Low Resistance State Research Articles

The influence of mercury vapor on the electrical resistance of chalcogenide amorphous films

Using the planar structures "Ni layer - chalcogenide amorphous film - Ni layer" and "graphite probe - chalcogenide amorphous film graphite probe" samples, the influence of mercury vapor on the electrical resistance of amorphous films of the Se-Te, Se-Sb and Se-As systems was investigated. It was established that exposure of samples in mercury vapor leads to a decrease in their electrical resistance by 4-7 orders of magnitude. As the temperature and mercury concentration increase, the transition time from a high-resistance state to a low-resistance state decreases. When introducing Te, Sb, and As into amorphous selenium and increasing their concentration in the composition of the films, the transition time increases, and the value of the change in resistance decreases. It was established that the change in resistance is mainly determined by the change in surface conductivity of chalcogenide films. A decrease in the electrical resistance of selenium-containing amorphous films modified with mercury is caused by the formation of HgSe crystalline inclusions in their matrix.

Probing the Photo-Activated Switching Dynamics of Halide Perovskite Memristors

The hysteresis effects due to electronic-ionic conductivity can be utilized to develop memory devices for information storage and brain-like computing. Halide perovskites-based devices exhibit frequent hysteresis in their current–voltage curves, making them suitable for neuromorphic computing. Despite recent advances in this field, the exact mechanism behind switching between high and low resistive states in halide perovskite memristors is still under debate. This study aims to understand the switching mechanism and charge transport in the ITO/MAPbBr3/Au device’s geometry by analyzing their SET-RESET states through current–voltage characteristics and impedance spectroscopy at different applied biases and under different light intensities. A clear shift in the SET voltage due to increased light power correlates with the electronic–ionic coupling and ion migration. In the impedance spectroscopy measurement, the AC conductivity shows a negative slope at the SET state, especially at the low-frequency regime due to the ion-induced voltage, which gets screened by photogenerated charge carriers.

Nonvolatile resistive switching in lead-free La2CoMnO6-based memory device

Dense and flat La2CoMnO6 films as the resistive switching functional layer were deposited on n-type Si substrates by sol–gel method. Excellent bipolar resistive switching performance was observed in the Au/La2CoMnO6/Si device for the first time. The high and low resistance states with a ratio of ∼105 could be maintained for more than 1.4 × 104 s and 750 cycles without significant degradation at room temperature. The bipolar resistive switching effect could be sustained within a wide temperature range of 220 K∼300 K. Electrical conduction analysis indicated that the resistive switching behavior in La2CoMnO6 films was primarily controlled by space-charge-limited current mechanism which originated from the change of oxygen vacancies. Density functional theory calculations indicated that the conductive ability of La2CoMnO6 films was promoted with increasing concentration of oxygen vacancies. Moreover, it is found that the modulation of the barrier located at the Au/La2CoMnO6 interface was responsible for the resistive switching under applied bias voltages.

Bipolar nonlinear photo-controlled thyristor with variable-resistance effect

With the advancement of artificial intelligence technology, volatile memristors emulating neurons have gained widespread attention in the field of neuromorphic computing. This paper proposes a volatile bipolar nonlinear photo-controlled thyristor (PCT) compatible with CMOS technology, providing a reference for the structural design of silicon-based neurons. Technology computer aided design (TCAD) simulation is used to analyze the variable-resistance mechanism and photoelectric effect of the device. The PCT fabricated based on the 0.18 μm Bipolar-CMOS-DMOS (BCD) process has two electrode ports. When a fixed amplitude bipolar periodic excitation signal is applied to the anode of the device, the output current and voltage of PCT show nonlinear changes at the same time due to the negative differential resistance effect, satisfying the fundamental requirements of an oscillatory neuron. By further coupling the photoelectric effect, the device can achieve continuous switching from high-resistance state to low-resistance state under light source driving conditions. Finally, the transient data of PCT is extracted and the hysteresis loop is fitted, which verifies the accuracy of the device theory and model simulation.Index Terms—CMOS technology, variable-resistance effect, photoelectric effect, TCAD simulation.

Enhanced Synaptic Characteristics under Applied Magnetic Field in V2O5/NiMnIn-Based Switching Device for Neuromorphic Computing

The present study reports a memory structure Al/V2O5/NiMnIn on a flexible stainless steel (SS) substrate for neuromorphic applications. The fabricated device exhibits gradual SET and RESET switching characteristics with an OFF/ON resistance ratio of ∼100, good consistency of 4500, and excellent data retention capability up to 3000 s. The current–voltage (I–V) study supports an Ohmic conduction mechanism in the low-resistance state (LRS). In contrast, the trap-controlled modified space charge conduction mechanism demonstrated the high-resistance state (HRS). The resistance vs temperature measurement (R–T) in the LRS and HRS of the device signifies that oxygen vacancies form the conduction filament. We further analyze the synaptic functioning by applying identical consecutive voltage pulses, and the device’s conductance change has been observed. These characteristics show a good representation of the biological memory synapse in terms of the artificial memory device. Long-term potentiation (LTP) and long-term depression (LTD) show nonlinear and asymmetry behavior, which is substantial for neuromorphic applications. A considerable shift in LTP and LTD was detected by applying external temperature and magnetic field. This is explained via temperature and magnetic field strain in the functional NiMnIn bottom electrode of the fabricated device. The mechanical flexibility of the memory structure was tested by exploring the switching characteristics with various bending angles and bending cycles. Therefore, the present study offers new avenues for flexible devices with high data storage capability for futuristic neuromorphic applications.

Linear and symmetric synaptic weight update characteristics by controlling filament geometry in oxide/suboxide HfOx bilayer memristive device for neuromorphic computing

Memristive devices have been explored as electronic synaptic devices to mimic biological synapses for developing hardware-based neuromorphic computing systems. However, typical oxide memristive devices suffered from abrupt switching between high and low resistance states, which limits access to achieve various conductance states for analog synaptic devices. Here, we proposed an oxide/suboxide hafnium oxide bilayer memristive device by altering oxygen stoichiometry to demonstrate analog filamentary switching behavior. The bilayer device with Ti/HfO2/HfO2−x(oxygen-deficient)/Pt structure exhibited analog conductance states under a low voltage operation through controlling filament geometry as well as superior retention and endurance characteristics thanks to the robust nature of filament. A narrow cycle-to-cycle and device-to-device distribution were also demonstrated by the filament confinement in a limited region. The different concentrations of oxygen vacancies at each layer played a significant role in switching phenomena, as confirmed through X-ray photoelectron spectroscopy analysis. The analog weight update characteristics were found to strongly depend on the various conditions of voltage pulse parameters including its amplitude, width, and interval time. In particular, linear and symmetric weight updates for accurate learning and pattern recognition could be achieved by adopting incremental step pulse programming (ISPP) operation scheme which rendered a high-resolution dynamic range with linear and symmetry weight updates as a consequence of precisely controlled filament geometry. A two-layer perceptron neural network simulation with HfO2/HfO2−x synapses provided an 80% recognition accuracy for handwritten digits. The development of oxide/suboxide hafnium oxide memristive devices has the capacity to drive forward the development of efficient neuromorphic computing systems.

Comparative analysis of low-frequency noise based resistive switching phenomenon for filamentary and interfacial RRAM devices

We investigate the low-frequency noise (LFN) characteristics of resistive switching random access memory (RRAM) devices with metal–insulator–metal structures of TiN/Ti/TiO2/TiN (filamentary) and TiN/Ti/TiO2/HfO2/TiN (interfacial). By comparing filamentary and interfacial RRAM devices, we stipulate guidelines for noise sources according to the resistance states or resistive switching mechanisms of RRAM device. In filamentary RRAM devices, the dominant noise source in the low resistance state is the localized oxygen vacancies, whereas the noise characteristics in the high resistance state represent a bulk effect. In interfacial RRAM devices, the noise characteristics in both resistance states represent the bulk effect. The physical mechanism of the multilevel cell operation is inferred by the I–V characteristics in both Icc and Vreset control modes. Specifically, the changes in the structure of the conductive filament inside the switching layer can be confirmed through LFN measurement.

Electrically erasable writing properties of ZnS films by conductive atomic force microscopy

Resistive switching cycles were realized in Au/ZnS/substrate (indium–tin oxide (ITO), Cu, Si) structures, and electrically erasable writing operations were achieved in the Au/ZnS/Si structure using conductive atomic force microcopy. High-resolution transmission electron microscopy revealed that high resistance state was a mixture of amorphous and nanocrystalline state, while the frequency response of alternating current conductivity indicated that the low resistance state (LRS) was only nanocrystalline. Electric field and thermal effects contributed to the distribution of conductive defects in the ZnS film, and nearest-neighbor hopping conduction controlled the electrical resistance of the Au/ZnS/ITO structure. X-ray photoemission spectroscopy analysis of conductive defects of ZnS films in the LRS revealed that they were zinc-rich or sulfur-poor. This study confirms the intrinsic resistive switching characteristic of ZnS films, which can serve as nonoxide materials for nonvolatile memory application.

40‐4: Invited Paper: Self‐Aligned Top‐Gate Amorphous In‐Ga‐Zn‐O Thin‐Film Transistors with Hafnium‐Induced Source/Drain Regions

We demonstrated self‐aligned top‐gate (SATG) amorphous indium‐gallium‐zinc oxide (a‐IGZO) thin‐film transistor (TFT) where the source/drain (S/D) regions were induced into a low resistance state by first coating a thin hafnium (Hf) film and then performing thermal annealing in oxygen. The experimental results show that the sheet resistance of the Hf‐treated a‐IGZO layer can be as low as 408 Ω/□. The a‐IGZO TFT fabricated in the proposed processes shows excellent electrical performances, such as a field effect mobility of 16.6 cm 2 /V·s, a subthreshold swing of 0.20 V/dec, an on/off current ratio over 10 9, and high stability against electrical stress.

Resistive Switching: Physics, Devices and Applications

Resistive Switching: Physics, Devices and Applications

Successive crystallization in indium selenide thin films for multi-level phase-change memory

Increasing the storage density of phase-change memory is a challenging subject towards the universal memory commercialization. Multi-level data storage can be implemented in phase-change memory cells by designing multiple stages of crystallization of phase-change materials, which is favorable to push forward the application of phase-change memory in storage-class memory and the emerging in-memory computing. Here, the structure and properties of In2Se3 phase-change thin films with multi-level phase transitions are investigated. The In2Se3 thin films changes resistance states twice upon heating with high crystallization temperature and good thermal stability. The amorphous In2Se3 thin films undergo partial crystallization of the Se phase followed by crystallization of the γ-In2Se3 phase, with successive stages of crystallization accounting for the three distinct levels of resistivity. The phase-change memory cell based on In2Se3 thin films shows a continuous switching process of high resistance state, intermediate resistance state and low resistance state with low drift coefficient in SET-RESET operations at a speed as fast as 60 ns, and the RESET power is as low as 311 pJ, indicating that the In2Se3 thin films have good performance of three-state storage property and can effectively improve the memory density.

Performance degradation and I–V model of TiO2-film-based resistive switching memory under proton irradiation

The performance degradation of a TiO2-film-based RRAM (resistive random access memory) is investigated in a proton irradiation experiment with an energy of 25 MeV. The results reveal that the fabricated Au/TiO2 film/Ti devices exhibit typical I–V of bipolar resistive switching behavior under an irradiation of 1 × 1011 protons/cm2. The low-resistance state (LRS) resistance remains nearly constant, but the high-resistance state (HRS) resistance decreases with an increasing proton fluence. The value of the HRS resistance decreases by approximately one order of magnitude when the value of proton fluence reaches 1 × 1011 protons/cm2. Moreover, the SET voltage decreases with a decreasing proton fluence, while the RESET voltage remains almost constant. Material characterization via x-ray photoelectron spectroscopy demonstrates that the decrease in SET voltage and HRS resistance is mainly caused by radiation-induced oxygen vacancies and non-lattice oxygen. Based on the Voltage Threshold Adaptive Memristor model, a mathematical model of the I–V curve which demonstrates the variation in the RRAM resistance and voltage as a function of proton irradiation is constructed. The simulation results conformed to the experimental results under different proton fluences. Our results form a fundamental guide for the study of radiation performance degradation and radiation hardening of the RRAM with oxygen vacancy conducting filament.

SwitchX: Gmin-Gmax Switching for Energy-efficient and Robust Implementation of Binarized Neural Networks on ReRAM Xbars

Memristive crossbars can efficiently implementBinarized Neural Networks(BNNs) wherein the weights are stored in high-resistance states (HRS) and low-resistance states (LRS) of the synapses. We proposeSwitchXmapping of BNN weights onto ReRAM crossbars such that the impact of crossbar non-idealities, that lead to degradation in computational accuracy, are minimized. Essentially,SwitchXmaps the binary weights in such a manner that a crossbar instance comprises of more HRS than LRS synapses. We find BNNs mapped onto crossbars withSwitchXto exhibit better robustness against adversarial attacks than the standard crossbar-mapped BNNs, the baseline. Finally, we combineSwitchXwith state-aware training (that further increases the feasibility of HRS states during weight mapping) to boost the robustness of a BNN on hardware. We find that this approach yields stronger defense against adversarial attacks than adversarial training, a state-of-the-art software defense. We perform experiments on a VGG16 BNN with benchmark datasets (CIFAR-10, CIFAR-100 and TinyImagenet) and useFast Gradient Sign Method(ε = 0.05 to 0.3) andProjected Gradient Descent(\(\epsilon =\frac{2}{255}\)to\(\frac{32}{255},~\alpha =\frac{2}{255}\)) adversarial attacks. We show thatSwitchXcombined with state-aware training can yield upto ∼35% improvements in clean accuracy and ∼6–16% in adversarial accuracies against conventional BNNs. Furthermore, an important by-product ofSwitchXmapping is increased crossbar power savings, owing to an increased proportion of HRS synapses, which is furthered with state-aware training. We obtain upto ∼21–22% savings in crossbar power consumption for state-aware trained BNN mapped viaSwitchXon 16 × 16 and 32 × 32 crossbars using the CIFAR-10 and CIFAR-100 datasets.

Electromechanical Switching of a C60 Chain in a Nanogap

Electromechanical switching in fullerene C60 nanochains, introduced in the device as a C60 pyrrolidine tris-acid (CPTA) film, was realized in nanogap electrodes with ∼20 nm separation. Unlike microscale C60 channels, a conductive C60 chain spontaneously formed in the nanogap without electron beam irradiation. The initial current flow was likely due to electron hopping through the CPTA molecules. A higher voltage generated a nonlinear current and caused a rapid current step to drastically generate a large current flow. A further high current generated a sudden current reduction recognized as the negative differential resistance, suggesting a resistance state change from a low state to a high state. At the high-resistance state, a step-like current increase changed the nanochain conduction to the low-resistance state. The high- to low-resistance state switching was reproducible, and a sequential input voltage executed a binary resistance switching operation at room temperature. From the switching voltage and current values, the switching energy for the C60 chain in the nanogap was estimated to be approximately several milliwatts, most probably caused by the polymerization and depolymerization of the conductive C60 chain.

First-Principles Prediction of Potential Candidate Materials MCu3X4 ( M = V,Nb,Ta;X=S,Se,Te ) for Neuromorphic Computing

Inspired by the neurosynaptic frameworks in the human brain, neuromorphic computing is expected to overcome the bottleneck of traditional von Neumann architecture and be used in artificial intelligence. Here, we predict a class of potential candidate materials, $M{\mathrm{Cu}}_{3}{X}_{4}$ ($M$ = $\mathrm{V}$, $\mathrm{Nb}$, $\mathrm{Ta};\phantom{\rule{0.2em}{0ex}}X\phantom{\rule{0.25em}{0ex}}=\phantom{\rule{0.25em}{0ex}}\mathrm{S},\phantom{\rule{0.2em}{0ex}}\mathrm{Se},\phantom{\rule{0.2em}{0ex}}\mathrm{Te}$), for neuromorphic computing applications through first-principles calculations based on density-functional theory. We find that when $M{\mathrm{Cu}}_{3}{X}_{4}$ are inserted with $\mathrm{Li}$ atom, the systems would transform from semiconductors to metals due to the considerable electron filling [approximately 0.8 electrons per formula unit (f.u.)] and still maintain well-structural stability. Meanwhile, the inserted $\mathrm{Li}$ atom also has a low diffusion barrier (approximately 0.6 eV/f.u.), which ensures the feasibility to control the insertion and extraction of $\mathrm{Li}$ by gate voltage. These results establish that the system can achieve the reversible switching between two stable memory states, i.e., high or low resistance state, indicating that it could potentially be used to design synaptic transistor to enable neuromorphic computing. Our work provides inspiration for advancing the search of candidate materials related to neuromorphic computing from the perspective of theoretical calculations.

Self-Powered Phase Transition Driven by Triboelectric Nanogenerator

The phase transition of SrCoO2.5 (BM-SCO) is very popular in recent reports based on its special structure. The oxygen vacancy channel of BM-SCO provides a convenient condition for phase transformation to SrCoO3-δ (PV-SCO), with prospects in smart windows, memristive devices, and magnetic recording. The traditional method for phase transition is thermal annealing, while the electric-field-controlled ionic liquid (IL) gating is also a convenient method. Herein, we use a triboelectric nanogenerator as a self-powered system, which can provide a constant voltage for the IL and achieve ion injection to induce phase transition, and this procedure proved to be reversible. X-ray diffraction scanning and high-resolution transmission electron microscope observation showed that the crystal structures of the two phases are significantly different. Besides, BM-SCO is antiferromagnetic, PV-SCO is ferromagnetic, and the optical transmittance also changes during the phase transition. As for the applications of this film, we used IL gating to modulate the resistive switching behavior, which shows a change between high-resistance state and low-resistance state during the phase transition and can be used in resistive random access memory devices.

Resistive Switching and Current Conduction Mechanisms in Hexagonal Boron Nitride Threshold Memristors with Nickel Electrodes

AbstractThe 2D insulating material hexagonal boron nitride (h‐BN) has attracted much attention as the active medium in memristive devices due to its favorable physical properties, among others, a wide bandgap that enables a large switching window. Metal filament formation is frequently suggested for h‐BN devices as the resistive switching (RS) mechanism, usually supported by highly specialized methods like conductive atomic force microscopy (C‐AFM) or transmission electron microscopy (TEM). Here, the switching of multilayer hexagonal boron nitride (h‐BN) threshold memristors with two nickel (Ni) electrodes is investigated through their current conduction mechanisms. Both the high and the low resistance states are analyzed through temperature‐dependent current–voltage measurements. The formation and retraction of nickel filaments along boron defects in the h‐BN film as the resistive switching mechanism is proposed. The electrical data are corroborated with TEM analyses to establish temperature‐dependent current–voltage measurements as a valuable tool for the analysis of resistive switching phenomena in memristors made of 2D materials. The memristors exhibit a wide and tunable current operation range and low stand‐by currents, in line with the state of the art in h‐BN‐based threshold switches, a low cycle‐to‐cycle variability of 5%, and a large On/Off ratio of 107.

A Facile Hydrothermal Synthesis and Resistive Switching Behavior of α-Fe2O3 Nanowire Arrays.

A facile hydrothermal process has been developed to synthesize the α-Fe2O3 nanowire arrays with a preferential growth orientation along the [110] direction. The W/α-Fe2O3/FTO memory device with the nonvolatile resistive switching behavior has been achieved. The resistance ratio (RHRS/RLRS) of the W/α-Fe2O3/FTO memory device exceeds two orders of magnitude, which can be preserved for more than 103s without obvious decline. Furthermore, the carrier transport properties of the W/α-Fe2O3/FTO memory device are dominated by the Ohmic conduction mechanism in the low resistance state and trap-controlled space-charge-limited current conduction mechanism in the high resistance state, respectively. The partial formation and rupture of conducting nanofilaments modified by the intrinsic oxygen vacancies have been suggested to be responsible for the nonvolatile resistive switching behavior of the W/α-Fe2O3/FTO memory device. This work suggests that the as-prepared α-Fe2O3 nanowire-based W/α-Fe2O3/FTO memory device may be a potential candidate for applications in the next-generation nonvolatile memory devices.

Perforated Turbostratic Graphene As Active Layer in a Nonvolatile Resistive Switching Memory Device

Perforated turbostratic graphene (PTG) sheets have been synthesized from a natural waste material, dead bougainvillea bracts, using a single-step pyrolysis method, and a resistive switching (RS) memory device has been constructed with it for the very first time. Herein, the edges of these large-area multilayer graphene sheets are highly conducting due to the turbostratic stacking between the adjacent layers of the graphene sheets. These highly conducting PTG sheets embedded inside an insulating polymer matrix can act as an active layer for resistive switching memory devices. This hybrid structure shows nonlinear resistance change between two distinct resistance states by simple bias voltage variation. The trap-assisted space-charge-limited conduction can realize the high resistive state (HRS), whereas the low resistive state (LRS) takes place through direct conduction. To achieve the best performing device, a number of optimizations have been performed, like the variation of polymer matrices, variation of PTG and polymer concentration, active layer thickness variation, and top electrode area variation. The best performing device showed reproducibility of current–voltage data (>200 cycles), low power consumption (SET voltage <1 V), a high ON/OFF ratio (>104), a long retention time (>104 s), and a large number of endurance cycles (>103). High writing-read-erase-read speed and flexibility/bending cycle tests were also carried out on the best-performing device to examine its tenacity. The current PTG-based flexible RS memory device derived from a biowaste, dead bougainvillea bracts, can provide an important step toward developing green electronics.

Resistive switching performance and synaptic behavior of La-doped HfO2 thin film

Resistive random-access memory has great application prospects in developing nonvolatile memory and artificial synapse devices. In this work, lanthanum (La) doped hafnium dioxide (HfO2) (La: HfO2) thin film is fabricated by sol-gel deposition. Using gold (Au) and lanthanum nickelate (LaNiO3) as electrodes, the resistive switching performance and synaptic behavior of memristor based on La: HfO2 thin films with different doping concentrations as resistive switching layers are investigated. Current-voltage characteristics show that La-doped devices all exhibit bipolar resistive switching performance. When La doping concentration is 10%, the device shows reliable switching ratio (∼103) under 110 consecutive cycles. And the conduction mechanism of the device in high resistance state and low resistance state is analyzed by ohmic conduction and space charge limited conduction. In addition, the analog resistive switching can be obtained by increasing the voltage scanning and the result reveals that the device can be used to mimic the potentiation and depression behavior of biological synapses. Au/10% La: HfO2/LaNiO3/Si memristor effectively simulates the synaptic properties, such as long-term potentiation/depression, short-term potentiation/depression, paired-pulse facilitation and spike-time-dependent-plasticity learning rule. Furthermore, the information is classified and processed in an 8×8 pixel array. These findings will open up a unique way for the future development of nonvolatile memory and neural morphology computation.