Low Resistance State Research Articles

Investigation of Indium doped Se-Te bulk chalcogenide glasses for electrical switching and phase changing applications

Recently, Metal-doped Se-Te chalcogenides have gained a lot of interest due to their unique capacity for electrical switching, which makes them desirable for electronic applications. This study examines the electrical switching characteristics of bulk Se86−xTe14Inx (0 ≤ x ≤ 6) amorphous alloys produced by the conventional melt-mix-quench process. The samples with an Indium atomic percentage between 2 to 6 exhibited a remarkable transition from a highly resistive to a low resistive state when subjected to an electric field with a current of 1 mA, displaying quick and reversible switching behaviour. The threshold voltage (Vth) significantly dropped from 410.6 V to 49.2 V with an increase in Indium concentration. Additionally, above the specific current threshold, these bulk glasses demonstrated memory-type switching, demonstrating their potential for data storage applications. To comprehend the trend of glass forming ability, thermal stability range and Hruby’s glass stability parameters, with their compositional dependency, Differential Scanning Calorimetry (DSC) was utilized. The sample Se80Te14In6 emerged to be the fastest phase-changing material, with a memory switching current threshold of Ith = 1.3 mA and a threshold voltage value of 49.2 V. To study the formation of crystallites in Se-Te-In alloy, X-ray diffraction patterns of pristine glass and the annealed sample were examined. Furthermore, temperature-dependent conductivity investigations showed a sharp rise in conductivity once the process crystallization begins (Tx), and also the threshold voltage (Vth) of the samples decreased linearly with rising temperature. Overall, this study provides valuable insights into the electrical switching behaviour and thermal properties of Se-Te-In chalcogenide glasses, enhancing their suitability in electronic devices.

Electric-Field Control of Perpendicularly Magnetized Ferrimagnetic Order and Giant Magnetoresistance in Multiferroic Heterostructures.

Electrical control of magnetism is highly desirable for energy-efficient spintronic applications. Realizing electric-field-driven perpendicular magnetization switching has been a long-standing goal, which, however, remains a major challenge. Here, electric-field control of perpendicularly magnetized ferrimagnetic order via strain-mediated magnetoelectric coupling is reported. We show that the gate voltages isothermally toggle the dominant magnetic sublattice of the compensated ferrimagnet FeTb at room temperature, showing high reversibility and good endurance under ambient conditions. By implementing this strategy in FeTb/Pt/Co spin valves with giant magnetoresistance (GMR), we demonstrate that the distinct high and low resistance states can be selectively controlled by the gate voltages with assisting magnetic fields. Our results provide a promising route to use ferrimagnets for developing electric-field-controlled, low-power memory and logic devices.

Ultralow Voltage Resistive Switching in Hafnium–Zirconium Oxide

AbstractUltralow SET and RESET voltage are essential for high‐density, low‐power, and small heat dissipation nonvolatile random‐access memory (NVRAM) elements. A nanoscale polycrystalline Hf0.75Zr0.25O2 (HZO) thin films on Pt/Si substrate are fabricated and investigated for suitability for bipolar resistive switching. The device illustrates monoclinic and tetragonal/orthorhombic phases with weak ferroelectricity and robust resistive switching. Small remanent polarization (≈0.1 μC cm−2) may assist in the height reduction of barrier height and ease the electron for transport. Remarkably, the Al/HZO/Pt/Si device, consisting of thin films with 10 and 5 nm thicknesses, exhibits a switching voltage below −30 mV from a low‐resistance state (LRS) to a high‐resistance state (HRS). It shows a significant ROFF/RON ratio of 106, making it suitable for low power consumption and minimal heat dissipation devices. Moreover, the utilization of an ultrathin film (5 nm) results in an improved reduction (< 0.7 V) of the operating window at the positive voltage. Direct tunneling and the Fowler–Nordheim tunneling model are performed in current–voltage (I–V) data to study the charge transportation behavior over a trapezoidal and triangular potential barrier. These results of the HZO candidate may stimulate the futuristic nonvolatile resistive random‐access memory (ReRAM) in the optoelectronic industry.

A carbon conductive filament-induced robust resistance switching behavior for brain-inspired computing.

Memristors have revolutionized the path forward for brain-inspired computing. However, the instability of the nucleation process of conductive filaments based on active metal electrodes leads to the discrete distribution of switching parameters, which hinders the realization of high-performance and low-power devices for neuromorphic computing. In response, a carbon conductive filament-induced robust memristor is demonstrated with variation coefficients as low as 3.9%/-1.18%, a threshold power as low as 10-9 W, and 3 × 106 s retention and 107 cycle endurance behaviors can be maintained. The recognition accuracy for Modified National Institute of Standards and Technology (MNIST) handwriting is as high as 96.87%, attributed to the high linearity of the iterative updating of synaptic weights. The demodulation and storage functions of the American Standard Code for Information Interchange (ASCII) are demonstrated by programmable pulse modulation. Notably, the transmission electron microscopy (TEM) images allow the observation of carbon conductive filament paths formed in the low resistance state. First-principles calculations analyze the energetics of defects involved in the diffusion of carbon atoms into MoTe2 films. This work presents a novel guideline for studying memristor-based neuromorphic computing.

An in-sensor humidity computing system for contactless human-computer interaction.

Being capable of processing large amounts of redundant data and decreasing power consumption, in-sensor computing approaches play significant roles in neuromorphic computing and are attracting increasing interest in perceptual information processing. Herein, we proposed a high performance humidity-sensitive memristor based on a Ti/graphene oxide (GO)/HfOx/Pt structure and verified its potential for application in remote health management and contactless human-machine interfaces. Since GO possesses abundant hydrophilic groups (carbonyl, epoxide, and hydroxyl), the memristor shows a high humidity sensitivity, fast response, and wide response range. By utilizing the proton-modulated redox reaction, humidity exposure to the memristor induces a dynamic change in the switching between high and low resistance states, ensuring essential synaptic learning functions, such as paired-pulse facilitation, spike number-dependent plasticity, and spike amplitude-dependent plasticity. More importantly, based on the humidity-induced salient features originating from the abundant hydrophilic functional groups in GO, we have implemented a noncontact human-machine interface utilizing the respiratory mode in humans, demonstrating the potential of promoting health monitoring applications and effectively blocking virus transmission. In addition, the high recognition accuracy of contactless handwriting in a 5 × 5 array artificial neural network was successfully achieved, which is attributed to the excellent emulated synaptic behaviors. This study provides a feasible method to develop an excellent humidity-sensitive memristor for constructing efficient in-sensor computing for application in health management and contactless human-computer interaction.

Simulation of the resistance switching performance and synaptic behavior of TiO2-based RRAM devices with CoFe2O4 insertion layers.

The electrothermal coupling model of Pt/CoFe2O4/TiO2/TiN devices was established to study their resistive switching characteristics and basic biological synaptic properties in our research. The processes of set and reset are simulated, and the distribution of the temperature, the electric field and the concentration of oxygen vacancies in the dielectric layer are obtained. The switching performance of the TiO2-based device is significantly improved after the CoFe2O4 layer is inserted, with the switching voltage, working current and power consumption being reduced, while the switching ratio is increased. By changing the thermal conductivity of the top electrode, the rupture position of the conductive filament can be controlled. The I-V characteristics of the Pt/CoFe2O4/TiO2/TiN device during the reset and set processes are fitted linearly in logarithmic coordinates, and the ohmic conduction mechanism or the space-limited charge conduction mechanism is mainly satisfied in the high and low resistance states. Finally, the application of dual-layer devices on biological synapses is studied, and the basic biological characteristics of enhancement, inhibition and paired pulse promotion are simulated successfully. In addition, the redox reaction induced by oxygen vacancy migration also promotes the formation and rupture of the conductive filament. Results of the study show this ferrite material as an insertion layer in a resistive random-access memory structure that offers potential for future information storage and bioneuromorphic computation devices.

Solution-processed PEDOT: PSS/PVA polymer blend write-once-read-many memory devices

In this work, all-solution-processed resistive switching memory devices in a polymer blend are realised. The memory, in this work, is Write-Once-Read-Many memory (WORM). The polymer blend is the blend of Poly(3,4-ethylenedioxythiophene) Polystyrene Sulfonate (PEDOT: PSS) and Polyvinyl Alcohol (PVA). The devices can sustain 50 bending cycles at a bending radius of 0.5mm, while still able to maintain and perform memory functions. The mechanism of the switching can be attributed to electrochemical properties of the polymers. The migrations of polymers (PEDOT: PSS/PVA blend) and electrolysis of the absorbed water distort the conducting pathways and switch the state of the device from a low resistance state (LRS) to a high resistance state (HRS). The work may pave the way for future low cost flexible electronic memory devices. Flexible memory devices

Conformational transitions in redissolved silk fibroin films and application for printable self-powered multistate resistive memory biomaterials.

3D printing of water stable proteins with elastic properties offers a broad range of applications including self-powered biomedical devices driven by piezoelectric biomaterials. Here, we present a study on water-soluble silk fibroin (SF) films. These films were prepared by mixing degummed silk fibers and calcium chloride (CaCl2) in formic acid, resulting in a silk I-like conformation, which was then converted into silk II by redissolving in phosphate buffer (PBS). Circular dichroism, Raman and infrared (IR) spectroscopies were used to investigate the transitions of secondary structure in silk I and silk II as the pH of the solvent and the sonication time were changed. We showed that a solvent with low pH (e.g. 4) maintains the silk I β-turn structure; in contrast solvent with higher pH (e.g. 7.4) promotes β-sheet features of silk II. Ultrasonic treatment facilitates the transition to water stable silk II only for the SF redissolved in PBS. SF from pH 7.4 solution has been printed using extrusion-based 3D printing. A self-powered memristor was realized, comprising an SF-based electric generator and an SF 3D-printed memristive unit connected in series. By exploiting the piezoelectric properties of silk II with higher β-sheet content and Ca2+ ion transport phenomena, the application of an input voltage driven by a SF generator to SF 3D printed holey structures induces a variation from an initial low resistance state (LRS) to a high resistance state (HRS) that recovers in a few minutes, mimicking the transient memory, also known as short-term memory. Thanks to this holistic approach, these findings can contribute to the development of self-powered neuromorphic networks based on biomaterials with memory capabilities.

Spike rate dependent synaptic characteristics in lamellar, multilayered alpha-MoO3 based two-terminal devices - efficient way to control the synaptic amplification.

Brain-inspired computing systems require a rich variety of neuromorphic devices using multi-functional materials operating at room temperature. Artificial synapses which can be operated using optical and electrical stimuli are in high demand. In this regard, layered materials have attracted a lot of attention due to their tunable energy gap and exotic properties. In the current study, we report the growth of layered MoO3 using the chemical vapor deposition (CVD) technique. MoO3 has an energy gap of 3.22 eV and grows with a large aspect ratio, as seen through optical and scanning electron microscopy. We used transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy for complete characterisation. The two-terminal devices using platinum (Pt/MoO3/Pt) exhibit superior memory with the high-resistance state (HRS) and low-resistance state (LRS) differing by a large resistance (∼MΩ). The devices also show excellent synaptic characteristics. Both optical and electrical pulses can be utilised to stimulate the synapse. Consistent learning (potentiation) and forgetting (depression) curves are measured. Transition from long term depression to long term potentiation can be achieved using the spike frequency dependent pulsing scheme. We have found that the amplification of postsynaptic current can be tuned using such frequency dependent spikes. This will help us to design neuromorphic devices with the required synaptic amplification.

Schottky barrier reduction on optoelectronic responses in heavy ion irradiated WSe2 memtransistors.

Two-dimensional transition metal dichalcogenide-based memtransistors provide simulation, sensing, and storage capabilities for applications in a remotely operated aerospace environment. Swift heavy ion (SHI) irradiation technology is a common method to simulate the influences of radiation ions on electronic devices in space environments. Here, SHI irradiation technology under different conditions was utilized to produce complex defects in WSe2-based memtransistors. Low-resistance state to low-resistance state (LRS-LRS) switching behaviors under light illumination were achieved and photocurrent responses with different spike trains were observed in SHI-irradiated memtransistors, which facilitated the design of devices with enriched analog functions. Reduction of the Schottky barrier height due to the introduced defects at the metal/WSe2 interface was confirmed to be the major factor responsible for the observed behaviors. 1T phase and concentric circle-type vacancies were also created in the SHI-irradiated 2H-WSe2 channel besides the amorphous structure; these complex defects could seriously affect the transport properties of the devices. We believe that this work serves as a foundation for aerospace radiation applications of all-in-one devices. It also opens a new application field of heavy ion irradiation technology for the development of multiterminal memtransistor-based optoelectronic artificial synapses for neuromorphic computing.

Kinetic Monte Carlo simulation analysis of the conductance drift in Multilevel HfO2-based RRAM devices.

The drift characteristics of valence change memory (VCM) devices have been analyzed through both experimental analysis and 3D kinetic Monte Carlo (kMC) simulations. By simulating six distinct low-resistance states (LRS) over a 24-hour period at room temperature, we aim to assess the device temporal stability and retention. Our results demonstrate the feasibility of multi-level operation and reveal insights into the conductive filament (CF) dynamics. The cumulative distribution functions (CDFs) of read-out currents measured at different time intervals provide a comprehensive view of the device performance for the different conductance levels. These findings not only enhance the understanding of VCM device switching behaviour but also allow the development of strategies for improving retention, thereby advancing the development of reliable nonvolatile resistive switching memory technologies.

Control of positive and negative photo- and thermal-responses in a single PbI2@CH3NH3PbI3 micro/nanowire-based device for real-time sensing, nonvolatile memory, and logic operation.

CH3NH3PbI3 has shown great potential for photodetectors and photovoltaic devices due to its excellent positive response to visible light. However, its real-time response characteristics hinder its application in optical memory and logic operation; moreover, the presence of excessive PbI2 is a double-edged sword. Herein, we constructed a dual-terminal device using a single CH3NH3PbI3 micro/nanowire with two Ag electrodes, and then in situ introduced PbI2 quantum dots (QDs) as hole trap centres by thermal decomposition at 160 °C. An anomalous negative photoconductivity (NPC) effect for sub-bandgap light below the PbI2 bandgap is obtained. Importantly, an electrically erasable nonvolatile photomemory can be realized. Furthermore, the device also exhibits an abnormal positive thermal resistance (PTR)-related thermomemory effect, and the thermal-induced high-resistance state (HRS) can be erased by a large bias or an illumination of 365 nm super-bandgap UV light. Additionally, logical "OR" gate operations are achieved through a combination of 650 nm sub-bandgap light and a 70 °C temperature-induced HRS, as well as a large bias and 365 nm super-bandgap light-triggered low-resistance state. These effects are attributed to the excitation and injection of holes in QDs and structural defect traps. This multifunctional device, integrating real-time sensing, nonvolatile memory, and logical operation, holds significant potential for novel electronic and optoelectronic applications.

Elucidating dynamic conductive state changes in amorphous lithium lanthanum titanate for resistive switching devices

Exploration of novel resistive switching materials attracts attention to achieve neuromorphic computing that can surpass the limit of the current Von-Neumann computing for the time of Internet of Things (IoT). Battery materials priorly used to serve as an electrode or electrolyte have demonstrated metal-insulator transitions upon an electrical biasing due to resulting compositional change, which is desirable property for future resistive switching devices. For example, it has been suggested that solid-state electrolyte amorphous lithium lanthanum titanate (a-LLTO) changes in electronic conductivity depending on oxygen content. In this work, switching behavior of a-LLTO was investigated at both bulk- and nano-scale by employing a range of voltage sweep techniques, ultimately establishing a stable and optimal operating condition within the voltage window of − 3.5 V to 3.5 V. This voltage range effectively balances the desirable trait of a substantial resistance change by three orders of magnitude with the imperative avoidance of LLTO decomposition. Experiment and computation with different LLTO composition shows that LLTO has two distinct conductivity states due to Ti reduction. The distribution of these two states is discussed using simplified binary model, implying the conductive filament growth during low resistance state. Consequently, our study deepens understanding of LLTO electronic properties and encourages the interdisciplinary application of battery materials for resistive switching devices.

Self-Healing, Laminated, and Low Resistance NH3 Sensor Based on 6,6',6″-(Nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) Sensing Material Operating at Room Temperature.

With the rapid development of the concept of the Internet of Things (IoT), gas sensors with the function of simulating the human sense of smell became irreplaceable as a key element. Among them, ammonia (NH3) sensors played an important role in respiration tests, environmental monitoring, safety, and other fields. However, the fabrication of the high-performance device with high stability and resistance to mechanical damages was still a challenge. In this work, polyurethane (PU) with excellent self-healing ability was applied as the substrate, and the sensor was designed from new sensitive material design and device structure optimization, through applying the organic molecule with groups which could absorb NH3 and the laminated structure to shorten the electronic transmission path to achieve a low resistance state and favorable sensing properties. Accordingly, a room temperature flexible NH3 sensor based on 6,6',6″-(nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) (TPA-3DCNPZ) was successfully developed. The device could self-heal by means of a thermal evaporation assisted method. It exhibited a detection limit of 1 ppm at 98% relative humidity (RH), as well as great stability, selectivity, bending flexibility, and self-healing properties. The improved NH3 sensing performance under high RH was further investigated by complex impedance plots (CIPs) and density functional theory (DFT), attributing to the enhanced adsorption of NH3. The TPA-3DCNPZ based NH3 sensors proved to have great potential for application on simulated exhaled breath to determine the severity of kidney diseases and the progress of treatment. This work also provided new ideas for the construction of high-performance room temperature NH3 sensors.

Cobalt sulfide films by sulfurizing cobalt for resistive switching memory

A cobalt sulfide (CoS x ) film compromising CoS2 and Co9S8 nanograins was formed by sulfurizing the surface of a Co film to use for resistive switching (RS) memory. The work function and band gap of the CoS x film were measured to be 4.78 eV and 2.18 eV, respectively. The CoS x film was used as a resistive layer together with the Co film underneath as a bottom electrode, and a Ag or Cu film as the top electrode. Both Ag/CoS x /Co and Cu/CoS x /Co devices exhibited bipolar RS behavior with the capability of multi-level memory storage. The conduction of both devices in low resistive states was correlated with metallic filamentary paths following ohmic conduction, whereas Schottky emission originated at the Ag/CoS x and Cu/CoS x interfaces dominated in the high resistance state. The performance of Ag/CoS x /Co and Cu/CoS x /Co devices were compared and correlated with the properties of Ag and Cu electrodes.

Multibit, Lead‐Free Cs2SnI6 Resistive Random Access Memory with Self‐Compliance for Improved Accuracy in Binary Neural Network Application

AbstractIn the realm of neuromorphic computing, integrating Binary Neural Networks (BNN) with non‐volatile memory based on emerging materials can be a promising avenue for introducing novel functionalities. This study underscores the viability of lead‐free, air‐stable Cs2SnI6 (CSI) based resistive random access memory (RRAM) devices as synaptic weights in neuromorphic architectures, specifically for BNNs applications. Herein, hydrothermally synthesized CSI perovskites are explored as a resistive layer in RRAM devices either on the rigid or flexible substrate, highlighting reproducible multibit switching with self‐compliance, low‐ resistance‐state (LRS) variations, a decent On/Off ratio(or retention) of ≈103(or 104 s), and endurance exceeding 300 cycles. Moreover, a comprehensive evaluation with the 32 × 32 × 3 RGB CIFAR‐10 dataset reveals that binary convolutional neural networks (BCNN) trained solely on binary weight values can achieve competitive rates of accuracy comparable to those of their analog weight counterparts. These findings highlight the dominance of the LRS for CSI RRAM with self‐compliance in a weighted configuration and minimal influence of the high resistance state despite substantial fluctuations for flexible CSI RRAM under varying bending radii. With its unique electrical switching capabilities, the CSI RRAM is highly anticipated to emerge as a promising candidate for embedded AI systems, especially in IoT devices and wearables.

Multi-factors-regulated multi-level down-scalable and robust memristors

The memristor based on resistive switching (RS) behavior has attracted extensive attention due to its wide application prospects in artificial intelligence (AI) and information memory. In this work, a multi-factor responsive memristor based on Ag/MnO2/F-doped tin oxide (FTO) sandwich structure was fabricated by magnetic sputtering method. It was found that the RS behavior of the device was significantly improved when the diameter of the top electrode decreased from 2.0 mm to 0.5 mm, indicating that the device with Ag/MnO2/FTO structure has the down-scalable potential. Through comprehensive research, it can be concluded that the bipolar RS behavior of the memristor can be adjusted by multi-factors such as active layer thickness, top electrode size, voltage scanning rate, bias voltage amplitude and temperature. Specifically, the resistance-temperature dependence and temperature coefficient of the device in the low resistance state (LRS) indicate that the formation and disconnection of metallic Ag conductive filaments (CFs) play an important role in the RS behavior of the memristive device. Therefore, this work will lay an experimental and theoretical foundation for comprehensively understanding the mechanism of RS behavior and developing high-performance memristor with multi-level memory capacity.

Fabrication of ZnO-encapsulated porous alumina structure utilizing a two-step anodizing technique for memristor applications

Highly ordered porous alumina thin films with various aspect ratios were fabricated by a two-step anodizing technique. The dependence of the high resistance state to low resistance state ratio on the aspect ratio of the pores was observed in the memristors utilizing porous alumina. The reduction of threshold voltage and improvement in stability were achieved by properly encapsulating i-ZnO inside the porous alumina as the switching medium. A significant improvement in the ratio of high resistance state to low resistance state was achieved by i-ZnO encapsulation in porous alumina compared to the conventional planer switching layer of ZnO alone.

Vliyanie shuma na rezistivnoe pereklyuchenie memristora na osnove stabilizirovannogo dioksida tsirkoniya

The effect of Gaussian noise on the switching of a ZrO2(Y) based memristor from the low resistance state (LRS) into the high resistance state (HRS) including transitions from the LRS into intermediate metastable states has been studied. The series of positive (with addition of the noise signal or without the one) and negative rectangular voltage pulses were used as the switching signals. The adding of noise to the switching signal initiated the switching of the memristor from the LRS into the HRS at smaller pulse magnitudes than in the case of switching by the rectangular pulses without adding the noise. A necessary (preset) HRS can be achieved passing the intermediate states by adding the noise with certain parameters to the rectangular switching pulses. The resistive switching is performed without application of adaptive switching protocols. The results of the present study can be applied in the development of innovative memristor switching protocols.

Nitrogen-doped carbon nanotubes for self-powered memristive systems

Memristive devices are one of the promising candidates for creating neuromorphic systems due to the possibility of multilevel switching, low operating voltages and high scalability. However, as with any passive element, the memristor requires an external bias voltage to operate, which requires the inclusion of a power source in the circuit. In this regard, of great interest are works on the creation of self-powered memristive systems consisting of connecting in series a memristor and a nanogenerator that converts the energy of the external environment into electrical energy [1, 2]. Such a memristive system has a high potential for applications in aerospace and implantable electronics. At the moment, the first self-powered memristive and sensor systems based on metal oxides and piezoelectric nanogenerators (PENG) have already been developed [2]. The main problems in this area are to reduce the size of the nanogenerator and to match the output parameters of the nanogenerator and the input parameters of the memristor. In the framework of this work, these problems are being resolved by creating a self-powered memristive system based on nitrogen-doped carbon nanotubes (N-CNTs). Previously, we studied the memristive properties of N-CNTs and showed that nanotubes demonstrate reproducible multilevel switching with a resistance ratio in the high- and low-resistance states (HRS/LRS) of about 4⋅105 [3, 4]. It was found that the memristive effect in N-CNTs is due to the incorporation of nitrogen atoms into the nanotube structure and the formation of an internal piezoelectric field [4]. As part of further studies, it was found that an array of vertically aligned N-CNTs is a promising material for creating PENG: the generated output voltage is hundreds of mV and the current generated by single nanotube reaches hundreds of nA [5]. The results obtained allow us to speak about the possibility of developing a self-powered memristive system by connecting in series a memristor and PENG based on N-CNTs. To optimize the output characteristics of the PENG, in particular, the amplitude of the generated voltage, and the input switching voltage of the N-CNT-based memristor, studies were carried out to increase the piezoelectric response and reduce the switching voltage of the N-CNT resistance by changing the concentration of the dopant nitrogen in the nanotube growth process. It was found that it is necessary to grow N-CNTs with a doping nitrogen concentration of up to 12% and a high aspect ratio of length to diameter (more than 60) to create PENG with an output voltage of up to 2 V. These N-CNT parameters are provided at a low growth temperature (500–550 C°) and high ratio of acetylene and ammonia flows (1:5 - 1:6). On the contrary, the N-CNTs with a small aspect ratio (less than 30) and doping nitrogen concentrations of 4–6% are required for the manufacture of memristors with a minimum switching voltage (about 2 V), These N-CNT parameters are provided by increasing the growth temperature to 615 C° and reduction in growth time. The obtained results can be used in the development of self-powered memristive and sensor systems based on nitrogen-doped carbon nanotubes.