Search Results (14)

In the pursuit of advanced non-volatile memory technologies, ferroelectric memristors have attracted great attention. However, traditional perovskite ferroelectric materials are hampered by environmental pollution, limited applicability, and the complexity and high cost of conventional vacuum deposition methods. This has spurred the exploration of alternative materials and fabrication strategies. Herein, a flexible Pt/Zr: HfO₂ (HZO)/graphene oxide (GO)/mica memristor is successfully fabricated using the total solution-processed method. The interfacial oxygen competition mechanism between the HZO layer and the GO bottom electrode facilitates the formation of the HZO ferroelectric phase. The as-prepared device exhibits a switching ratio of approximately 150 and can maintain eight distinct resistance levels, and it can also effectively simulate neural responses. By integrating the ferroelectric polarization principle and the piezoelectric effect of HZO, along with the influence of GO, the performance variations of the as-prepared device under mechanical and thermal influences are further explored. Notably, Morse code recognition is achieved by utilizing the device’s pressure properties and setting specific press rules. The as-prepared device can accurately convert and store information, opening new avenues for non-volatile memory applications in silent communication and promoting the development of wearable electronics. Full article

Neuromorphic computing inspired by biological synapses requires memory devices capable of mimicking short-term memory (STM) and associative learning. In this study, we investigate a 15 nm-thick Hafnium zirconium oxide (HZO)-based ferroelectric memristor device, which exhibits robust STM characteristics and successfully replicates Pavlov’s dog experiment. The optimized 15 nm HZO layer demonstrates enhanced ferroelectric properties, including a stable orthorhombic phase and a reliable short-term synaptic response. Furthermore, through a series of conditional learning experiments, the device effectively reproduces associative learning by forming and extinguishing conditioned responses, closely resembling biological neural plasticity. The number of training repetitions significantly affects the retention of learned responses, indicating a transition from STM-like behavior to longer-lasting memory effects. These findings highlight the potential of the optimized ferroelectric device in neuromorphic applications, particularly for implementing real-time learning and memory in artificial intelligence systems. Full article

The pursuit of low-power/low-voltage operation in devices has prompted a keen interest in the mesoscale effects within ferroelectric thin films. The downsizing of ferroelectrics can significantly influence performance; for instance, the remanent polarization and coercive field are susceptible to alterations based on thickness. In this study, randomly oriented Bi_3.25La_0.75Ti₃O₁₂ thin films were fabricated on Pt/Ti/SiO₂/Si substrates using the sol–gel method, and SEM observations revealed rod-like grains in all thin films. The investigation delved into the correlation between dielectric and ferroelectric properties with thin film thickness. The thin film exhibited an increased remanent polarization and a reduced coercive electric field. Additionally, the ferroelectric domain structure was scrutinized through PFM, and the resistor properties of the BLT4 thin film were studied, which shows the potential of BLT thin films in non-volatile memory and memristor. Full article

Computing systems are becoming more and more power-constrained due to unconventional computing requirements like computing on the edge, in-sensor, or simply an insufficient battery. Emerging Non-Volatile Memories are explored to build low-power computing circuits, and adders are one among them. In this work, we propose a low-power adder using a Ferroelectric Tunnel Junction (FTJ). FTJs are two-terminal devices where the data is stored in the polarization state of the device. An FTJ-based majority gate is proposed, which uses a current-mode sensing technique to evaluate the majority of the inputs. By conditionally selecting between the majority and its complement, an XOR operation is implemented, thereby achieving full-adder functionality. Since FTJ-based majority operation is slow, a ternary adder architecture is used to compensate for the speed loss. The ternary adder proposed by us has two stages of full adder and requires O(1) time for n-bit addition. The proposed adder is verified using a simulation in CMOS 130 nm technology. A 32-bit addition can be achieved in 100 μs and consumes 0.78 pJ, which is very power efficient (7.8 nW). The proposed adder can be used in applications where power consumption is crucial, and speed is not a strict requirement. Full article

Owing to the 4th Industrial Revolution, the amount of unstructured data, such as voice and video data, is rapidly increasing. Brain-inspired neuromorphic computing is a new computing method that can efficiently and parallelly process rapidly increasing data. Among artificial neural networks that mimic the structure of the brain, the spiking neural network (SNN) is a network that imitates the information-processing method of biological neural networks. Recently, memristors have attracted attention as synaptic devices for neuromorphic computing systems. Among them, the ferroelectric doped-HfO₂-based ferroelectric tunnel junction (FTJ) is considered as a strong candidate for synaptic devices due to its advantages, such as complementary metal–oxide–semiconductor device/process compatibility, a simple two-terminal structure, and low power consumption. However, research on the spiking operations of FTJ devices for SNN applications is lacking. In this study, the implementation of long-term depression and potentiation as the spike timing-dependent plasticity (STDP) rule in the FTJ device was successful. Based on the measured data, a CrossSim simulator was used to simulate the classification of handwriting images. With a high accuracy of 95.79% for the Mixed National Institute of Standards and Technology (MNIST) dataset, the simulation results demonstrate that our device is capable of differentiating between handwritten images. This suggests that our FTJ device can be used as a synaptic device for implementing an SNN. Full article

A transient chaotic neural network (TCNN) is particularly useful for solving combinatorial optimization problems, and its hardware implementation based on memristors has attracted great attention recently. Although previously used filamentary memristors could provide the desired nonlinearity for implementing the annealing function of a TCNN, the controllability of filamentary switching still remains relatively poor, thus limiting the performance of a memristor-based TCNN. Here, we propose to use ferroelectric memristor to implement the annealing function of a TCNN. In the ferroelectric memristor, the conductance can be tuned by switching the lattice non-centrosymmetry-induced polarization, which is a nonlinear switching mechanism with high controllability. We first establish a ferroelectric memristor model based on a ferroelectric tunnel junction (FTJ), which exhibits the polarization-modulated tunnel conductance and the nucleation-limited-switching (NLS) behavior. Then, the conductance of the ferroelectric memristor is used as the self-feedback connection weight that can be dynamically adjusted. Based on this, a ferroelectric memristor-based transient chaotic neural network (FM-TCNN) is further constructed and applied to solve the traveling salesman problem (TSP). In 1000 runs for 10-city TSP, the FM-TCNN achieves a shorter average path distance, a 32.8% faster convergence speed, and a 2.44% higher global optimal rate than the TCNN. Full article

In-memory computing is an attractive solution for reducing power consumption and memory access latency cost by performing certain computations directly in memory without reading operands and sending them to arithmetic logic units. Content-addressable memory (CAM) is an ideal way to smooth out the distinction between storage and processing, since each memory cell is a processing unit. CAM compares the search input with a table of stored data and returns the matched data address. The issues of constructing binary and ternary content-addressable memory (CAM and TCAM) based on ferroelectric devices are considered. A review of ferroelectric materials and devices is carried out, including on ferroelectric transistors (FeFET), ferroelectric tunnel diodes (FTJ), and ferroelectric memristors. Full article

Lithium niobate (LiNbO₃) crystals are important dielectric and ferroelectric materials, which are widely used in acoustics, optic, and optoelectrical devices. The physical and chemical properties of LiNbO₃ are dependent on microstructures, defects, compositions, and dimensions. In this review, we first discussed the crystal and defect structures of LiNbO₃, then the crystallization of LiNbO₃ single crystal, and the measuring methods of Li content were introduced to reveal reason of growing congruent LiNbO₃ and variable Li/Nb ratios. Afterwards, this review provides a summary about traditional and non-traditional applications of LiNbO₃ crystals. The development of rare earth doped LiNbO₃ used in illumination, and fluorescence temperature sensing was reviewed. In addition to radio-frequency applications, surface acoustic wave devices applied in high temperature sensor and solid-state physics were discussed. Thanks to its properties of spontaneous ferroelectric polarization, and high chemical stability, LiNbO₃ crystals showed enhanced performances in photoelectric detection, electrocatalysis, and battery. Furthermore, domain engineering, memristors, sensors, and harvesters with the use of LiNbO₃ crystals were formulated. The review is concluded with an outlook of challenges and potential payoff for finding novel LiNbO₃ applications. Full article

Electronic memory devices, such as memristors, charge trap memory, and floating-gate memory, have been developed over the last decade. The use of polymers in electronic memory devices enables new opportunities, including easy-to-fabricate processes, mechanical flexibility, and neuromorphic applications. This review revisits recent efforts on polymer-based electronic memory developments. The versatile contributions of polymers for emerging memory devices are classified, providing a timely overview of such unconventional functionalities with a strong emphasis on the merits of polymer utilization. Furthermore, this review discusses the opportunities and challenges of polymer-based memory devices with respect to their device performance and stability for practical applications. Full article

Herein, Bi₄Ti₃O₁₂ (BIT) ferroelectric thin films were fabricated into Au/BIT/LaNiO₃/Si structures to demonstrate their memristor properties. Repeatable and stable bipolar resistive switching (RS) characteristics of the device are first reported in this work. The switching ratio of the device annealed in air reached approximately 10² at 0.1 and −0.1 V. The RS performance was not significantly degraded after 100 consecutive cycles of testing. We also explored the factors affecting the RS behavior of the device. By investigating the RS characteristics of the devices annealed in O_2, and in combination with XPS analysis, we found that the RS properties were closely related to the presence of oxygen vacancies. The devices annealed in air exhibited a markedly improved RS effect over those annealed in O₂. According to the slope fitting, the conduction mechanism of the device was the ohmic conduction and space charge limited current (SCLC). This study is the first to successfully apply BIT ferroelectric films to the RS layers of memristors. Additionally, a theory of conductive filaments is proposed to adequately explain the relationship between RS behavior and oxygen vacancies, providing meaningful inspiration for designing high-quality resistive random access memory devices. Full article

Nanomaterials science is becoming the foundation stone of high-frequency applications. The downscaling of electronic devices and components allows shrinking chip’s dimensions at a more-than-Moore rate. Many theoretical limits and manufacturing constraints are yet to be taken into account. A promising path towards nanoelectronics is represented by atomic-scale materials. In this manuscript, we offer a perspective on a specific class of devices, namely switches designed and fabricated using two-dimensional or nanoscale materials, like graphene, molybdenum disulphide, hexagonal boron nitride and ultra-thin oxides for high-frequency applications. An overview is provided about three main types of microwave and millimeter-wave switch: filament memristors, nano-ionic memristors and ferroelectric junctions. The physical principles that govern each switch are presented, together with advantages and disadvantages. In the last part we focus on zirconium-doped hafnium oxide ferroelectrics (HfZrO) tunneling junctions (FTJ), which are likely to boost the research in the domain of atomic-scale materials applied in engineering sciences. Thanks to their Complementary Metal-Oxide Semiconductor (CMOS) compatibility and low-voltage tunability (among other unique physical properties), HfZrO compounds have the potential for large-scale applicability. As a practical case of study, we present a 10 GHz transceiver in which the switches are FTJs, which guarantee excellent isolation and ultra-fast switching time. Full article

The ultimate memristor, which acts as resistive memory and an artificial neural synapse, is made from a single atomic layer. In this manuscript, we present experimental evidence of the memristive properties of a nanopatterned ferroelectric graphene field-effect transistor (FET). The graphene FET has, as a channel, a graphene monolayer transferred onto an HfO₂-based ferroelectric material, the channel being nanopatterned with an array of holes with a diameter of 20 nm. Full article

The article presents the results of an experimental study of the transport of charge carriers through semiconductor PANI-polystyrene/ ferroelectric PVDF-TrFE interface. Current-voltage characteristics of the structure under study have a typical form for memristors and may be explained by the movement of charge carriers in the internal switchable field of the crystal ferroelectric microregions located within a bulk volume of amorphous PVDF-TrFE matrix. This assumption is subject to XRD phase analysis, FTIR spectroscopy, and X-ray EDS microanalysis. A long-term (about 100 h) relaxation is detected for the resistance of the PANI-polysturene/PVDF-TrFE interface after the current-voltage characteristics measurement cycle that is associated with the processes of capture and release traps of charge carriers. Full article

Solid-state memory is an essential component of the digital age. With advancements in healthcare technology and the Internet of Things (IoT), the demand for ultra-dense, ultra-low-power memory is increasing. In this review, we present a comprehensive perspective on the most notable approaches to the fabrication of physically flexible memory devices. With the future goal of replacing traditional mechanical hard disks with solid-state storage devices, a fully flexible electronic system will need two basic devices: transistors and nonvolatile memory. Transistors are used for logic operations and gating memory arrays, while nonvolatile memory (NVM) devices are required for storing information in the main memory and cache storage. Since the highest density of transistors and storage structures is manifested in memories, the focus of this review is flexible NVM. Flexible NVM components are discussed in terms of their functionality, performance metrics, and reliability aspects, all of which are critical components for NVM technology to be part of mainstream consumer electronics, IoT, and advanced healthcare devices. Finally, flexible NVMs are benchmarked and future prospects are provided. Full article