Memristor Device Overview

Chapter
Part of the Analog Circuits and Signal Processing book series (ACSP)

Abstract

Memristors are one of the emerging technologies that can potentially replace state-of-the-art integrated electronic devices for advanced computing and digital and analog circuit applications including neuromorphic networks. Over the past few years, research and development mostly focused on revolutionizing the metal-oxide materials, which are used as core components of the popular metal-insulator-metal (MIM) memristors owing to their highly recognized resistive switching behavior. This chapter outlines the recent advancements and characteristics of such memristive devices, with a special focus on (i) their established resistive switching mechanisms and (ii) the key challenges associated with their fabrication processes including the impeding criteria of material adaptation for the electrode, capping, and insulator component layers. Potential applications and an outlook into the future development of metal-oxide memristive devices are also outlined.

Keywords

Memory Memristor RRAM Thin film Electrode Metal-oxide Switching Mechanism VCM ECM Fuse-antifuse Fabrication Unipolar Bipolar 

Owing to low-power and ultra-fast switching capabilities, memristors with nanoscale thickness geometry have been extensively investigated as potential replacements for flash memory technology in simple analog- and digital-computing applications [1, 2, 3, 4, 5, 6 ]. In addition, both scalability and interconnectivity of memristors through brain-inspired computing have sparked a considerable move toward advancing of next-generation intelligent computing systems [7, 8, 9]. Over the past few years, research and development mostly focused on revolutionizing the metal-oxide materials, which are used as core components of the popular metal-insulator-metal (MIM) memristors owing to their highly recognized resistive switching behavior.

This chapter outlines the recent advancements and characteristics of such memristive devices, with a special focus on (i) their established resistive switching mechanisms and (ii) the key challenges associated with their fabrication processes including the impeding criteria of material adaptation for the electrode, capping, and insulator component layers. Potential applications and an outlook into the future development of metal-oxide memristive devices are also outlined.

1.1 Memristor Device Definition

The concept of a “memristor” (or memory resistor) device was initially postulated by Leon Chua in 1971, as the fourth fundamental circuit element based on symmetry arguments [3, 10, 11]. The device was proposed as a missing passive element that could link the magnetic flux (φ) to the electric charge (q), a property that cannot be obtained by any combination of the other three fundamental elements, namely the resistor, the capacitor, and the inductor. If the memristance (M) is a constant, then memristance is identical to resistance. However, if M is a function of q, yielding a nonlinear circuit element, then this is the behavior of the fourth circuit element, memristor. Unlike the resistor, if a constant voltage is applied across the memristor, nonlinear change in the current passing through the device is observed. The reason is that the memristor integrates the applied voltage over time (φ) and a change of the amount of charges occurs accordingly. The IV characteristic of the nonlinear relation between q and φ for a sinusoidal input voltage is generally a frequency-dependent, and no combination of nonlinear resistive, capacitive, and inductive components can duplicate the circuit properties of a nonlinear memristor [3, 10, 11]. An elementary memristor can be perceived as a two-terminal device with a sandwiched MIM structure, as illustrated in Fig. 1.1, which is generally integrated into an elementary crossbar circuit. Typical configuration allows for smaller interconnection and higher composite density than the one achieved using conventional three-terminal transistors [12]. Another peculiar feature of a memristor is its memory function, which originates from a resistance state that the device remembers after being subjected to an electric potential difference over a certain time. Although the theory of memristive switching was introduced 40 years ago [3, 11], interpretation of the driving mechanism only appeared two decades later and remains obscure to date [13]. The first clear connection between Chua’s theory and the practical demonstration of a memristor device was achieved by HP Labs in 2008, where scientists observed a memristive behavior at the nanoscale level using thin film titanium dioxide (TiO2) as insulator layer [12]. With a simple mathematical model, researchers at HP Labs were further able to demonstrate that the memristance phenomenon arises naturally in nanoscale systems. HP prototype memristors have been shown to store data, process logic at nanoscale footprint, exhibit long retention time, and offer fast, non-volatile, and low-power electrical switching [1, 12]. Memristors continue to stir up a continuous worldwide research market growth as promising alternatives to classic CMOS-devices, owing to their potential scalability and low-power consumption for memory applications. While interest in memristive devices is steeply increasing (Fig. 1.2), successful commercialization of this technology requires robust and predictive understanding of its fundamental mechanisms [14]. Impeding difficulties on correlating basic mathematical models with performance data collected out of physical devices are viewed as the main barrier to practical implementation of memristors in a wide variety of applications. One of the most complicated processes to understand and control at the molecular view is the electrical switching mechanism as a function of physical core parameters including (i) the chemistry of materials and (ii) the commonly neglected stochastic and interfacial phenomena arising between the sandwiched layers of the device upon physical contact or during electrical operation [1]. Access to such contained information to provide better description of the mechanistic operation of physical memristor devices would hence require thorough investigations of the physico-chemical properties of the materials configured down to nanoscale levels.
Fig. 1.1

Schematic of memristor device structure with Metal-Insulator-Metal (MIM) configuration

Fig. 1.2

Cumulative publications per year from 2008 to 2014. The number of publication is obtained by searching the keywords: memristor, RRAM, and resistive switching from the header “Topic” of the Web of Science electronic site https://webofknowledge.com/

1.2 Switching Mechanism

The first switchingmechanisms were elucidated in the late 1990s with a wide variety of oxide systems [14, 15, 16, 17]. Nowadays, common studies depict the memristive switching behavior based on a popular thin film MIM configuration, where the insulator layer is composed of one or more metal-oxides with semiconducting properties [14]. To act as memristor, a physical MIM device must exhibit a range of internal resistive states, which are tunable in a quasi-stable manner. Different factors play a key role on defining the instantaneous resistive state of the device, of which the applied electric field and the compliance current can be externally manipulated during device characterization. Other restricted synergistic determinants, including (i) electron mobility, (ii) gradient of species concentrations, and (iii) gradient of temperature within the insulator region, closely depend on the solid-state properties of the semiconducting material (i.e., lattice defects) and hence require the modification of the fabrication process for further tuning.

The commonly asserted model for resistive switching in metal-oxide memristors is the formation and rupturing of conductive filaments inside the active layer, which cause the device to shift from the “OFF” state to the “ON” state, and vice versa. The existence of one or more filaments between the two electrode terminals creates a low resistance state (LRS) while the absence of these filaments generates a high resistance state (HRS) (Fig. 1.3). Suggested explanations for this model mostly involve two main resistive switching mechanisms: (i) the valence change memory (VCM) and (ii) the electrochemical metallization memory (ECM). The valence change process particularly builds on induced anion migration that progressively modifies the stoichiometry of the insulator region via oxidation-reduction reactions. The electrochemical metallization mechanism relies on the oxidative interfacial dissolution of an active metal electrode, followed by subsequent cation migration across an ion-conducting electrolyte layer, acting as an insulator [18]. In some cases, a thermochemical process is also described in addition to these two main mechanisms, to further justify some structural and stoichiometric modification changes in the insulator layer as a result of current-induced thermal effects [19, 20].
Fig. 1.3

Schematics of resistive switching according to a filamentary conduction model. a native insulator (HRS); b creation of conductive channels via electroforming; c conductive filaments in a SET process (ON state, HRS to LRS transition); and d filament rupture in a RESET process (OFF state, LRS to HRS transition)

1.2.1 VCM Resistive Switching Mechanism

Evidence of resistive switching was first demonstrated with thin film metal‐oxide‐metal sandwiches, half a century ago [21, 22]. Considerable effort has been made since to study the switching mechanism in a variety of oxide systems, ranging from simple binary transition metal-oxides (e.g., HfO2, TiO2, ZnO, Nb2O5, Ta2O5, MoO, WO, MnO, NiO, CuO), to perovskites (e.g., SrTiO3, Ba0.7Sr0.3TiO3, SrZrO3, BiFeO3) and transparent conducting oxides (TCO), such as SnO2 and indium-tin-oxide (ITO) [21723, 24, 168, 169]. The fundamental mechanism agreed for switching in these oxides, which are classified as “anionic devices,” relies on the migration of oxygen anion species under an external electric field.

In most cases, an electroforming step is required before reproducible device switching can be detected at lower voltage values [2]. The electroforming process [25] is usually achieved by applying a large electrical bias across the two terminals of the memristor device within a certain time interval, in order to generate initial conductive channels via Joule heating effect. The forming step can be suppressed by appropriately modifying the fabrication process to readily introduce oxygen vacancies in order to facilitate the migration of anions within the switching layer [26].

Understanding the filament formation theory in relation to the external electric field applied and to the local generation of Joule heating is still one of the major complexities to unravel in the valence change model. The following factors are suggested to explain the driving force of anion transport during filament formation: (i) drift by electric potential gradient, (ii) electromigration assuming an electron kinetic energy, (iii) Fick diffusion due to ion-concentration gradient, and (iv) thermophoresis due to temperature gradient [1]. The valence change pathway in metal-oxide memristors is often described by a movement of oxygen species that alter the stoichiometry of insulator sublattice, resulting in a concentration gradient of mobile anion species due to parallel vacancy formation in the opposite direction. In order to modulate the resistive switching in anionic devices, naturally existing or initially formed conductive filaments can be further tuned by controlling the magnitude of external electric field applied [27, 28, 29].

1.2.2 ECM Resistive Switching Mechanism

The electrochemical metallization mechanism is usually described in MIM devices involving an electrochemically active electrode (AE), such as Ag or Cu, and a noble counter electrode (CE), such as Pt, Au, or W [30, 31, 32, 33]. Similar to anionic devices, electrochemical switching in cationic devices is based on filament formation throughout the insulator material acting as solid electrolyte. Conductive channels usually form via the movement of dissolved metal cations from the interface of the electrochemically active electrode into the insulator region. The need of a forming step is reported as common pre-requirement before observing reproducible resistive switching in several cationic systems. An assumption of structural changes induced in the electrolyte crystal during the forming step is made to explain the creation of conductive filaments via hosting nanotemplate channels that serve as diffusion paths for the migrating metal cations [14, 18, 34, 35, 36].

When an external electric field is applied, dissolved metal cations tend to move toward the inert counter electrode, leaving behind metal vacancies. Hence, gradual migration of metal cations decreases the effective thickness of insulating layer owing to a progressive nucleation and growth of conductive filaments. As reported in [37], the vacancy formation energy may vary from 0.3 to 3.5 eV, depending on the electrode material. The following steps subsequently take place when a sufficient positive bias voltage is applied to a Cu electrode (AE), during the forming and SET processes (i.e., from HRS to LRS) of an Al/Cu/GeOx/W memristor [36]:
  1. (i)

    Anodic dissolution of the Cu electrode (half-reaction oxidation process):

     
$${\text{Cu}} \to \, {\text{Cu}}^{2 + } + \, 2{\text{e}}^{ - } ;$$
  1. (ii)

    Migration of Cu2+ ions toward the inert tungsten electrode (CE), driven by external electric field and Joule heating. Ion movement is facilitated along rapid diffusion channels that are created by grain boundaries existing inside the GeOx semiconducting electrolyte crystal.

     
  2. (iii)

    Reduction and electrocrystallization of Cu2+ ions at the interface of the W counter electrode, leading to growth of nanowidth Cu filaments (half-reaction equation):

     
$${\text{Cu}}^{2 + } + \, 2{\text{e}}^{ -} \, \to \, {\text{Cu}};$$

Once the Cu filaments short-circuit the GeOx to create a low-resistance metallic ion trail between AE and CE, the memristor device is switched ON from HRS to LRS. For a RESET process (i.e., from LRS to HRS), a negative voltage is applied to Cu (AE), which leads to dissolution/rupture of existing nano Cu metallic filaments due to oxidation (i.e., reversed redox process) and potential Joule heating effect. Hence, reversing the electrode polarity allows for flipping of the migration of dissolved Cu2+ ions back toward Cu (AE).

1.3 Switching Behavior

Two different switching modes, (i) “unipolar” (or nonpolar) and (ii) “bipolar”, are generally recognized for anionic and cationic memristor devices. The schematics of IV curve characteristic of unipolar and bipolar resistive switching are illustrated in Fig. 1.4.
Fig. 1.4

Schematics of IV curve switching characteristics of memristors a unipolar mode; b bipolar mode. “cc = compliance current”

In a unipolar mode (Fig. 1.4a), the change in the resistance state only depends on the magnitude of applied voltage and not the polarity. The SET process (toward ON state) is established at higher voltage than that required for the RESET operation. The level of current reached at the RESET transition point is also greater than the compliance defined during the SET operation. In a bipolar mode (Fig. 1.4b), the use of opposite voltage polarities is a key requirement to switch the devices ON (SET) and OFF (RESET), respectively. Frequent asymmetry of IV curve characteristic is also observed with both switching modes and can be tailored through device fabrication or electrical forming [1].

Although the resistance switching is electrically induced in both modes, the concrete driving force is quite different, depending on the relative implication of the electric field and Joule heating on controlling the formation and stability of conductive channels. Generally speaking, a memristive switching tends to be unipolar when Joule heating effect dominates and bipolar when electric field effect is mainly involved [1].

1.3.1 Unipolar Switching Behavior

A plausible explanation for unipolar switching of metal-oxide memristors is a fuse-antifuse mechanism relying on a filamentary model with the Joule heating effect as a key driving force for mass transfer. According to this view, the SET and RESET transitions are achieved, respectively, via the thermally induced formation and rupture of nanowidth conductive filaments stretching over the entire oxide layer. For instance, the formation of conductive filaments in unipolar anionic switches (i.e., Pt/TiO2/Pt/Au) is attributed to a steep gradient of inner device temperature at the threshold SET or forming voltage, leading to thermophoresis and/or oxygen ion-diffusion within the insulator region [38]. A thermal mapping investigation of the RESET transition of unipolar Pt/NiO/Pt anionic devices suggests that filament rupture occurs by heat-induced solid phase dissolution of oxygen species at very high current densities (strictly beyond the initially set compliance current) [19, 39]. According to a universal model describing the filamentary-based memristive switching from the literature [40], the RESET current (IRESET) and its corresponding voltage (VRESET) are mostly dependent on the SET-state resistance (RSET), with negligible effects on the device geometry and the metal-oxide composition. Ielmini et al. [40] reported the measured IRESET as a function of RSET for several unipolar and bipolar switching RRAM. It is worth mentioning that the value of RSET can be controlled through the compliance current used during the SET operation.

Unipolar resistive switching is rarely observed with cationic devices, since the heat-induced migration mechanism is not yet fully developed within the electrochemical metallization theory. General observations only imply the dependence of the RON resistance range of unipolar devices on the conductivity of the insulator layer before thermal breakdown. Only a few examples of temperature-dependent switching studies of unipolar cationic systems (i.e., Cu/Ta2O5/Pt and Cu/Cu-doped-ZrO2/Pt) suggest an assistant thermal-diffusion path of metallic species that contribute to the RESET event [41, 42]. Furthermore, the geometry of conductive filaments and their growth dynamics remains disputed. For example, a recent in situ electronic imaging of devices under programming suggested that cationic conducting channels may be composed of nanoisland structures rather than co-continuous filaments [43, 44]. Hence, further experimental studies are necessary to clarify the directionality of metallic migration in cationic devices and the level of implication of the inert or active electrode interface on inducing and defining the dynamics of filament rupture in the RESET process.

1.3.2 Bipolar Switching Behavior

Bipolar resistive switching is observed in most metal-oxide cationic devices and in similar anionic systems. It is often associated with a nanoionic transport mechanism that is governed by redox equilibria and is mainly driven by external field. The classic polarity-dependence fingerprint of a bipolar switching regime of cationic switches is reasonably explained by the electrochemical metallization (ECM) theory. The formation of conductive channels during the SET transition requires a positive bias on the active electrode (AE) to release cations, which will be reduced into metallic filaments at the (inert) counter electrode surface. Reversing the polarity triggers the RESET event via backward oxidative dissolution of the metallic filaments, which induces the progressive destruction of the electrodes’ connectivity with existing conductive channels spanning the bulk solid electrolyte [18]. The dynamics of filament growth in cationic metal-oxide devices showing a bipolar switching regime are rarely explored in the literature [14]. An example model is depicted in cationic devices (ECM) having a different insulator system when compared to metal-oxides, such as in the case of Ag/Ag-GeSe/Pt electrochemical cell [45]. According to this model, metal filaments grow in a preferential direction of the active electrode (Ag) during the SET process (i.e., in a direction opposite to the migration of cations). Once the metallic filaments reach the active electrode surface, they create a galvanic metallic contact between the two electrodes, which allows the device to switch ON. If a sufficient voltage of opposite polarity is applied, electrochemical dissolution of metal filaments will take place to RESET the device to its initial OFF state.

Generally speaking, the switching speed of bipolar cationic devices (bipolar ECM) is mainly determined by the kinetics of the various electrochemical processes involved in the formation and rupture of conductive metallic filaments. The underlying mechanism of bipolar switching in anionic systems is better explored in the literature in regards to oxygen anion motion (VCM). A main interpretation of this phenomenon is that the viable resistance state of an anionic device depends on the oxygen affinity of the electrode metal and the height of the Schottky barrier formed at the electrode-active insulator junction [46, 47].

An important question concerns the typical electrode polarization in the SET and RESET processes. For a p-type semiconductor oxide (where holes are the majority charge carriers), few mobile oxygen ions exist near crystal defects involving grain boundaries (i.e., dislocations). When a positive voltage is applied to a terminal electrode having a high affinity toward oxygen species, mobile oxygen anions migrate (via drift or electromigration) toward it and progressively accumulate in its proximity. The resulting abundant negative charge helps narrow the depletion region at the electrode interface, leading to a stable reduction of the electron potential energy barrier (or Schottky barrier height). When the interfacial depletion width is sufficiently narrowed down, assistive electron tunneling further minimizes the contact resistance until the device is switched ON (HRS to LRS). For the RESET process, a negative bias is applied to the same terminal electrode, to create an opposite phenomenon via electrostatic repulsion, which forces the accumulated oxygen anions to move away from the electrode surface. An ion-transport recombination model is proposed by Gao et al. [48] to explain the migration of oxygen ion species back into the insulator bulk. According to this model, oxygen ions move away from the negatively polarized electrode and recombine with bulk oxygen vacancies through which conductive filaments eventually get destroyed, leading to a reset switching event (i.e., from LRS to HRS).

In regards to the dynamics of bipolar switching in anionic devices, linear (i.e., super-exponential) and nonlinear IV bipolar loops are generally recognized, depending on the implication level of the electric field into the kinetics of the ion-transport mechanism and into the observed current (in addition to dissipated power and heat) [49, 50, 51, 52, 170]. Such devices may exhibit switching in subthreshold regime (no sharp switching threshold voltage is defined), due to their large dependence on the smallest variability of memristor chemistry, mainly stemming out of the different fabrication processes explored. It is important to mention that nonlinearity in ionic transport behavior is substantial for simultaneously achieving fast switching speeds and long retention times in memristive devices [53, 59, 171].

1.3.3 Mixed Bipolar/Unipolar Switching Behavior

Several metal-oxide systems including those based on transition metal elements show atypical coexistent bipolar and unipolar resistive switching. Examples of these oxides include TiOx, ZrOx, MoOx, AlOx, and HfO2. In these devices, the external current is the crucial factor determining whether the device will be in a bipolar switching regime (usually at low current) or in a unipolar mode (usually at high current due to Joule heating). The main reason for this mixed behavior is yet unclear, but can possibly be explained in terms of formation and rupturing of conductive filaments. At low currents, it is difficult to generate an optimal temperature that allows the rupture of conductive filaments; whereas by applying small current, it may possible to drift the oxygen vacancy toward the formation of conductive filaments. A compliance current-dependency is particularly believed to affect the switching regime in some of those devices. An example study carried on TiO2thin films describes a resistive bipolar switching regime at low current range and unipolar switching characteristics at a greater value of compliance current [54].

1.4 Effect of Electrodes

The impact of the electrode material on the resistive switching of memristive devices is extensively reported as one of the crucial factors in device fabrication, due to potential chemical interplay existing at the contact surface with the active material [55, 56, 57]. For example, cation inter-diffusion, lack of phase stability and interfacial reactions involving vacancy migration from the electrode surface toward the insulating layer, should be critically examined during the electrode selection process. Typical side interactions usually dictate how the device will behave after a prolonged period of operation and are primarily dependent on the electrode work function (i.e., electron-removal ionization energy), in addition to structural similarities with the insulating layer sublattice (i.e., elemental size and crystal phase) [58, 59, 172].

It is important to mention that the work function criterion must be carefully interpreted since it is usually highly sensitive toward crystal orientation and hence the ways of measurements for the pure electrode material. For instance, the experimental results presented in [60] show a linear increase of the strontium titanate (STO) grains work function as a function of the crystal orientation angle. The effective work function is also completely altered by the nearby composition of the contact surface, which mainly evolves from the electrode deposition process and from interfacing inside the sandwiched MIM structure [61, 62, 63].

Figure 1.5 summarizes the absolute work function of a wide variety of native metals and semiconductor materials including those considered in memristor electrode stacks such as aluminum (Al), titanium (Ti), copper (Cu), nickel (Ni), noble metals like platinum (Pt), gold (Au), ruthenium (Ru), and metal nitrides (TiN, AlN) [64, 65]. A low work function and high oxygen affinity of the electrode material are sometimes regarded as substantial for reducing the forming voltage. For instance, Cagli et al. [66] concluded that a Ti electrode, which is considered as a strong oxygen getter (acceptor), effectively reduces the forming voltage of HfO2memristors by sourcing out interfacial oxygen atoms leading to substoichiometric HfOx regions within the bulk switching film. Nevertheless, it is widely accepted that high work function elements can easily block ion transport and would be more suited for electrode materials to minimize side interactions that may cause irreversible changes within the memristor switching mechanism, ultimately impacting the device’s endurance.
Fig. 1.5

Native work function of various metal and semiconductor elements [127]

The impact of electrode nature on resistive switching has also been of extensive research for the late development of advanced atomic and molecular scale electronics [55, 66]. In MIM two-terminal devices, the resistive switching is mainly observed when a positive voltage is applied to the top electrode resulting into higher resistance state programming [67]. The location where each filament ruptures during the RESET operation seems to largely depend on the type of electrode material. For example, Cagli et al. [66] demonstrated that having top and bottom Pt electrodes leads to unipolar switching in HfO2memristors, whereas mixed TiN-Pt or TiN-Ti electrode systems result in bipolar characteristics. The origin of filament rupture is not well established particularly for ECM (or cationic) devices. Example studies on HfO2 devices with Ti, TiN, or TiON top electrodes, and Pt or Ru bottom electrodes, showed that filament rupture occurs near the top electrode interface [68, 69, 70, 71] while other studies supported the implication of the bottom electrode at inducing the RESET process [67, 72, 73].

An example of real-time dynamic observation of conduction channels in Ag/ZrO2/Pt cationic system reveals the initiation of filament rupture at the interface between the conduction channel and the inert counter electrode Pt (acting as anode) [74]. More research is still needed to elucidate the fundamental nature of the switching regime of cationic devices from the microscopic point of view.

For ZnO memristive devices, the effect of metal electrodes on memristor switching behavior is explained in terms of differences observed on the active layer and electrode materials work function. Recently, Kumar and Baghini [75] demonstrated that a high work function electrode such as Pt can yield a more pronounced hysteresis curve compared to Cr, owing to larger difference between the Pt and ZnO work function. This observation was interpreted with the ability of a Pt/ZnO interface to form a Schottky contact and a depletion layer, which varies with applied external voltage, as opposed to non-switchable Cr/ZnO system [75]. However, when the Pt electrode was replaced with a similar work function material such as Au, a narrower hysteresis curve was recorded. In this case, the soft material properties of Au promote its diffusion into the ZnO interface, which results in the modification of the Schottky contact via the creation of Zn vacancies and the subsequent reduction of the ROFF/RON ratio of the device [75].

The area of the electrode contact is a frequently neglected synthetic parameter and could be an important target for further device optimization. The possible implication of the electrode area is assumed on distinguishing two different geometrical localizations of the switching event: (i) the single filament model and (ii) the area-distributed switching [18, 76]. Typical switching scenarios can be differentiated by measuring the area dependence of the low-resistance state. The ON resistance would be completely independent of the electrode area when the SET event only requires the formation of a single filament [76, 77, 78]. In this case, the remaining non-switching electrode area would be contributing to a parallel resistance, and the nanoscale size of the filament should hence be considered to determine the ultimate scaling limit of the device [79, 80]. When the switching occurs more or less homogeneously over the entire active layer, the ON resistance is found to increase almost proportionally with the electrode area [81, 82]. Hence, scaling down should be considered to improve the ROFF/RON resistance ratio.

In summary, the electrode material properties like work function, oxygen affinity, and softness significantly affect the switching mechanism and the subsequent IV dynamics of memristive devices. It is critically important to further understand the effect of the electrode material on other salient features of device operation, including retention time, endurance, SET and RESET voltages, and ROFF/RON ratios.

1.5 Effect of Capping Layer

The capping is often regarded as a thin buffer layer that can be placed between the top or bottom electrode and the active insulator matrix to improve the switching properties of the memristor devices (i.e., retention time, resistance range, switching speed). The use of a capping layer is mostly reported with anionic devices where it essentially serves on enhancing the switching dynamics by promoting the diffusivity of oxygen species or vacancy carriers. Examples of capping materials include low-resistance metal-oxides (i.e., ITO) [83] or metals of similar or different nature than that present in the insulator matrix (i.e., Ti, Zr, Al, and AlCu) [84, 85, 57, 86, 87]. The affinity of the capping material toward oxygen anions particularly dictates the extent of vacancy migration and hence the speed at which conductive filaments are formed [88, 89]. For instance, it has been reported that a Ti over layer is more adequate for capping interposed metal-oxide—high-k dielectric stacks than Al— owing to its higher oxygen scavenging properties [90].

Studies on TiN/HfO2/TiN memristor reveal that the introduction of a thin Ti buffer layer into the MIM structure induces the formation of a TiOX/HfOX bilayer, which increases the resistance range and improves the overall switching speed and endurance of the device when comparing to the performance of native switching material [84, 73, 87].

The type of capping layer material also affects the HRS/LRS current ratios and the operation voltage window, in view of distinctive kinetics introduced on oxygen and vacancy-related trap formation and destruction. For TaN/(capping)/HfO2/Pt memristive device structure, studies show that Zr capping results into lower VSET/VRESET values, larger window between LRS/HRS current and better HRS current stability at high temperatures (up to 110 °C) than Ti capping [91]. Besides the oxygen affinity of capping layer, another important factor to consider is the bonding energy between the capping material and oxygen. Wang et al. [92] used a thermodynamic quantity, which is the molar Gibbs energy, to quantify the bonding between the capping material and oxygen atoms migrating from the active layer. The study concluded that capping materials with high molar Gibbs energy can hold oxygen atoms so tightly and consequently it becomes difficult to rupture local conducting filaments during the RESET operation.

1.6 Insulating Layer Materials in Memristors

The selection of an appropriate active material is another crucial step in memristor device fabrication. A variety of factors including mainly the semiconducting properties and the inevitably associated Joule heating effects are decisive in the design of operational MIM stacking [93]. For the device to have resistive switching characteristics, it requires an active layer with dual conductive and insulating behavior [1]. Established manners that ensure the formation and rupture of conductive filaments in semiconducting metal-oxide systems are (i) the usage of ready-made non-stoichiometric active materials [94, 95, 96, 97], (ii) doping the insulator with one or more metal or metal-oxide [98, 99], and (iii) interfacing the insulator with a buffering agent layer [84, 100, 101, 102, 85], as illustrated in Fig. 1.6.
Fig. 1.6

Examples of MIM stacks considered in metal-oxide memristor literature. (The relative sizes of the layers are for illustration purposes, only) a [94]; b [95]; c [98]; d [84]; e [100]; f [101]; g [83]

Active materials are generally categorized based on their anionic composition (i.e., oxides, tellurides, sulfides, nitrides [2]), crystal structure (i.e., amorphous, perovskites [1]), dimensionality (i.e., zero, one and two with respect to nanoparticles [103], nanowires [104], and films [105]), but more prominently according to their unipolar and bipolar switching behavior [2, 49, 106]. The particular focus on metal-oxide-based insulators is in view of their simplistic atomic structure, good thermal stability, compatibility with mature CMOS processing, and optimum switching characteristics [107, 108].

Tables 1.1, 1.2, and 1.3 provide a mapping of important operational memristive characteristics of various physical MIM metal-oxide systems reported in the literature. The devices are listed according to their bipolar/unipolar switching nature and according to their chemical composition. Example of relevant electrical performance descriptors include VSET and VRESET (or voltage sweep window), ROFF/RON ratio, switching speed, retention time, and endurance. Of the quantitative data collected, a large variability is generally observed on the electrical performance characteristics and behavior of metal-oxide memristor devices, due to non-standardized testing conditions and high intrinsic implications of (i) historical processing operations, (ii) stack configurations and elementary compositions, and (iii) elaboration methods. For example, the fabrication of an active insulator layer can be performed via various techniques (Tables 1.1, 1.2 and 1.3), which are generally based on (i) physical deposition, such as sputtering, electron beam evaporation, pulsed laser deposition, thermal evaporation, and electrohydrodynamic printing, or on (ii) chemical transformation such as atomic layer deposition (ALD), ultrasonic spray pyrolysis, rapid thermal oxidation, plasma-enhanced molecular beam epitaxy, and sol-gel process. Particularly, radio frequency (RF) sputtering is considered as the most popular approach for large-area uniform thin film deposition, owing to its high yield with nanometric thickness control capabilities and low cost of operation [49]. For advanced nanoscale fabrication, greater focus is made on ALD process, which further allows a chemically uniform deposition at one atomic-scale resolution. The ALD route also allows for selective tuning of the material composition via the introduction of chemical dopants [109] and control of oxygen vacancy concentration [110]. Finally, the sol-gel process is regarded as the least expensive approach but is mainly useful for microscale engineering [111]. In conclusion, the growth temperature will be the decisive factor in determining the CMOS processing compatibility of metal-oxide memristor devices. Any fabrication process anticipated of the above will certainly have a different implication on the thermo-mechanical stability and ion migration properties, which should be mapped against the cost of durability, scalability, and performance reproducibility of the devices.
Table 1.1

Examples of bipolar metal-oxide memristors and their operational characteristics

Material

TE/BE

VSET/VRESET

Roff (Ω)

Ron (Ω)

ΔR = Roff /Ron

Switching speed

Retention time

Endurance

Fabrication process

References

ZnO

Ag/Cu

1.2 V/−1.25 V

5E6

5E3

1000

>500 cycles

Electrohydrodynamic printing

[128]

Pt/Pt

1 V/−0.5 V

6E4

3E2

200

10 ms

106 cycles

RF-magnetron sputtering

[129]

TiO2

Pt/Pt

1E7

1E5

100

ALD

[130]

TiN/Pt

+1 V/−1.5 V

1E3

1E2

10

1 μs

104 s

104 cycles

RF-reactive sputtering

[96]

TaN–TiN/TiN–TaN

1.5 V/−1.5 V

6E3

4E3

1.5

102–103 cycles

Sputtering

[131]

Al/Al

3 V/−2 V

1E6

1E4

100

104 s

100 cycles

Plasma-enhanced

ALD

[132]

LaO

ITO/SrTiO3

5 V/−1.6 V

200

>4 × 104 s

2000 cycles

Pulsed laser deposition

[133]

TaOx

Pt/Pt

10 years at 85 °C

109 cycles

Sputtering

[134]

W/Pt

>10 years

104 cycles

RF-magnetron sputtering

[135]

NiO

Pt/Pt

>10 V/≤10 V

>104 s

Pulsed laser deposition

[136]

Au/Au

+5.2 V/−6 V

Electrochemical plating

[94]

HfO2

TiN/TiN

1.5 V/−1.4 V

1E5

1E3

100

<10 ns

>500 min at 200 °C

>106 cycles

ALD

[90]

TiN/TiN

>50

5 ns

105 s at 200 °C

5 × 107 cycles

ALD

[102]

ZrO2

ITO/Ag

1 V/−1 V

~2E3

~250

~8

106 s at 27 °C

>50 cycles

Electrohydrodynamic printing

[137]

Ag/Ag

3 V/−3 V

~1E7

1E5

~100

Electrohydrodynamic printing

[138]

TiN/Pt

0.8 V/−0.5 V

104 s at 27 °C

103 cycles

RF-magnetron sputtering

[139]

CeO2

Au/Au

2.4 V/−3 V

1E7

1E3

1E4

Sol-gel (drop-coating)

[140]

AlOx

Al or CNT/CNT

105 s

104 cycles

ALD

[141]

Cu/W

1.3 V/−0.05 V

5E6

1E4

500

103 s

E-beam evaporation

[142]

Al2O3

Ti/Pt

1.4 V/−1.7 V

<1000

10 ns

104 s

RF-magnetron sputtering

[143]

Cu2O/CuO

Pt//Nb-STO

1E8

1E3

1E5

Plasma assisted molecular beam epitaxy

[144]

GdOx

Cr/TiN

<+4 V/−4 V

5E5

5E3

100

3 × 104 s

105 cycles

E-beam evaporation

[145]

MnO

Ti/Pt

0.7 V/−1.1 V

104 s at 85 °C

105 cycles

RF-reactive sputtering

[146]

“–”: data not found in the associated reference paper

Table 1.2

Examples of bipolar mixed metal-oxide memristors and their operational characteristics

Material

TE/BE

VSET/VRESET

Roff (Ω)

Ron (Ω)

ΔR = Roff /Ron

Switching speed

Retention Time

Endurance

Fabrication process

References

Cu-doped SiO2 bipolar-unipolar

Cu/W

0.9 V/−0.75 V

1E6

1E3

1E3

5 × 104 s

107 cycles

E-beam evaporation

[147]

Cu-doped ZrO2 Bipolar-Unipolar

Au–Cu/Pt–Ti

3.6 V/−1.5 V

3E8

3E2

1E6

50 ns (Reset → Set)

100 ns

(Set → Reset)

104 s

Thermal evaporation

[98]

ZnO1–x/ZnO bilayer structure

Pt/Pt

1.5 V/−0.6 V

1E4

1E2

1E2

>104 s

100 cycles

Sol-gel

[148]

ZnO/NiO

Au/n-Si

8 V/−8 V

Ultrasonic spray pyrolysis

[95], [99]

ZnO/ZnWOx bilayer structure

Pt/W

0.8 V/−0.6 V

6E3

90

67

>200 cycles

Sputtering

[149]

ZTO

Al/Pt

0.25 V/−0.85 V

1E6

1E3

1E3

>104 s

>50 cycles

Sol-gel (spin coating)

[150]

TiO2/CuxO

Ti/Cu

2.5 V/−1 V

50 ns

up to 30 h

Electrochemical deposition

[151]

HfLaOx

TaN/Pt

2.27 V/−1.81 V

1E9

1E3

1E6

10 ns

104 s at 27 °C

104 cycles

ALD

[152]

MgO/CoOx

Pt/Au

15 V/−3 V

1E12

1E10

1E2

>102 s

108 cycles

Pulsed laser deposition

[153]

WSiOx

Pt/TiN

2 V/−2 V

105 s at 250 °C

105 cycles

RF-magnetron sputtering

[154]

WSiOx/WSiON

Pt/TiN

2E4

2E2

1E2

108 cycles

RF-magnetron sputtering

[155]

Pt-dispersed SiO2

Pt/Ta

<100 ps

>6 months

>3 × 107 cycles

RF-magnetron sputtering

[156]

Au doped HfO2

Cu/Pt

0.34 V/−0.9 V

1E2

10

1E2

RF-reactive sputtering

[157]

TiOx/HfO2

TiN/TiN

1.5 V/−1.4 V

>1000

5 ns

10 years at 200 °C

>106 cycles

ALD

[90]

AlHfO2/Cu

Cu/n + Si

4 V/−6 V

1E7

1E4

1E3

104 s

RF-magnetron sputtering

[158]

AlCu/HfO2

TiN/TiN

<1 V /≥1 V

<50 ns

3 × 104 at 85 °C

105 cycles

ALD

[85]

AlOx/TaOx

W/TiN

>10 years at 85 °C

106 cycles

E-beam evaporation

[159]

AlOx/WOx

Al/W

1.4 V/−0.8 V

104 s

Rapid thermal oxidation (RTO)

[97]

Nitrogen doped WOx

Ti/Pt

2 V/−2 V

104 s

>102 cycles

RF-reactive sputtering

[99]

“–”: data not found in the associated reference paper

Table 1.3

Examples of unipolar metal-oxide memristors and their operational characteristics

Material

TE/BE

VSET/VRESET

ΔR = Roff /Ron

Switching speed

Retention time

Endurance

Fabrication process

References

CoOx

Pt/Pt

104 s

103 cycles

RF-sputtering

[160]

Co3O4

Pt/Pt

1.9 V/−0.52 V

1 × 104 = 5×106/5 × 103

Cold pressing

[161]

CuOx

Al/Cu

–/0.7 V

104 cycles

Electrochemical plating

[162]

Gd2O3

Ti/Pt

2.5 V/1.2 V

102 cycles

Pulsed laser deposition

[163]

NiO

Nobel Metals

2 × 107 s

1012 cycles

RF-sputtering or plasma oxidation

[164]

SnO2

Pt, Au,TI/Pt

1.5–2 V /0.5–1 V

104 s

102 cycles

Pulsed laser deposition

[165]

HfO2

Ni/TiN

102 cycles

ALD

[55]

WOx

TiN/W

>50 ns

104 s at 100 °C

107 cycles

Rapid thermal oxidation

[166]

Ti- embedded ZrO2

Ti/Pt

-1.2 V/−0.7 V

105 s

103 cycles

RF-sputtering

[167]

“–”: data not found in the associated reference paper

1.7 Prospective Applications

Application areas of memristor devices are numerous owing to their versatile nature in terms of elementary design structure, their CMOS fabrication compatibility along with their superior operational characteristics in terms of switching speed, retention rate, and endurance. One of the promising uses of memristor devices is “non-volatile memory” for computing. Table 1.4 summarizes some of the key parameters of existing commercial memory technologies and emerging ones [112]. As can be seen from the table, a memristor has the density of the dynamic random access memory (DRAM) and the speed of the static random access memory (SRAM) which makes it ideal for universal and content addressable memory (CAM) type memory [113]. The non-volatile nature of memristor also enables the zero-leakage power for memory and can be used as part of power management unit in wireless sensor nodes [114, 115]. Memristor devices can also be used for analog applications including programmable analog circuits, analog filters, oscillators, and chaotic analog circuits [116, 117]. In particular, the introduction of memristor technology could help increase the linear range of analog amplifier circuits as opposed to traditional setups [113, 114, 118]. Memristor devices also have potential uses in digital logic applications supporting in-memory computing [119, 120]. While analog systems are constructed with memristors having continuous resistance change, digital applications require stable discrete resistance state [49]. One of the most promising digital applications of memristor devices is as field-programmable gate array (FPGA) [121]. A discrete FPGA architecture was reported by Cong et al. [122] where interconnections are designed only by memristors and show a reduction of up to 5.5 times and 1.6 times, respectively, on achievable device area and power requirement. Current developments are also being projected toward neuromorphic applications to span the cognitive computing [123, 124, 125]. In typical area, the memristor would be implemented as an electronic synapse, where it could mimic the electrical response of the elementary structures in the human brain, allowing for replacement of defected neurons. Until now, several non-volatile technologies have been tested as electronic synapse, such as RRAM ferroelectric tunneling junctions (FTJs) and magnetic tunnel junctions (MTJs) [123]. To date, RRAM is the most reliable technology owing to its famous operation characteristics [126].
Table 1.4

Key specifications of state-of-the-art commercial memory technologies versus transpiring memristor device

 

Available commercial technologies

Transpiring technology

 

DRAM

Flash (NAND)

Flash (NOR)

SRAM

Memristor

Cell density (F2)

6–30

1–4

1–10

140

4

Retention time

>64 ms

>10 yrs

>10 yrs

as long as voltage is applied

>10 yrs

Endurance

>1016 cycles

>105 cycles

105 cycles

>1016 cycles

>1012 cycles

Read time

2 ns

0.1 ms

15 ns

0.1–0.3 ns

<2 ns

Feature size

36 nm

16 nm

45 nm

45 nm

<5 nm

Device cell element

ITIC

1T

1T

6T

1R/1T1R

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© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Khalifa University of Science and TechnologyAbu DhabiUnited Arab Emirates

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