Metal Oxide Resistive Switching Research Articles

Ultra-Low-Power Hybrid Synaptic Memristor via Simultaneous-Controlled Mechanism of Cations and Anions for Hyper-Scale Synaptic Cores

Recently, memristive devices such as phase change random access memory (PCRAM), resistive random access memory (ReRAM), and ferroelectric random access memory (FeRAM) have been actively researched to implement hyper-scale synaptic cores of various ANNs, i.e., deep neural networks (DNNs), spiking neural networks (SNNs), convolutional neural networks (CNNs), and binarized neural networks (BNNs). In particular, ReRAM is currently being highlighted as an artificial synaptic device because of its multilevel capability (> 11 bits)1, high switching speed (< 100 ps)2, high endurance (> 1012 cycles)3, high scalability, and complementary metal-oxide-semiconductor (CMOS) compatibility4. ReRAM is generally divided into two types: valence change memory (VCM) cells having oxygen vacancy filaments and electrochemical metallization (ECM) cells having conductive metal filaments. VCM cells have great retention but exhibit high switching current (~ 100 μA). In contrast, ECM cells exhibit relatively lower switching current (~10 uA) than VCM cells but have poor retention due to diffusion phenomena at high external temperatures5. Due to their high switching current and poor reliability, VCM and ECM cells have limitations in their application as synaptic devices in next-generation neuromorphic systems for energy consumption similar to that of the human brain (~20 W). In this study, for the first time, we developed a Ru-based ultra-low-power (< 1μA) hybrid synaptic memristor having a simultaneous-controlled mechanism of Ru cations and oxygen anions in a resistive switching layer. To elucidate the simultaneous-controlled mechanism of Ru cations and oxygen anions, we fabricated the VCM, ECM, and Ru-based hybrid memristor and performed x-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) analysis depending on the resistance states (i.e., pristine, set, and reset). In addition, the mobility of mobile species in VCM, ECM, and Ru-based hybrid memristors was calculated indirectly via electrical properties (switching speed, operating voltage) and ToF-SIMS depth profiles, revealing the mechanism by which Ru-based hybrid memristor has low switching currents (< 1μA). Finally, the power consumption of active synaptic cores in the training and inference process of the designed DNN was evaluated for VCM, ECM, and Ru-based hybrid memristor. The simultaneous-controlled mechanism of Ru cations and oxygen anions of the Ru-based hybrid memristor and its application to DNN will be presented in detail. Acknowledgement This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00260527) and Institute of Information & communications Technology Planning & Evaluation (IITP) under the artificial intelligence semiconductor support program to nurture the best talents (IITP-(2023)-RS-2023-00253914) grant funded by the Korea government(MSIT)". References Rao, M. et al. Thousands of conductance levels in memristors integrated on CMOS. Nature 615, 823–829 (2023).Yu, S., Wu, Y., Jeyasingh, R., Kuzum, D. & Wong, H. S. P. An electronic synapse device based on metal oxide resistive switching memory for neuromorphic computation. IEEE Trans. Electron Devices 58, 2729–2737 (2011).Lee, H. Y. et al. Evidence and solution of over-RESET problem for HfOX based resistive memory with sub-ns switching speed and high endurance. Tech. Dig. - Int. Electron Devices Meet. IEDM 7–10 (2010) doi:10.1109/IEDM.2010.5703395.Wong, H. S. P. et al. Metal-oxide RRAM. Proc. IEEE 100, 1951–1970 (2012).Yoon, J. H. et al. A Low-Current and Analog Memristor with Ru as Mobile Species. Adv. Mater. 32, 1–9 (2020). Figure 1

Resistive‐Switching Devices: Recent Progress in Solution‐Based Metal Oxide Resistive Switching Devices (Adv. Mater. 7/2021)

Resistive‐Switching Devices: Recent Progress in Solution‐Based Metal Oxide Resistive Switching Devices (Adv. Mater. 7/2021)

Recent Progress in Solution-Based Metal Oxide Resistive Switching Devices.

Metal oxide resistive switching memories have been a crucial component for the requirements of the Internet of Things, which demands ultra-low power and high-density devices with new computing principles, exploiting low cost green products and technologies. Most of the reported resistive switching devices use conventional methods (physical and chemical vapor deposition), which are quite expensive due to their up-scale production. Solution-processing methods have been improved, being now a reliable technology that offers many advantages for resistive random-access memory (RRAM) such as high versatility, large area uniformity, transparency, low-cost and a simple fabrication of two-terminal structures. Solution-based metal oxide RRAM devices are emergent and promising non-volatile memories for future electronics. In this review, a brief history of non-volatile memories is highlighted as well as the present status of solution-based metal oxide resistive random-access memory (S-RRAM). Then, a focus on describing the solution synthesis parameters of S-RRAMs which induce a massive influence in the overall performance of these devices is discussed. Next, a precise analysis is performed on the metal oxide thin film and electrode interface and the recent advances on S-RRAM that will allow their large-area manufacturing. Finally, the figures of merit and the main challenges in S-RRAMs are discussed and future trends are proposed.

Reliable Multivalued Conductance States in TaO x Memristors through Oxygen Plasma-Assisted Electrode Deposition with in Situ-Biased Conductance State Transmission Electron Microscopy Analysis.

Transition metal oxide-based memristors have widely been proposed for applications toward artificial synapses. In general, memristors have two or more electrically switchable stable resistance states that device researchers see as an analogue to the ion channels found in biological synapses. The mechanism behind resistive switching in metal oxides has been divided into electrochemical metallization models and valence change models. The stability of the resistance states in the memristor vary widely depending on: oxide material, electrode material, deposition conditions, film thickness, and programming conditions. So far, it has been extremely challenging to obtain reliable memristors with more than two stable multivalued states along with endurances greater than ∼1000 cycles for each of those states. Using an oxygen plasma-assisted sputter deposition method of noble metal electrodes, we found that the metal-oxide interface could be deposited with substantially lower interface roughness observable at the nanometer scale. This markedly improved device reliability and function, allowing for a demonstration of memristors with four completely distinct levels from ∼6 × 10-6 to ∼4 × 10-8 S that were tested up to 104 cycles per level. Furthermore through a unique in situ transmission electron microscopy study, we were able to verify a redox reaction-type model to be dominant in our samples, leading to the higher degree of electrical state controllability. For solid-state synapse applications, the improvements to electrical properties will lead to simple device structures, with an overall power and area reduction of at least 1000 times when compared to SRAM.

Stuck-at Fault Tolerance in RRAM Computing Systems

Emerging metal-oxide resistive switching random-access memory (RRAM) devices and RRAM crossbars have demonstrated their potential in boosting the speed and energy-efficiency of analog matrix-vector multiplication. However, due to the immature fabrication technology, commonly occurring Stuck-At-Faults (SAFs) seriously degrade the computational accuracy of an RRAM-based computing system (RCS). In this paper, we present a fault-tolerant framework for RCS. A mapping algorithm with inner fault tolerance is proposed to convert matrix parameters into RRAM conductances in RCS and tolerate SAFs by fully exploring the available mapping space. Two baseline redundancy schemes are proposed to ensure that RCS is effective when the percentage of faulty RRAM cells is high. To reduce the number of redundant RRAM cells when the SAFs follow a non-uniform distribution or an unknown distribution, a distribution-aware redundancy scheme and a re-configurable redundancy scheme are proposed to provide dynamic fault tolerance. Simulation results show that, the baseline redundancy schemes can improve the recognition accuracy of the MNIST data set to almost the same as the RRAM-fault-free case, with an energy overhead of approximately 30%. When SAFs follow a non-uniform and an unknown distribution, the distribution-aware and re-configurable schemes can reduce the number of redundant RRAM cells from more than 200% to less than 40% and 60%, respectively, without reducing the recognition accuracy.

Effect of transition metal element X (X=Mn, Fe, Co, and Ni) doping on performance of ZnO resistive memory

Resistance random access memory (RRAM) based on resistive switching in metal oxides has attracted considerable attention as a promising candidate for next-generation nonvolatile memory due to its high operating speed, superior scalability, and low power consumption. However, some operating parameters of RRAM cannot meet the practical requirement, which impedes its commercialization. A lot of experimental results show that doping is an effective method of improving the performance of RRAM, while the study on the physical mechanism of doping is rare. It is generally believed that the formation and rupture of conducting filaments, caused by the migration of oxygen vacancies under electric field play a major role in resistive switching of metal oxide materials. In this work, the first principle calculation based on density functional theory is performed to study the effects of transition metal element X (X=Mn, Fe, Co, and Ni) doping on the migration barriers and formation energy of oxygen vacancy in ZnO. The calculation results show that the migration barriers of both the monovalent and divalent oxygen vacancy are reduced significantly by Ni doping. This result indicates that the movement of oxygen vacancies in Ni doped ZnO is easier than in undoped ZnO RRAM device, thus Ni doping is beneficial to the formation and rupture of oxygen vacancy conducting filaments. Furthermore, the calculation results show that the formation energy of the oxygen vacancy in ZnO system can be reduced by X doping, especially by Ni doping. The formation energy of the oxygen vacancy decreases from 0.854 for undoped ZnO to 0.307 eV for Ni doped ZnO. Based on the above calculated results, Ni doped and undoped ZnO RRAM device are prepared by using pulsed laser deposition method under an oxygen pressure of 2 Pa. The Ni doped ZnO RRAM device shows the optimized forming process, low operating voltage (0.24 V and 0.34 V for Set and Reset voltage), and long retention time (&gt;104 s). Set and Reset voltage in Ni doped ZnO device decrease by 80% and 38% respectively compared with those in undoped ZnO device. It is known that the density of oxygen vacancies in the device is dependent on the oxygen pressure during preparation. The Ni doped ZnO RRAM device under a higher oxygen pressure (5 Pa) is also prepared. The Ni doped ZnO RRAM device prepared under 5 Pa oxygen pressure shows a little higher Set and Reset voltage than the device prepared under 2 Pa oxygen pressure, while the operating voltages are still lower than those of undoped ZnO RRAM. Thus, the doping effect in the ZnO system is affected by the density of oxygen vacancies in the device. Our work provides a guidance for optimizing the performance of the metal oxide based RRAM device through element doping.

Parasitic resistive switching uncovered from complementary resistive switching in single active-layer oxide memory device

This paper reports the reversible transition processes between the bipolar and complementary resistive switching (CRS) characteristics on the binary metal-oxide resistive memory devices of Pt/HfOx/TiN and Pt/TaOx/TiN by applying the appropriate bias voltages. More interestingly, by controlling the amplitude of the negative bias, the parasitic resistive switching effect exhibiting repeatable switching behavior is uncovered from the CRS behavior. The electrical observation of the parasitic resistive switching effect can be explained by the controlled size of the conductive filament. This work confirms the transformation and interrelationship among the bipolar, parasitic, and CRS effects, and thus provides new insight into the understanding of the physical mechanism of the binary metal-oxide resistive switching memory devices.

(Invited) Resistive Switching in SrTixFe1-XO3 Solid Solution Thin Films: The Influence of Doping on Memristance Dynamics

Redox-based metal oxide resistive switching devices, often referred to as memristors, offer new perspectives towards replacement of classic transistor based memories. Despite the promises of fast non-volatile ns-switching and high package density there is a lack of studies in which the electronic band gap and carrier types are systematically varied for an oxide solid solution in a memristor. In this study we tackle this by doing an extrinsic doping investigation on the oxide system Sr(Tix,Fe1-x)O3 for which the p-type electronic conduction and oxygen vacancy mobility and concentration is strongly altered as band gap of the oxide by almost 1.5 eV. Memory arrays of the model system Pt|Sr(Tix,Fe1-x)O3|Pt cross-bar structures were prepared via sputtering, pulsed laser deposition and microfabrication with respect to oxide doping in the range of 0<x<1. Here, we discuss carrier contributions for the restive switch`s kinetics and switching mechanism dependent on extrinsic doping level of the thin film structures. First, we classically analyze switching kinetics via cyclic voltammetry and impedance.1,2 In these experiments hysteretic bipolar I-V profiles were recorded; a decrease of resistance together with an oppressed resistive switching is observed with increasing doping level 25%. Additionally, we propose chronoamperometry measurements1 to analyze diffusion kinetics of resistive switching oxide materials to the field to understand equilibrium vs. non equilibrium transport processes relative to extrinsic doping concentration applied in the oxide of the resistive switching device. In contrast to state-of-the art cyclovoltametry and pulsed experiments in which the material remains in a metastable state this method allows analyzing the resistive switch in thermodynamical equilibrium giving therefore additional insights into its switching behavior. Through the newly proposed “Memristor-based Cottrell analysis” we determine bias-dependent diffusion constants of 3x10-15 for 6 MV/m for SrTiO3 at ambient.1 These complementary measurement methods demonstrate an extended strategy to analyze redox-based metal oxide resistive switching kinetics. Secondly, we study the influence of humidification effects on the devices performances are discussed.3 We find that Pt|SrTiO3-δ|Pt will strongly modify the overall resistance states by up to 4 orders of magnitude as well as the device`s current-voltage profile shape, number of crossings and switching capability with the moisture level exposure, see figure 1. Comparison of the same humidity shows that this process is fully reversible.3 We attribute this behavior to the changed Schottky barrier by adsorbed surface water molecules and its interplay with the charge transfer of oxygen anionic-electronic charge carriers in the oxide affecting the memristance itself. From a fundamental perspective, these results show that moisture cannot be neglected in the development of anionic-electronic resistive switches as hydroxyl interaction seems to be crucial to the basic property of memristance. This study shows how by systematic doping of the metal oxide the resistive switching properties can be actively tuned to increase its performance.

Metal oxide resistive switching memory: Materials, properties and switching mechanisms

Abstract With the continuously changing landscape of the computer technologies, a new memory type is needed that will be fast, energy efficient and long-lasting. It shall combine the speed of random access memory (RAM) and non-volatile in the same time. Resistive RAM (RRAM) is one of the most promising candidates in this respect. RRAM has attracted a great deal of attention owing to its potential as a possible replacement for flash memory in next-generation nonvolatile memory (NVM) applications. A brief summary of binary metal oxide RRAM is given in this review. We discuss the RRAM technology development based on published papers, including the mechanism of resistive switching in transition metal oxides, resistive switching materials, device structure, properties, and reliability such as endurance and retention of the device. We also provide possible solutions through innovations in device materials, structures, and understanding the device physics.

Resistive switching in TiO2 nanocolumn arrays electrochemically grown

Resistive switching in metal oxides, especially in TiO2, has been intensively investigated for potential application in non-volatile memory microdevices. As one of the working mechanisms, a conducting filament consisting of a substoichiometric oxide phase is created within the oxide layer. With the aim of investigating the filament formation in spatially confined elements, we fabricate arrays of self-ordered TiO2 nanocolumns by porous-anodic-alumina (PAA)-assisted anodizing, incorporate them into solid-state microdevices, study their electron transport properties, and reveal that this anodizing approach is suitable for growing TiO2 nanostructures exhibiting resistive switching. The electrical properties and resistive switching behavior are both dependent on the electrolytic formation conditions, influencing the concentration and distribution of oxygen vacancies in the nanocolumn material during the film growth. Therefore, the PAA-assisted TiO2 nanocolumn arrays can be considered as a platform for investigating various phenomena related to resistive switching in valve metal oxides at the nanoscale.

The effect of oxygen vacancy on switching mechanism of ZnO resistive switching memory

Oxygen vacancy (Vo) is believed to control the switching mechanism of metal oxide resistive switching memory. However, an accurate and quantitative theory to prove this point of view remains absent. In this letter, we propose a model combining the Poole-Frenkel effect, space charge limited current, and the modification of Vo density to simulate the current-voltage curves. The calculated results show reasonable agreements with the experimental data, which indicates that resistive switching between high resistance state and low resistance state in the devices of Al/ZnO/p+-Si is led by the density change of Vo. Furthermore, the essence of this leading effect of Vo density is explained by electrons capture and emission via oxygen vacancies. This research demonstrates the significance of Vo in theory and gives an insight into the switching mechanism.

Optimized stateful material implication logic for three-dimensional data manipulation

The monolithic three-dimensional integration of memory and logic circuits could dramatically improve the performance and energy efficiency of computing systems. Some conventional and emerging memories are suitable for vertical integration, including highly scalable metal-oxide resistive switching devices (“memristors”). However, the integration of logic circuits has proven to be much more challenging than expected. In this study, we demonstrated memory and logic functionality in a monolithic three-dimensional circuit by adapting the recently proposed memristor-based stateful material implication logic. By modifying the original circuit to increase its robustness to device imperfections, we experimentally showed, for the first time, a reliable multi-cycle multi-gate material implication logic operation and half-adder circuit within a threedimensional stack of monolithically integrated memristors. Direct data manipulation in three dimensions enables extremely compact and high-throughput logicin- memory computing and, remarkably, presents a viable solution for the Feynman Grand Challenge of implementing an 8-bit adder at the nanoscale.

Investigation of the Switching Mechanism in TiO2-Based RRAM: A Two-Dimensional EDX Approach

The next generation of nonvolatile memory storage may well be based on resistive switching in metal oxides. TiO2 as transition metal oxide has been widely used as active layer for the fabrication of a variety of multistate memory nanostructure devices. However, progress in their technological development has been inhibited by the lack of a thorough understanding of the underlying switching mechanisms. Here, we employed high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) combined with two-dimensional energy dispersive X-ray spectroscopy (2D EDX) to provide a novel, nanoscale view of the mechanisms involved. Our results suggest that the switching mechanism involves redistribution of both Ti and O ions within the active layer combined with an overall loss of oxygen that effectively render conductive filaments. Our study shows evidence of titanium movement in a 10 nm TiO2 thin-film through direct EDX mapping that provides a viable starting point for the improvement of the robustness and lifetime of TiO2-based resistive random access memory (RRAM).

Technological Exploration of RRAM Crossbar Array for Matrix-Vector Multiplication

Matrix-vector multiplication is the key operation for many computationally intensive algorithms. The emerging metal oxide resistive switching random access memory (RRAM) device and RRAM crossbar array have demonstrated a promising hardware realization of the analog matrix-vector multiplication with ultra-high energy efficiency. In this paper, we analyze the impact of both device level and circuit level non-ideal factors, including the nonlinear current-voltage relationship of RRAM devices, the variation of device fabrication and write operation, and the interconnect resistance as well as other crossbar array parameters. On top of that, we propose a technological exploration flow for device parameter configuration to overcome the impact of non-ideal factors and achieve a better trade-off among performance, energy, and reliability for each specific application. Our simulation results of a support vector machine (SVM) and Mixed National Institute of Standards and Technology (MNIST) pattern recognition dataset show that RRAM crossbar array based SVM is robust to input signal fluctuation but sensitive to tunneling gap deviation. A further resistance resolution test presents that a 6-bit RRAM device is able to realize a recognition accuracy around 90 %, indicating the physical feasibility of RRAM crossbar array based SVM. In addition, the proposed technological exploration flow is able to achieve 10.98 % improvement of recognition accuracy on the MNIST dataset and 26.4 % energy savings compared with previous work. Experimental results also show that more than 84.4 % power saving can be achieved at the cost of little accuracy reduction.

RRAM-Based Analog Approximate Computing

Approximate computing is a promising design paradigm for better performance and power efficiency. In this paper, we propose a power efficient framework for analog approximate computing with the emerging metal-oxide resistive switching random-access memory (RRAM) devices. A programmable RRAM-based approximate computing unit (RRAM-ACU ) is introduced first to accelerate approximated computation, and an approximate computing framework with scalability is then proposed on top of the RRAM-ACU. In order to program the RRAM-ACU efficiently, we also present a detailed configuration flow, which includes a customized approximator training scheme, an approximator-parameter-to-RRAM-state mapping algorithm, and an RRAM state tuning scheme. Finally, the proposed RRAM-based computing framework is modeled at system level. A predictive compact model is developed to estimate the configuration overhead of RRAM-ACU and help explore the application scenarios of RRAM-based analog approximate computing. The simulation results on a set of diverse benchmarks demonstrate that, compared with a x86–64 CPU at 2 GHz, the RRAM-ACU is able to achieve 4.06– $196.41 {\times }$ speedup and power efficiency of 24.59–567.98 GFLOPS/W with quality loss of 8.72% on average. And the implementation of hierarchical model and X application demonstrates that the proposed RRAM-based approximate computing framework can achieve >12.8 $\times$ power efficiency than its pure digital implementation counterparts (CPU, graphics processing unit, and field- programmable gate arrays).

(Keynote) Oxide based Resistive Memories for Low Power Embedded Applications and Neuromorphic Systems

The application potential of the new emerging resistive memories - as phase change memory (PCM), metal oxide resistive switching memory (OxRAM), conductive-bridge memory (CBRAM) or magnetic memories (MRAM) - covers the standalone memory technologies (as NAND and DRAM), but offers also potential for exciting new applications and markets, as new functionality coupled with logic circuits to enable block power-down, or use as synapses in neuromorphic circuits. In this work, we will focus on the role that metal oxide resistive switching memory (OxRAM) can play in these new emerging fields of applications. Concerning the introduction of non-volatile functionality at the logic level, we will demonstrate hybrid (CMOS logic + ReRAM devices) circuits for Ultra Low Power (ULP) fixed-logic IC design (as Non Volatile Flip-Flops). Concerning neuromorphic circuits, we will focus on the emulation of synaptic plasticity effects with resistive memories synapses. We will show the implementation of large-scale energy efficient neuromorphic systems with deterministic multi-level synapses or stochastic-binary synapses. Prototype applications such as complex visual- pattern extraction will be also shown using Convolutional Neural Networks.

Metal Oxide Resistive Switching: Evolution of the Density of States Across the Metal-Insulator Transition

We report the study of gold-SrTiO3 (STO)-gold memristors where the doping concentration in STO can be fine-tuned through electric field migration of oxygen vacancies. In this tunnel junction device, the evolution of the density of states (DOS) can be followed continuously across the metal-insulator transition (MIT). At very low dopant concentration, the junction displays characteristic signatures of discrete dopant levels. As the dopant concentration increases, the semiconductor band gap fills in but a soft Coulomb gap remains. At even higher doping, a transition to a metallic state occurs where the DOS at the Fermi level becomes finite and Altshuler-Aronov corrections to the DOS are observed. At the critical point of the MIT, the DOS scales linearly with energy N(ϵ)∼ϵ, the possible signature of multifractality.

Resistive Switching in Metal Oxides: From Physical Modeling to Device Scaling

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(Invited) Resistive Switching in Metal Oxides: From Physical Modeling to Device Scaling

Resistive switching memory (RRAM) devices are receiving considerable interest as future-generation high-density storage technology or possible enablers of storage class memory. For these applications, there is a strong push toward scaling, in terms of low current operation, low power consumption and small device area. To assess the scaling potential of RRAM, however, the physical mechanisms for switching and reliability issues, such as noise, must be understood in deep detail. This work reviews the current understanding of RRAM switching in terms of ion diffusion and migration mechanisms. The model is used to inspire new RRAM operation schemes, such as complementary switching (CS) which may allow self-select memory crossbar and novel multilevel storage approaches. The scaling dependence of random telegraph noise (RTN) is finally discussed based on numerical simulations of drift-diffusion transport and Poisson equation within the conductive filament.

Composite Cu/VO and VO/Cu Nanofilaments in Cu/Ta2O5/Pt Devices

Formation of nanofilament conductive path in solid electrolytes is a promising phenomenon exploited in reversible resistive switching. 1 Widely researched metal oxide resistive switching memory is one of the most competitive candidates for future generations of nonvolatile memory applications due to its simple cross-point structure, fastswitchingspeed,highscalabilitypotential,andcompatibilitywith CMOS technology. The mechanism of resistive switching random access memory (RRAM) has been widely attributed to formation and rupture of conductive filaments assumed to consist of metal precipitates such as (Cu, Ag, Ni) or oxygen vacancies. 2 Specifically, switching of a resistive Cu/TaOx/Pt device can be based on the formation of two types of CFs in the same device: Cu and oxygen vacancy (Vo) filaments depending on the polarity of switching voltage. 3 The two types of conduction can be distinguished by different values of the temperature coefficient (α) of resistance defined as R(T) = R(To) [1 + α(T-To)]. For TaOx formed by physical vapor deposition (PVD), the temperature coefficient α of the on-resistance Ron is α(Cu-CF) = 0.0033 K −1 for Cu CF and α(Vo-CF) = 0.001 K −1 for Vo CF. 3 The α(Cu-CF) in oxygen deficient TaOx is close to the bulk value of Cu, α(Cu) =0.0039 K −1 . In this paper, we present evidence for composite Cu and VO single CF observed in Cu/Ta2O5/Pt devices with a Ta2O5 deposited by atomic layer deposition (ALD). The characterization of the temperature dependence of the filament resistance is an effective way of exploring the properties of the elusive nano-filaments. 4‐7 In Ni/HfO2/p + Si devices an α(Ni-CF) = 0.0063 K −14 which is close to the temperature coefficient of solid Ni nanowire (30 nm diameter) of α(Ni-NW). = 0.0048 K −1 . 5 In Ref. 6 the temperature coefficient of the resistance has been measured in the range of 100 K to 300 K on Ag CF in Ag/La-BFO/Pt devices and a difference has been found for bipolar α(Ag-bipolar) = 0.00194 K −1 and for unipolar characteristics α(Ag-unipolar) = 0.00177 K −1 . In Ni/ZrO2/Pt devices it was found that α(Ni-CF) varies between 0.00127 K −1 and 0.00220 K −1 , 7 indicating that the Ni CFs are metallic and close to the α coefficients of Ni nanowire with 10‐30 nm diameter. 5,8,9