Solid-State Synapse Based on Magnetoelectrically Coupled Memristor

Unraveling the Interplay Between Memristive and Magnetoresistive Behaviors in LaCoO3/SrTiO3 Superlattice-Based Neural Synaptic Devices

Memristors and magnetic tunnel junctions are showing great potential in data storage and computing applications. A magnetoelectrically coupled memristor utilizing electron spin and electric field-induced ion migration can facilitate their operation, uncover new phenomena, and expand applications. In this study, devices consisting of Pt/(LaCoO3/SrTiO3)n/LaCoO3/Nb:SrTiO3 (Pt/(LCO/STO)n/LCO/NSTO) are engineered using pulsed laser deposition to form the LCO/STO superlattice layer, with Pt and NSTO serving as the top and bottom electrodes, respectively. The results show that both memristive and magnetoresistive properties can coexist without any compromise in performance, and the values of ROFF/RON and tunnel magnetoresistance (TMR) ratio are both improved by ≈1000% compared to a single-period heterostructure. Notably, the Pt/(LCO/STO)5/LCO/NSTO device demonstrates superior multilevel storage performance, characterized by extended endurance, reliable retention, high ROFF/RON ratio, significant TMR ratio, and fundamental synaptic behaviors. Furthermore, density functional theory (DFT) is employed to calculate the changes in oxygen vacancies, affecting the overall energy bands and magnetic moments in the monolayer and multi-periodic structures. Simulations using the handwritten digit recognition classification achieve the highest accuracy of 94.38%. These attributes suggest that the devices hold considerable promise for application in data storage and neuromorphic computing, offering a platform for high-density neural circuits in intelligent electronic devices.

Guanine-based spin valve with spin rectification effect for an artificial memory element

Non-volatile electronic memory elements are very attractive for applications, not only for information storage but also in logic circuits, sensing devices and neuromorphic computing. Here, a ferroelectric film of guanine nucleobase is used in a resistive memory junction sandwiched between two different ferromagnetic films of Co and CoCr alloys. The magnetic films have an in-plane easy axis of magnetization and different coercive fields whereas the guanine film ensures a very long spin transport length, at 100 K. The non-volatile resistance states of the multiferroic spintronic junction with two-terminals are manipulated by a combined action of small external magnetic and electric fields. Thus, the magnetic field controls the relative orientation of the magnetization of the metallic ferromagnetic electrodes, that leads to different magnetoresistance states. The orientation and the magnitude of the electric field controls the orientation of the polarization of the guanine ferroelectric barrier, that leads to different electroresistance states, respectively. Moreover, we have observed a strong interfacial coupling of the two parameters. Consequently, positive and negative magnetoresistance hysteresis loops corresponding to spin rectification effects and non-hysteretic (erased) resistive states are manipulated with the electric field by switching the orientation of the electrical polarization of the organic ferroelectric.

Voltage-Driven Fluorine Motion for Novel Organic Spintronic Memristor

Integrating tunneling magnetoresistance (TMR) effect in memristors is a long-term aspiration because it allows to realize multifunctional devices, such as multi-state memory and tunable plasticity for synaptic function. However, the reported TMR in different multiferroic tunnel junctions is limited to 100%. This work demonstrates a giant TMR of -266% in La0.6Sr0.4MnO3(LSMO)/poly(vinylidene fluoride)(PVDF)/Co memristor with thin organic barrier. Different from the ferroelectricity-based memristors, this work discovers that the voltage-driven florine (F) motion in the junction generates a huge reversible resistivity change up to 106% with nanosecond (ns) timescale. Removing F from PVDF layer suppresses the dipole field in the tunneling barrier, thereby significantly enhances the TMR. Furthermore, the TMR can be tuned by different polarizing voltage due to the strong modification of spin-polarization at the LSMO/PVDF interface upon F doping. Combining of high TMR in the organic memristor paves the way to develop high-performance multifunctional devices for storage and neuromorphic applications.

Emerging ferroelectric materials ScAlN: applications and prospects in memristors

The research found that after doping with rare earth elements, a large number of electrons and holes will be produced on the surface of AlN, which makes the material have the characteristics of spontaneous polarization. A new type of ferroelectric material has made a new breakthrough in the application of nitride-materials in the field of integrated devices. In this paper, the application prospects and development trends of ferroelectric material ScAlN in memristors are reviewed. Firstly, various fabrication processes and structures of the current ScAlN thin films are described in detail to explore the implementation of their applications in synaptic devices. Secondly, a series of electrical properties of ScAlN films, such as the current switching ratio and long-term cycle durability, were tested to explore whether their electrical properties could meet the basic needs of memristor device materials. Finally, a series of summaries on the current research studies of ScAlN thin films in the synaptic simulation are made, and the working state of ScAlN thin films as a synaptic device is observed. The results show that the ScAlN ferroelectric material has high residual polarization, no wake-up function, excellent stability and obvious STDP behavior, which indicates that the modified material has wide application prospects in the research and development of memristors.

Epitaxial Strain Enhanced Ferroelectric Polarization toward a Giant Tunneling Electroresistance

A substantial ferroelectric polarization is the key for designing high-performance ferroelectric nonvolatile memories. As a promising candidate system, the BaTiO3/La0.67Sr0.33MnO3 (BTO/LSMO) ferroelectric/ferromagnetic heterostructure has attracted a lot of attention thanks to the merits of high Curie temperature, large spin polarization, and low ferroelectric coercivity. Nevertheless, the BTO/LSMO heterostructure suffers from a moderate FE polarization, primarily due to the quick film-thickness-driven strain relaxation. In response to this challenge, we propose an approach for enhancing the FE properties of BTO films by using a Sr3Al2O6 (SAO) buffering layer to mitigate the interfacial strain relaxation. The continuously tunable strain allows us to illustrate the linear dependence of polarization on epitaxial strain with a large strain-sensitive coefficient of ∼27 μC/cm2 per percent strain. This results in a giant polarization of ∼80 μC/cm2 on the BTO/LSMO interface. Leveraging this large polarization, we achieved a giant tunneling electroresistance (TER) of ∼105 in SAO-buffered Pt/BTO/LSMO ferroelectric tunnel junctions (FTJs). Our research uncovers the fundamental interplay between strain, polarization magnitude, and device performance, such as on/off ratio, thereby advancing the potential of FTJs for next-generation information storage applications.

Enhanced Multiwavelength Response of Flexible Synaptic Transistors for Human Sunburned Skin Simulation and Neuromorphic Computation

In biological species, optogenetics and bioimaging work together to regulate the function of neurons. Similarly, the light-controlled artificial synaptic system not only enhances computational speed but also simulates complex synaptic functions. However, reported synaptic properties are mainly limited to mimicking simple biological functions and single-wavelength responses. Therefore, the development of flexible synaptic devices with multiwavelength optical signal response and multifunctional simulation remains a challenge. Here, flexible organic light-stimulated synaptic transistors (LSSTs) enabled by alumina oxide (AlOX ), with a simple fabrication process, are reported. By embedding AlOX nanoparticles, the excitons separation efficiency is improved, allowing for multiple wavelength responses. Optimized LSSTs can respond to multiple optical and electrical signals in a highly synaptic manner. Multiwavelength optical synaptic plasticity, electrical synaptic plasticity, sunburned skin simulation, learning efficiency model controlled by photoelectric cooperative stimulation, neural network computing, "deer" picture learning and memory functions are successfully proposed, which promote the development for future artificial intelligent systems. Furthermore, as prepared flexible transistors exhibit mechanical flexibility with bending radius down to 2.5 mm and improved photosynaptic plasticity, which facilitating development of neuromorphic computing and multifunction integration systems at the device-level.

Nanoscale multistate resistive switching in WO3 through scanning probe induced proton evolution

Multistate resistive switching device emerges as a promising electronic unit for energy-efficient neuromorphic computing. Electric-field induced topotactic phase transition with ionic evolution represents an important pathway for this purpose, which, however, faces significant challenges in device scaling. This work demonstrates a convenient scanning-probe-induced proton evolution within WO₃, driving a reversible insulator-to-metal transition (IMT) at nanoscale. Specifically, the Pt-coated scanning probe serves as an efficient hydrogen catalysis probe, leading to a hydrogen spillover across the nano junction between the probe and sample surface. A positively biased voltage drives protons into the sample, while a negative voltage extracts protons out, giving rise to a reversible manipulation on hydrogenation-induced electron doping, accompanied by a dramatic resistive switching. The precise control of the scanning probe offers the opportunity to manipulate the local conductivity at nanoscale, which is further visualized through a printed portrait encoded by local conductivity. Notably, multistate resistive switching is successfully demonstrated via successive set and reset processes. Our work highlights the probe-induced hydrogen evolution as a new direction to engineer memristor at nanoscale.

Ferroelectric Nitride Heterostructures on CMOS Compatible Molybdenum for Synaptic Memristors

Achieving ferroelectricity in III-nitride (III-N) semiconductors by alloying with rare-earth elements, e.g., scandium, has presented a pivotal step toward next-generation electronic, acoustic, photonic, and quantum devices and systems. To date, however, the conventional growth of single-crystalline nitride semiconductors often requires the use of sapphire, Si, or SiC substrate, which has prevented their integration with the workhorse complementary metal oxide semiconductor (CMOS) technology. Herein, we demonstrate single-crystalline ferroelectric nitride semiconductors grown on CMOS compatible metal-molybdenum. Significantly, we find that a unique epitaxial relationship between wurtzite and body-centered cubic crystal structure can be well maintained, enabling the realization of single-crystalline wurtzite ferroelectric nitride semiconductors on polycrystalline molybdenum that was not previously possible. Robust and wake-up-free ferroelectricity has been measured, for the first time, in the epitaxially grown ScAlN directly on metal. We further propose and demonstrate a ferroelectric GaN/ScAlN heterostructure for synaptic memristor, which shows the capability of emulating the spike-time-dependent plasticity in a biological synapse. This work provides a viable path for the integration of III-N architectures with the mature CMOS technology and sheds light on the promising applications of ferroelectric nitride memristors in neuromorphic computing.

Directional Formation of Conductive Filaments for a Reliable Organic-Based Artificial Synapse by Doping Molybdenum Disulfide Quantum Dots into a Polymer Matrix

The conductive filament (CF) model, as an important means to realize synaptic functions, has received extensive attention and has been the subject of intense research. However, the random and uncontrollable growth of CFs seriously affects the performances of such devices. In this work, we prepared a neural synaptic device based on polyvinyl pyrrolidone-molybdenum disulfide quantum dot (MoS₂ QD) nanocomposites. The doping with MoS₂ QDs was found to control the growth mode of Ag CFs by providing active centers for the formation of Ag clusters, thus reducing the uncertainty surrounding the growth of Ag CFs. As a result, the device, with a low power consumption of 32.8 pJ/event, could be used to emulate a variety of synaptic functions, including long-term potentiation (LTP), long-term depression (LTD), paired-pulse facilitation, post-tetanic potentiation, short-term memory to long-term memory conversion, and "learning experience" behavior. After having undergone consecutive stimulation with different numbers of pulses, the device stably realized a "multi-level LTP to LTD conversion" function. Moreover, the synaptic characteristics of the device experienced no degradation due to mechanical stress. Finally, the simulation result based on the synaptic characteristics of our devices achieved a high recognition accuracy of 91.77% in learning and inference tests and showed clear digital classification results.

High-precision and linear weight updates by subnanosecond pulses in ferroelectric tunnel junction for neuro-inspired computing

The rapid development of neuro-inspired computing demands synaptic devices with ultrafast speed, low power consumption, and multiple non-volatile states, among other features. Here, a high-performance synaptic device is designed and established based on a Ag/PbZr_0.52Ti_0.48O₃ (PZT, (111)-oriented)/Nb:SrTiO₃ ferroelectric tunnel junction (FTJ). The advantages of (111)-oriented PZT (~1.2 nm) include its multiple ferroelectric switching dynamics, ultrafine ferroelectric domains, and small coercive voltage. The FTJ shows high-precision (256 states, 8 bits), reproducible (cycle-to-cycle variation, ~2.06%), linear (nonlinearity <1) and symmetric weight updates, with a good endurance of >10⁹ cycles and an ultralow write energy consumption. In particular, manipulations among 150 states are realized under subnanosecond (~630 ps) pulse voltages ≤5 V, and the fastest resistance switching at 300 ps for the FTJs is achieved by voltages <13 V. Based on the experimental performance, the convolutional neural network simulation achieves a high online learning accuracy of ~94.7% for recognizing fashion product images, close to the calculated result of ~95.6% by floating-point-based convolutional neural network software. Interestingly, the FTJ-based neural network is very robust to input image noise, showing potential for practical applications. This work represents an important improvement in FTJs towards building neuro-inspired computing systems.

Brain-inspired computing demands high-performance synapses. Here, the authors report a subnanosecond ferroelectric tunnel junction with 256 conductance states, 10⁹ endurance, and 5.3 fJ/bit energy consumption, satisfactory to build synaptic devices.

High-Speed Switching and Giant Electroresistance in an Epitaxial Hf0.5Zr0.5O2-Based Ferroelectric Tunnel Junction Memristor

HfO₂-based ferroelectric materials are good candidates for constructing next-generation nonvolatile memories and high-performance electronic synapses and have attracted extensive attention from both academia and industry. Here, a Hf_0.5Zr_0.5O₂-based ferroelectric tunnel junction (FTJ) memristor is successfully fabricated by epitaxially growing a Hf_0.5Zr_0.5O₂ film on a 0.7 wt % Nb-doped SrTiO₃ (001) substrate with a buffer layer of La_2/3Sr_1/3MnO₃ (∼1 u.c.). The FTJ shows a high switching speed of 20 ns, a giant electroresistance ratio of ∼834, and multiple states (eight states or three bits) with good retention >10⁴ s. As a solid synaptic device, tunable synapse functions have also been obtained, including long-term potentiation, long-term depression, and spike-timing-dependent plasticity. These results highlight the promising applications of Hf_0.5Zr_0.5O₂-based FTJ in ultrafast-speed and high-density nonvolatile memories and artificial synapses.

Direct Observation of Interface-Dependent Multidomain State in the BaTiO3 Tunnel Barrier of a Multiferroic Tunnel Junction Memristor

Multiferroic tunnel junctions (MFTJs), normally consisting of a four-state resistance, have been studied extensively as a potential candidate for nonvolatile memory devices. More interestingly, the MFTJs whose resistance can be tuned continuously with applied voltage were also reported recently. Since the performance of MFTJs is closely related to their interfacial structures, it is necessary to investigate MFTJs at the atomic scale. In this work, atomic-resolution HAADF, ABF, and EELS of the La_0.7Sr_0.3MnO₃/BaTiO₃/La_0.7Sr_0.3MnO₃ MFTJ memristor have been obtained with aberration-corrected scanning transmission electron microscopy (STEM). These results demonstrate varied degree of interfacial cation intermixing at the bottom BTO/LSMO interface, which has a direct influence on the polarization of the ferroelectric barrier BTO and the electronic structure of Mn near the interfaces. We also took advantage of a simplified model to explain the relation between the interfacial behavior and polarization states, which could be a contributing factor to the transport properties of this MFTJ.

Dielectric Relaxation Behavior of BTO/LSMO Heterojunction

The BaTiO₃ (BTO)/La_0.7Sr_0.3MnO₃ (LSMO) magnetoelectric composite films were prepared by sol-gel method on STO (001) substrates. The heterojunction has highly preferred orientation and exhibits well ferroelectric properties with perfect hysteresis loops and microscopic polarization switch behaviors. The most interesting thing is the abnormal dielectric relaxation phenomenon in the dielectric spectra at high frequency range and around the phase transition temperature of LSMO. By analyzing the resistance properties of LSMO films, it is indicated that charge-based interfacial coupling, Maxwell-Wagner effect due to the JT polaron and fast resistivity rise in LSMO layer is the main reason. This work emphasizes the crucial role of resistivity exchanges and of carrier accumulation at interfaces for the application of magnetoelectric heterojunction.

Interface-engineered electron and hole tunneling

Although the phenomenon of tunneling has been known since the advent of quantum mechanics, it continues to enrich our understanding of many fields of science. Commonly, this effect is described in terms of electrons traversing the potential barrier that exceeds their kinetic energy due to the wave nature of electrons. This picture of electron tunneling fails, however, for tunnel junctions, where the Fermi energy lies sufficiently close to the insulator valence band, in which case, hole tunneling dominates. We demonstrate the deterministic control of electron and hole tunneling in interface-engineered Pt/BaTiO₃/La_0.7Sr_0.3MnO₃ ferroelectric tunnel junctions by reversal of tunneling electroresistance. Our electrical measurements, electron microscopy and spectroscopy characterization, and theoretical modeling unambiguously point out to electron or hole tunneling regimes depending on interface termination. The interface control of the tunneling regime offers designed functionalities of electronic devices.

Intrinsic asymmetric ferroelectricity induced giant electroresistance in ZnO/BaTiO3 superlattice

Here, we combine the piezoelectric wurtzite ZnO and the ferroelectric (111) BaTiO3 as a hexagonal closed-packed structure and report a systematic theoretical study on the ferroelectric behavior induced by the interface of ZnO/BaTiO3 films and the transport properties between the SrRuO3 electrodes. The parallel and antiparallel polarizations of ZnO and BaTiO3 can lead to intrinsic asymmetric ferroelectricity in the ZnO/BaTiO3 superlattice. Using first-principles calculations we demonstrate four different configurations for the ZnO/BaTiO3/ZnO superlattice with respective terminations and find one most favorable for the stable existence of asymmetric ferroelectricity in thin films with thickness less than 4 nm. Combining density functional theory calculations with non equilibrium Green's function formalism, we investigate the electron transport properties of SrRuO3/ZnO/BaTiO3/ZnO/SrRuO3 FTJ and SrRuO3/ZnO/BaTiO3/SrRuO3 FTJ, and reveal a high TER effect of 581% and 112% respectively. These findings provide an important insight into the understanding of how the interface affects the polarization in the ZnO/BaTiO3 superlattice and may suggest a controllable and unambiguous way to build ferroelectric and multiferroic tunnel junctions.

Memristive Circuit Implementation of Biological Nonassociative Learning Mechanism and Its Applications

Biological nonassociative learning is one of the simplest forms of unsupervised learning in animals and can be categorized into habituation and sensitization according to mechanism. This paper proposes a memristive circuit that is based on nonassociative learning and can adapt to repeated inputs, reduce power consumption (habituation), and be sensitive to harmful inputs (sensitization). The circuit includes 1) synapse module, 2) neuron module, 3) feedback module. The first module mainly consists of memristors representing synapse weights that vary with corresponding inputs. Memristance is automatically reduced when a harmful stimulus is input, and climbs at the input interval according to the feedback input when repeated stimuli are input. The second module produces spiking voltage when the total input is above the given threshold. The third module can provide feedback voltage according to the frequency and quantity of input stimuli. Simulation results show that the proposed circuit can generate output signals with biological nonassociative learning characteristics, with varying amplitudes depending on the characteristics of input signals. When the frequency and quantity of the input stimuli are high, the degree of habituation and sensitization intensifies. The proposed circuit has good robustness; can reduce the influence of noise, circuit parasitics and circuit aging during nonassociative learning; and simulate the afterimages caused by visual fatigue for application in automatic exposure compensation.

A Glance at Processing-Microstructure-Property Relationships for Magnetoelectric Particulate PZT-CFO Composites

In this work, we investigated the processing-microstructure-property relationships for magnetoelectric (ME) particulate composites consisting of hard ferromagnetic CoFe₂O₄ (CFO) particles dispersed in a Nb-doped PbZr_xTi_1-xO₃ (PZT) soft ferroelectric matrix. Several preparation steps, namely PZT powder calcination, PZT-CFO mixture milling and composite sintering were tailored and a range of microstructures was obtained. These included open and closed porosities up to full densification, PZT matrices with decreasing grain size across the submicron range down to the nanoscale and well dispersed CFO particles with bimodal size distributions consisting of submicron and micron sized components with varying weights. All samples could be poled under a fixed DC electric field of 4 kV/mm and the dielectric, piezoelectric and elastic coefficients were obtained and are discussed in relation to the microstructure. Remarkably, materials with nanostructured PZT matrices and open porosity showed piezoelectric charge coefficients comparable with fully dense composites with coarsened microstructure and larger voltage coefficients. Besides, the piezoelectric response of dense materials increased with the size of the CFO particles. This suggests a role of the conductive magnetic inclusions in promoting poling. Magnetoelectric coefficients were obtained and are discussed in relation to densification, piezoelectric matrix microstructure and particle size of the magnetic component. The largest magnetoelectric coefficient α₃₃ of 1.37 mV cm^-1 Oe^-1 was obtained for submicron sized CFO particles, when closed porosity was reached, even if PZT grain size remained in the nanoscale.

Research progress on solutions to the sneak path issue in memristor crossbar arrays

Since the emergence of memristors (or memristive devices), how to integrate them into arrays has been widely investigated. After years of research, memristor crossbar arrays have been proposed and realized with potential applications in nonvolatile memory, logic and neuromorphic computing systems. Despite the promising prospects of memristor crossbar arrays, one of the main obstacles for their development is the so-called sneak-path current causing cross-talk interference between adjacent memory cells and thus may result in misinterpretation which greatly influences the operation of memristor crossbar arrays. Solving the sneak-path current issue, the power consumption of the array will immensely decrease, and the reliability and stability will simultaneously increase. In order to suppress the sneak-path current, various solutions have been provided. So far, some reviews have considered some of these solutions and established a sophisticated classification, including 1D1M, 1T1M, 1S1M (D: diode, M: memristor, T: transistor, S: selector), self-selective and self-rectifying memristors. Recently, a mass of studies have been additionally reported. This review thus attempts to provide a survey on these new findings, by highlighting the latest research progress realized for relieving the sneak-path issue. Here, we first present the concept of the sneak-path current issue and solutions proposed to solve it. Consequently, we select some typical and promising devices, and present their structures and properties in detail. Then, the latest research activities focusing on single-device structures are introduced taking into account the mechanisms underlying these devices. Finally, we summarize the properties and perspectives of these solutions.

Sub-nanosecond memristor based on ferroelectric tunnel junction

Next-generation non-volatile memories with ultrafast speed, low power consumption, and high density are highly desired in the era of big data. Here, we report a high performance memristor based on a Ag/BaTiO₃/Nb:SrTiO₃ ferroelectric tunnel junction (FTJ) with the fastest operation speed (600 ps) and the highest number of states (32 states or 5 bits) per cell among the reported FTJs. The sub-nanosecond resistive switching maintains up to 358 K, and the write current density is as low as 4 × 10³ A cm⁻². The functionality of spike-timing-dependent plasticity served as a solid synaptic device is also obtained with ultrafast operation. Furthermore, it is demonstrated that a Nb:SrTiO₃ electrode with a higher carrier concentration and a metal electrode with lower work function tend to improve the operation speed. These results may throw light on the way for overcoming the storage performance gap between different levels of the memory hierarchy and developing ultrafast neuromorphic computing systems.

Memristor devices based on ferroelectric tunnel junctions are promising, but suffer from quite slow switching times. Here, the authors report on ultrafast switching times at and above room temperature of 600ps in Ag/BaTiO3/Nb:SrTiO3 based ferroelectric tunnel junctions.

Energy-Efficient Artificial Synapses Based on Oxide Tunnel Junctions

The development of artificial synapses has enabled the establishment of brain-inspired computing systems, which provides a promising approach for overcoming the inherent limitations of current computer systems. The two-terminal memristors that faithfully mimic the function of biological synapses have intensive prospects in the neural network field. Here, we propose a high-performance artificial synapse based on oxide tunnel junctions with oxygen vacancy migration. Both short-term and long-term plasticities are mimicked in one device. The oxygen vacancy migration through oxide ultrathin films is utilized to manipulate long-term plasticity. Essential synaptic functions, such as paired pulse facilitation, post-tetanic potentiation, as well as spike-timing-dependent plasticity, are successfully implemented in one device by finely modifying the shape of the pre- and postsynaptic spikes. Ultralow femtojoule energy consumption comparable to that of the human brain indicates its potential application in efficient neuromorphic computing. Oxide tunnel junctions proposed in this work provide an alternative approach for realizing energy-efficient brain-like chips.

Resistive Switching Memory Devices Based on Body Fluid of Bombyx mori L

Resistive switching memory devices are strong candidates for next-generation data storage devices. Biological memristors made from renewable natural biomaterials are very promising due to their biocompatibility, biodegradability, and ecological benignity. In this study, a nonvolatile memristor was fabricated using the body fluid of Bombyx mori as the dielectric layer. The developed Al/Bombyx mori body fluid film/indium tin oxide (ITO) biomemristor exhibited bipolar resistive switching characteristics with a maximum on/off current ratio greater than 10⁴. The device showed a retention time of more than 1 × 10⁴ s without any signs of deterioration, thus proving its good stability and reliability. The resistive switching behavior of the Al/Bombyx mori body fluid film/ITO biological memristor is driven by the formation and breakage of conductive filaments formed by the migration of oxygen ions. This study confirms that Bombyx mori body fluid, a 100% natural, inexpensive, and abundant material, is a potential candidate as a nonvolatile biomemristor material with broad application prospects.

Memristor in a Reservoir System-Experimental Evidence for High-Level Computing and Neuromorphic Behavior of PbI2

Lead halides in an asymmetric layered structure form memristive devices which are controlled by the electronic structure of the PbX₂|metal interface. In this paper, we explain the mechanism that stands behind the I- V pinched hysteresis loop of the device and shortly present its synaptic-like plasticity (spike-timing-dependent plasticity and spike-rate-dependent plasticity) and nonvolatile memory effects. This memristive element was incorporated into a reservoir system, in particular, the echo-state network with delayed feedback, which exhibits brain-like recurrent behavior and demonstrates metaplasticity as one of the available learning mechanisms. It can serve as a classification system that classifies input signals according to their amplitude.

Electric-Field-Controlled Nonvolatile Magnetization Rotation and Magnetoresistance Effect in Co/Cu/Ni Spin Valves on Piezoelectric Substrates

Electric-field control of magnetism is a key issue for the future development of low-power spintronic devices. By utilizing the opposite strain responses of the magnetic anisotropies in Co and Ni films, a Co/Cu/Ni/0.7Pb(Mg_1/3Nb_2/3)O₃-0.3PbTiO₃ (PMN-PT) spin-valve/piezoelectric heterostructure with ∼7 nm Cu spacer layer was properly designed and fabricated. The purely electric-field-controlled nonvolatile and reversible magnetization rotations in the Co free layer were achieved, whereas the magnetization of the Ni fixed layer was almost unchanged. Accordingly, not only the electroresistance but also the electric-field-tuned magnetoresistance effects were obtained, and more importantly at least six nonvolatile magnetoresistance states in the strain-tuned spin valve were achieved by setting the PMN-PT into different nonvolatile piezo-strain states. These findings highlight potential strategies for designing electric-field-driven multistate spintronic devices.

Control of Synaptic Plasticity Learning of Ferroelectric Tunnel Memristor by Nanoscale Interface Engineering

Brain-inspired computing is an emerging field, which intends to extend the capabilities of information technology beyond digital logic. The progress of the field relies on artificial synaptic devices as the building block for brainlike computing systems. Here, we report an electronic synapse based on a ferroelectric tunnel memristor, where its synaptic plasticity learning property can be controlled by nanoscale interface engineering. The effect of the interface engineering on the device performance was studied. Different memristor interfaces lead to an opposite virgin resistance state of the devices. More importantly, nanoscale interface engineering could tune the intrinsic band alignment of the ferroelectric/metal-semiconductor heterostructure over a large range of 1.28 eV, which eventually results in different memristive and spike-timing-dependent plasticity (STDP) properties of the devices. Bidirectional and unidirectional gradual resistance modulation of the devices could therefore be controlled by tuning the band alignment. This study gives useful insights on tuning device functionalities through nanoscale interface engineering. The diverse STDP forms of the memristors with different interfaces may play different specific roles in various spike neural networks.