switching materials, we show that this is a quite general phenomenon and that this significant on/off ratio, in reading conditions, is reproducible and beneficial to ensure recognition of device’s two-state in applications such as stochastic computing integrated circuits (ICs). These events were reproducible for all the aforementioned RS device types in sequential measurements and under different bias conditions.Dispositivos de comutação resistiva (RS) estruturados em uma célula do tipo MIM (Metal Isolante Metal) são cada vez mais estudados para diversas aplicações como, por exemplo, no armazenamento de informações, na computação estocástica e na computação inspirada na atividade cerebral. Isso se deve à capacidade desses dispositivos de superar em performance e eficiência os dispositivos atuais, apesar dos desafios relacionados à confiabilidade. O Random Telegraph Noise é um parâmetro relevante para avaliar a robustez de dispositivos memresistivos, relativos à atividade de defeitos (armadilhas). Neste trabalho, um novo modelo para RTN anômalo (aRTN) é apresentado, indicando o acoplamento na amplitude da flutuação de corrente produzida por diferentes armadilhas no mesmo dispositivo. Determina-se que a contribuição de um defeito para o desvio de corrente que leva ao RTN depende do estado (ocupado ou vago) de outra armadilha, caracterizando, dessa forma, o efeito de acoplamento. Propõe-se um modelo elétrico capaz de descrever esse fenômeno para operação de leitura do dispositivo (∼ 0,1 V). Esse modelo pode ser aplicado para melhor compreensão da dinâmica da distribuição dos filamentos na célula e da atividade e interação das armadilhas presentes. Além disso, uma nova observação da atividade de defeitos é apresentada: verificou-se, experimentalmente e em condição de leitura do estado, flutuações significativas na condutância desses dispositivos, que alcançam até 3 ordens de magnitude, semelhantes ao RTNs. Os experimentos foram feitos em dispositivos RS baseados em dielétricos compostos por TiO2, HfO2 e nitreto de boro hexagonal (h-BN). Considerando este comportamento, apresentado para três diferentes materiais de comutação resistiva, verifica-se que este é um fenômeno bastante recorrente e que a significativa relação entre os estados (LRS/HRS), durante a operação de leitura, é reproduzível e benéfica para assegurar o reconhecimento de estados em aplicações como circuitos integrados de computação estocástica (ICs). Esses eventos se mostram reproduzíveis para todos os tipos de dispositivos RS acima mencionados, em medições sequenciais e sob diferentes condições de polarização de leitura

Cerium oxide based resistive random access memory devices

Resistive Random Access Memory (RRAM) is an emerging technology of non-volatile memory (NVM). Although the observation of metal oxide that can undergo an abrupt insulator-metal transition into a conductive state has been known for over 40 years, researchers started investigating those materials for memory applications in late 1990s. It has been considered as the next generation memory technology to replace current flash memory because RRAM has demonstrated feasible switching characteristics and potential to build high density arrays and also RRAM is also compatible with contemporary CMOS processes, which means RRAM can be integrated into current CMOS chips. While the structure of RRAM is a simple metal-insulator-metal (MIM) device, there are numerous materials that exhibit resistive switching. The switching behavior is not only dependent on the switching layer materials but also dependent on the choice of metal electrodes and their interfacial properties. Many metal oxides such as hafnium oxide, titanium oxide, aluminum oxide, nickel oxide (NiO), tantalum oxide and etc. have been studied in details; however, some materials are unexplored such as cerium oxide. In addition to nonvolatile storage applications, RRAM is considered as one of essential elements for advancing neuromorphic computing because of its analog switching and retention characteristics. This thesis investigated CeO[subscript x]-based RRAMs, from its fundamental device characteristics to neuromorphic applications.Electrical and Computer Engineerin