Assessing the forming temperature role on amorphous and polycrystalline HfO2-based 4 kbit RRAM arrays performance

The impact of temperature during the forming operation on the electrical cells performance and the post-programming stability were evaluated in amorphous and polycrystalline HfO2-based arrays. Forming (between − 40 and 150 °C), reset and set (at room temperature) operations were applied using the incremental step pulse with verify algorithm (ISPVA). The improvements achieved on the forming operation in terms of time and voltages reduction do not impact the subsequent reset/set results. ISPVA perturbations in LRS/HRS current distributions are almost negligible after the first reset/set operation. In this study the best improvement in forming operation in terms of yield, voltage values and cell-to-cell variability is achieved in polycrystalline samples at 80 °C

Investigation of pre-existing and generated defects in non-filamentary a-Si/TiO2 RRAM and their impacts on RTN amplitude distribution

An extensive investigation of the pre-existing and generated defects in amorphous-Si/TiO2 based non-filamentary (a-VMCO) RRAM device has been carried out in this work to identify the switching and degradation mechanisms, through a combination of random-telegraph-noise (RTN) and constant- voltage-stress (CVS) analysis. The amplitude of RTN, which leads to read instability, is also evaluated statistically at different stages of cell degradation and correlated with different defects, for the first time. It is found that the switching between low and high resistance states (LRS and HRS) are correlated with the profile modulation of pre-existing defects in the ‘defect-less’ region near the a-Si/TiO2 interface. The RTN amplitude observed at this stage is small and has a tight distribution. At longer stress times, a percolation path is formed due to defects generation, which introduces larger RTN amplitude and a significant tail in its distribution

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

Electrical Stress Induced Structural Dynamics in Silicon Oxide Resistive Memories

In this thesis, the effects of electrical stress on silicon oxide resistive random access memory (RRAM) devices are studied with a view of understanding the individual mechanisms involved in RRAM operation. This is achieved through a combination of density functional theory (DFT) modelling and characterisation using transmission electron microscopy (TEM). In Part I of the thesis, DFT is used to model the incorporation, diffusion, reduction, and cluster nucleation of Ag in Ag/SiO2/Pt RRAM devices. It is found that Ag incorporates into SiO2 as a Ag+1 ion, which is mobile through large rings, grain boundaries and column boundaries. An O vacancy (VO) mediated Ag cluster model is then proposed, where Ag+1 reduction is shown to occur at 33% and 11% of VO sites at the Ag and Pt electrodes, respectively. In this case, Ag+1 ions bind to VO forming the [Agi/VO] j complex, which is favoured to trap electrons from the electrodes. In this way, as a Ag cluster grows, the metallic Ag-Ag bonding compensates strain in the lattice leading to the breaking of Si-O bonds. The broken Si-O bonds open access to new voids into which small Ag clusters may break from the original Ag cluster and form, providing new sites for cluster nucleation. In Part II of the thesis, Au-Ti-SiOx-Mo, Au-SiOx-Mo and Ti-SiOx-Mo (x approx 1.95) RRAM devices are characterised through TEM. It is shown the roughness of the Mo layer leads to patterning in the device, where voids and column boundaries form in SiOx at the troughs of the SiOx/Mo interface. The column boundaries are shown to facilitate the transport of Ti and Mo during positive electroforming leading to conductive metal-oxide filaments in the SiOx layer. Conversely, oxygen is dispelled from SiOx under negative electroforming, allowing electron tunneling via trap assisted tunnelling through VO sites

Defect Engineering in HfO2/TiN-based Resistive Random Access Memory (RRAM) Devices by Reactive Molecular Beam Epitaxy

Recently, there has been huge interest in emerging memory technologies, spurred by the ever increasing demand for storage capacities in various applications like Internet of Things (IoT), Big Data, etc. CMOS based flash memory, the current mainstay of the memory technology, has been able to increase its density by scaling down to a 16 nm node and further implementation of 3D architectures. However, flash memory is expected to soon run into disadvantage due to challenges in further scaling. Therefore, extensive efforts are being made towards developing new devices for the next generation of non-volatile memories with the combined advantages of flash memory like non-volatility, high density, low cost and low power consumption as well as high speed performance of DRAM. Among the many competitors, resistive random access memories (RRAM) based on resistive switching in oxides are promising due to its simple metal-insulator-metal (MIM) structure, fast switching speeds (<10 ns), excellent scalability (<10 nm) and potential for multi-level switching. RRAM devices based on the popular dielectric-metal gate combination of hafnium oxide (HfO2) and titanium nitride (TiN), which is the subject of research in this work, are particularly interesting due to its compatibility with existing CMOS technology in addition to the aforementioned advantages. Though prototype RRAM chips have already been demonstrated, key problems for commercial realization of RRAM include large variability and insufficient understanding of the complex switching physics. Resistive switching mechanism in oxides is generally understood to be mediated via the transport of oxygen ions leading to the formation of a conductive filament composed of oxygen vacancy defects. Appropriate defect engineering approaches offer potential towards tailoring the switching behavior as well as improving the performance and yield of HfO2-RRAM. In this thesis, the impact of pre-induced defects on the resistive switching behavior of HfO2-RRAM is investigated in detail and our results are presented. Defect engineered oxide thin films were deposited using reactive molecular beam epitaxy (RMBE) to fabricate metal oxide/TiN based devices. RMBE technique offers the unique possibility to precisely and reproducibly control the oxygen stoichiometry of the thin films in a wide range. Using RMBE, defects were introduced in polycrystalline HfOx thin films intrinsically by oxygen stoichiometry engineering and extrinsically via impurity doping (trivalent lanthanum and pentavalent tantalum). Both the studies were performed at at CMOS compatible deposition temperatures (< 450 °C) with an eye on practical applications. Prior to tantalum doping in HfO2, oxygen stoichiometry engineering studies were also performed in amorphous tantalum oxide (TaOx) thin films to identify the oxidation conditions of tantalum metal. The density of oxygen stoichiometry engineered thin films of HfOx and TaOx could be tuned in a wide range from that of the bulk oxide density to close to metallic density. High degree of oxygen deficiency in oxides led to the formation of defect states near the Fermi level as well as multiple oxidation states of the metal, as observed by X-ray photoelectron spectroscopy (XPS). The pure stoichiometric hafnium oxide films crystallize as expected in a stable monoclinic structure (m-HfO2) whereas, oxygen deficient HfOx thin films were found to crystallize in vacancy stabilized tetragonal like structure (t-HfO2-x). Impurity doping also led to the stabilization of higher symmetry tetragonal (t-Ta:HfOx) or cubic structures (c-La:HfOx) depending on the ionic radii of the dopant. The growth of TiN thin films was also investigated using RMBE. The devices used for electrical studies in this work mostly involved deposition of oxides by RMBE on polycrystalline TiN/Si electrodes after ex-situ transfer for further deposition. Therefore, RMBE grown TiN thin film electrodes with similar or better quality would allow in-situ uninterrupted deposition of subsequent oxide layers in future to form cleaner interfaces. Optimized conditions for growth of epitaxial TiN films on the commercially relevant (001) oriented silicon and c-cut sapphire substrates were established, with focus on achieving smooth surfaces and low resistivity. High quality epitaxial TiN(111)||Al2O3(0001) and TiN(001)||Si(001) films with a low resistivity (20-200 uOhm.cm) were achieved, in spite of the large lattice mismatch. Very low surface roughness, characterized by a streaky reflection high energy electron diffraction (RHEED) pattern during TiN film growth was additionally obtained, by tuning the Ti/N flux ratios. Oxygen engineered HfOx/TiN devices were further electrically characterized to obtain I-V characteristics during quasi-static DC switching. Usually, an initial electroforming step (high voltages) is required to obtain further reproducible switching operation (at lower voltages). High device to device variability in RRAM is typically associated with the stochastic nature of electroforming process which increases at higher forming voltages. Using highly oxygen deficient HfOx and TaOx films, the forming voltages were found to be reduced to levels close to operating voltages, paving the way for forming-free devices. However, the use of high defect concentration adds to increasing the complexity of the switching mechanism. This is reflected in the rather complex and dissimilar switching behaviors observed in the myriad of similar RRAM devices reported in the rapidly growing literature. Using model Pt/HfOx/TiN-based device stacks; it is shown that a well-controlled oxygen stoichiometry governs the filament formation and the (partial) occurrence of multiple resistive switching modes (bipolar, unipolar, threshold, complementary). These findings fuel a better fundamental understanding of the underlying phenomena for future theoretical considerations. The oxygen vacancy concentration is found to be the key factor in manipulating the balance between electric field and Joule heating during formation, rupture (reset), and reformation (set) of the conductive filaments in the dielectric. While a bipolar switching occurs in all the devices irrespective of defect concentration, switching modes like unipolar and threshold switching is favored only at higher oxygen stoichiometry. This suggests the suppression of thermal effects via higher heat dissipation and lowered concentration gradient of oxygen vacancies in oxygen deficient devices. A qualitative switching model based on the drift, diffusion and thermophoresis of oxygen ions is suggested to account for the partial occurrence of various switching modes depending on the oxygen stoichiometry. Further, the evolution or drift of high resistance states during endurance test of the common bipolar operation is compared for HfO2 and HfO1.5 based devices and interpreted using the quantum point contact (QPC) model. Similar observations regarding switching modes were also obtained in oxygen engineered Pt/TaOx/TiN devices, therefore allowing the findings to be generalized to other filamentary resistive switching oxides and contributing towards developing a unified switching model. Besides finding application as non-volatile memory, RRAM devices are also promising for hardware implementation of neuromorphic computing. This is motivated by the possibility of multi-level switching or gradual (analog) modulation of resistance in an RRAM device which can emulate biological synapses. Defect engineering approaches have thus been investigated in Pt/hafnium oxide/TiN devices for tuning the DC I-V switching dynamics to achieve multi-level or gradual switching electronic synapses. Higher contribution of thermal effects in pure stoichiometric HfO2 typically results in a single sharp set process and abrupt sharp current jumps during the reset process during a conventional bipolar operation. By using ~18% La-doped HfOx based device, a completely gradual reset behavior with a higher ON/OFF ratio could be achieved during the bipolar reset operation. This is likely related to filament stabilization around the dopant sites allowing a uniform rupture during reset. More interestingly, in oxygen deficient HfO1.5 based devices, intermediate conductance states corresponding to integer or half-integer multiples of quantum conductance (G0) was observed during both the set and reset operations at room temperature. These are related to the better stabilization of intermediate atomic size filament constrictions during the switching process. Occurrence of these intermediate quantum conductance states, especially during the typically abrupt set process, is likely aided by a weaker filament and better thermal dissipation in the highly oxygen deficient devices. These results suggest that a combination of doping and high oxygen vacancy concentration may lead to improved synaptic functionality with concurrent gradual set and reset behaviors

The Direct Tunneling, Dielectric Breakdown Investigation, and RRAM Application in MBE Hexagonal Boron Nitride Monolayers Using Metal-Insulator-Metal Devices

In today’s post-Morre era, low-dimensional materials and their potential electronic applications have attracted extensive attention, but high-quality material synthesis and complicated device physics investigation is still challenging. Our lab is able to use Molecular Beam Epitaxy (MBE) epitaxy to reliably grow high quality millimeter grain size continuous ultrathin 2D (two-dimensional) hexagonal boron-nitridefilm (h-BN ) on Cobalt (Co) and Nickle (Ni) catalytic transition metal substrates. This is highly advantage in 2D electronic and photonic device applications. In this thesis, we report our comprehensive electric tunneling, dielectric breakdown, and memory application of single-layer h-BN film by fabricating scalable Metal-insulator-metal (MIM) diodes. Direct tunneling and dielectric breakdown in molecular beam epitaxial hexagonal boron nitride (h-BN) monolayers were studied based on Ni/h-BN/Ni device configuration in Chapter 2. Effective tunneling areas are orders of magnitude smaller than the physical areas of the devices. Statistical Weibull analysis of the breakdown characteristics shows that breakdown area-scaling law applies to the effective areas rather than physical areas of the devices. The h-BN based MIM devices can sustain repeated DC voltage sweeping stresses up to 85 times under an extremely high compliance current of 100 mA, and the critical electric field is determined to be at least 11.8 MV/cm, demonstrating high dielectric strength and reliability of these h-BN monolayers. The mechanism of the breakdown and recovery of the h-BN monolayer MIM devices is also discussed. The second project (Chapter 3) is devoted to the evaluation of Resistive Random Access Memory (RRAM) devices and the mechanism discussion of monolayer h-BN in MIM structure. The memory performance of bipolar switching shows great endurance with 97 cycles at 100mA compliance current, and a high average of 10^3 on/off ratio, but the reliability is an issue. For this particular film, both non-volatile bipolar and unipolar resistive switching (RS) and volatile threshold (TH) switching phenomena were found to coexist and could be converted from one to the other by controlling the electrical power, which provides a better understanding of the switching models. In devices with Graphene bottom electrodes, bipolar resistive switching with self-compliance current is discovered, making h-BN potential in low-power device applications

Bio-inspired Neuromorphic Computing Using Memristor Crossbar Networks

Bio-inspired neuromorphic computing systems built with emerging devices such as memristors have become an active research field. Experimental demonstrations at the network-level have suggested memristor-based neuromorphic systems as a promising candidate to overcome the von-Neumann bottleneck in future computing applications. As a hardware system that offers co-location of memory and data processing, memristor-based networks represent an efficient computing platform with minimal data transfer and high parallelism. Furthermore, active utilization of the dynamic processes during resistive switching in memristors can help realize more faithful emulation of biological device and network behaviors, with the potential to process dynamic temporal inputs efficiently. In this thesis, I present experimental demonstrations of neuromorphic systems using fabricated memristor arrays as well as network-level simulation results. Models of resistive switching behavior in two types of memristor devices, conventional first-order and recently proposed second-order memristor devices, will be first introduced. Secondly, experimental demonstration of K-means clustering through unsupervised learning in a memristor network will be presented. The memristor based hardware systems achieved high classification accuracy (93.3%) on the standard IRIS data set, suggesting practical networks can be built with optimized memristor devices. Thirdly, implementation of a partial differential equation (PDE) solver in memristor arrays will be discussed. This work expands the capability of memristor-based computing hardware from ‘soft’ to ‘hard’ computing tasks, which require very high precision and accurate solutions. In general first-order memristors are suitable to perform tasks that are based on vector-matrix multiplications, ranging from K-means clustering to PDE solvers. On the other hand, utilizing internal device dynamics in second-order memristors can allow natural emulation of biological behaviors and enable network functions such as temporal data processing. An effort to explore second-order memristor devices and their network behaviors will be discussed. Finally, we propose ideas to build large-size passive memristor crossbar arrays, including fabrication approaches, guidelines of device structure, and analysis of the parasitic effects in larger arrays.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147610/1/yjjeong_1.pd

Characterisation of Novel Resistive Switching Memory Devices

Resistive random access memory (RRAM) is widely considered as a disruptive technology that will revolutionize not only non-volatile data storage, but also potentially digital logic and neuromorphic computing. The resistive switching mechanism is generally conceived as the rupture/restoration of defect-formed conductive filament (CF) or defect profile modulation, for filamentary and non-filamentary devices respectively. However, details of the underlying microscopic behaviour of the resistive switching in RRAM are still largely missing. In this thesis, a defect probing technique based on the random telegraph noise (RTN) is developed for both filamentary and non-filamentary devices, which can reveal the resistive switching mechanism at defect level and can also be used to analyse the device performance issues. HfO2 is one of the most matured metal-oxide materials in semiconductor industry and HfO2 RRAM shows promising potential in practical application. An RTN-based defect extraction technique is developed for the HfO2 devices to detect individual defect movement and provide statistical information of CF modification during normal operations. A critical filament region (CFR) is observed and further verified by defect movement tracking. Both defect movements and CFR modification are correlated with operation conditions, endurance failure and recovery. Non-filamentary devices have areal switching characteristics, and are promising in overcoming the drawbacks of filamentary devices that mainly come from the stochastic nature of the CF. a-VMCO is an outstanding non-filamentary device with a set of unique characteristics, but its resistive switching mechanism has not been clearly understood yet. By utilizing the RTN-based defect profiling technique, defect profile modulation in the switching layer is identified and correlated with digital and analogue switching behaviours, for the first time. State instability is analysed and a stable resistance window of 10 for >106 cycles is restored through combining optimizations of device structure and operation conditions, paving the way for its practical application. TaOx-based RRAM has shown fast switching in the sub-nanosecond regime, good CMOS compatibility and record endurance of more than 1012 cycles. Several inconsistent models have been proposed for the Ta2O5/TaOx bilayered structure, and it is difficult to quantify and optimize the performance, largely due to the lack of microscopic description of resistive switching based on experimental results. An indepth analysis of the TiN/Ta2O5/TaOx/TiN structured RRAM is carried out with the RTN-based defect probing technique, for both bipolar and unipolar switching modes. Significant differences in defect profile have been observed and explanations have been provided

Variability in Resistive Memories

This research was supported by project B-TIC-624-UGR20 funded by the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER program. F.J.A. acknowledges grant PGC2018-098860-B-I00 and PID2021-128077NB-I00 financed by MCIN/ AEI/10.13039/501100011033/FEDER and A-FQM-66-UGR20 financed by the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER program. M.B.G. acknowledges the Ramón y Cajal Grant No. RYC2020-030150-I. M.L. and M.A.V. acknowl- edge generous support from the King Abdullah University of Science and Technology. A.N.M., N.V.A., A.A.D., M.N.K. and B.S. acknowledge the Government of the Russian Federation under Megagrant Program (agreement no. 074-02-2018-330 (2)) and the Ministry of Science and Higher Education of the Russian Federation under “Priority-2030” Academic Excellence Program of the Lobachevsky State University of Nizhny Novgorod (N-466-99_2021-2023). The authors thank D.O. Filatov, A.S. Novikov, and V.A. Shishmakova for their help in studying the dependence of MFPT on external voltage (Section 4). The devices in Section 4 were designed in the frame of the scientific program of the National Center for Physics and Mathematics (project “Artificial intel- ligence and big data in technical, industrial, natural and social systems”) and fabricated at the facilities of Laboratory of memristor nanoelectronics (state assignment for the creation of new laboratories for electronics industry). E.M. acknowledges the support provided by the European proj- ect MEMQuD, code 20FUN06, which has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme.Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuro- morphic computing, hardware cryptography, etc. Their fabrication control and performance have been notably improved in the last few years to cope with the requirements of massive industrial production. However, the most important hurdle to progress in their development is the so-called cycle-to-cycle variability, which is inherently rooted in the resistive switching mechanism behind the operational principle of these devices. In order to achieve the whole picture, variability must be assessed from different viewpoints going from the experi- mental characterization to the adequation of modeling and simulation techni- ques. Herein, special emphasis is put on the modeling part because the accurate representation of the phenomenon is critical for circuit designers. In this respect, a number of approaches are used to the date: stochastic, behavioral, meso- scopic..., each of them covering particular aspects of the electron and ion transport mechanisms occurring within the switching material. These subjects are dealt with in this review, with the aim of presenting the most recent advancements in the treatment of variability in resistive memories.Junta de Andalucía B-TIC-624-UGR20 PID2021-128077NB-I00European CommissionMCIN/AEI/FEDER A-FQM-66-UGR20 PGC2018-098860-B-I00Spanish Government RYC2020-030150-IKing Abdullah University of Science & TechnologyGovernment of the Russian Federation under Megagrant Program 074-02-2018-330 (2)Ministry of Science and Higher Education of the Russian Federation under "Priority-2030" Academic Excellence Program of the Lobachevsky State University of Nizhny Novgorod N-466-99_2021-2023European project MEMQuD 20FUN06EMPIR programmeEuropean Union's Horizon 2020 research and innovation programm

Graphene and Related Materials for Resistive Random Access Memories

Graphene and related materials (GRMs) are promising candidates for the fabrication of resistive random access memories (RRAM). Here, we analyze, classify and evaluate this emerging field, and summarize the performance of the RRAM prototypes using GRMs. Graphene oxide, amorphous carbon films, transition metal dichalcogenides, hexagonal boron nitride and black phosphorous can be used as resistive switching media, in which the switching can be governed either by the migration of intrinsic species or penetration of metallic ions from adjacent layers. Graphene can be used as electrode to provide flexibility and transparency, as well as an interface layer between the electrode and dielectric to block atomic diffusion, reduce power consumption, suppress surface effects, limit the number of conductive filaments in the dielectric, and improve device integration. GRMs-based RRAMs fit some non-volatile memory technological requirements like low operating voltages 10 years, endurance >109 cycles and power consumption ~10 pJ/transition still remain a challenge. More technology-oriented studies including reliability and variability analyses may lead to the development of GRMs-based RRAMs with realistic possibilities of commercialization.We acknowledge support from the Young 1000 Global Talent Recruitment Program of the Ministry of Education of China, the National Natural Science Foundation of China (grants no. 61502326, 41550110223), the Jiangsu Government (grant no. BK20150343), the Ministry of Finance of China (grant no. SX21400213), the Young 973 National Program of the Chinese Ministry of Science and Technology (grant no. 2015CB932700), the Collaborative Innovation Center of Suzhou Nano Science & Technology, the Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, the Priority Academic Program Development of Jiangsu Higher Education Institutions, the National Natural Science Foundation of China under Grant Nos. 61521064, 61322408, 61422407, the Beijing Training Project for the Leading Talents in S&T under Grant No. ljrc201508, the Opening Project of Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, the EU Graphene Flagship, FP7 Grant CARERAMM, ERC Grants Hetero2D and Highgraink, EPSRC Grants EP/K01711X/1, EP/K017144/1, EP/N010345/1, EP/M507799/1, EP/L016087/1, EP/M013243/1