Ag-dispersive chalcogenide media for readily activated electronic memristor

In this study, we implemented a high-performance two-terminal memristor device with a metal/insulator/metal (MIM) structure using a solution-derived In-Ga-Zn-Oxide (IGZO)-based nanocomposite as a resistive switching (RS) layer. In order to secure stable memristive switching characteristics, IGZO:N nanocomposites were synthesized through the microwave-assisted nitridation of solution-derived IGZO thin films, and the resulting improvement in synaptic characteristics was systematically evaluated. The microwave-assisted nitridation of solution-derived IGZO films was clearly demonstrated by chemical etching, optical absorption coefficient analysis, and X-ray photoelectron spectroscopy. Two types of memristor devices were prepared using an IGZO or an IGZO:N nanocomposite film as an RS layer. As a result, the IGZO:N memristors showed excellent endurance and resistance distribution in the 103 repeated cycling tests, while the IGZO memristors showed poor characteristics. Furthermore, in terms of electrical synaptic operation, the IGZO:N memristors possessed a highly stable nonvolatile multi-level resistance controllability and yielded better electric pulse-induced conductance modulation in 5 × 102 stimulation pulses. These findings demonstrate that the microwave annealing process is an effective synthesis strategy for the incorporation of chemical species into the nanocomposite framework, and that the microwave-assisted nitridation improves the memristive switching characteristics in the oxide-based RS layer.

The age of information has placed unprecedented demands on data storage. In response, a rich hub of research activity has erupted in the search for new types of memory with improved capacity and data processing speed [1, 2]. There has even been progress in mimicking the subtleties of how the human neural system remembers and forgets with artificial synaptic devices [3, 4]. Yet many challenges remain. As researchers at Brigham Young University in the US point out, 'Current data storage technologies have limitations that prevent their use in archival data storage applications'. Anthony C Pearson and colleagues look at the potential role of graphene in data storage solutions. Graphene's wide range of extraordinary properties has recommended it for a number of applications. This issue reports how it can form the basis of nanofuses that may be used for permanent, write-once-read-many (WORM) data storage devices [5].Leon Chua's forecast of 'Memristor—the missing circuit element' [6] and the subsequent demonstration of memristance in nanoscale systems byresearchers at HP Labs [7] triggered a surge of studies investigating the application of memristor devices in non-volatile memory [8]. In fact thesestructures may have a still broader impact in nanotechnology. At the nanoscale statistical variations in defect concentrations give rise to vast differences in behaviour, and device variability and ageing can be profound. These characteristics led George Snider to observe, 'Nanodevices are crummy', when considering their application in conventional Boolean logic systems [9]. Yet Snider's grim assessment was merely a prologue to an insightful recount of simulations demonstrating how to side-step a number of nanotechnology's main challenges by using self-organizing networks based on memristive devices.Similar fault tolerance is demonstrated in the organic-nanoparticle transistors developed by researchers at the University of Lille, who demonstrate a weighting behaviour that mimics aspects of synaptic functions that may be key to implementing neuromorphic computing [10]. Developments in this field show increasingly more sophisticated imitation of human neural processing with analogue memory functionality [3] and circuits that both learn and forget [4]. Keep an eye out for the Nanotechnology special issue on synaptic electronics later this year with guest editors James Gimzewski from the University of California, Los Angeles, and Dominique Vuillaume from the University of Lille, for a one-stop update on the latest cutting edge developments in this field.Graphene has demonstrated excellent potential in a number of applications from supercapacitors [11] to photomechanical actuators [12]. However, so far its potential in memory has been notably less explored. In this issue Anthony C Pearson and colleagues at Brigham Young University report how they fabricate graphene 'bow-tie' structures for fuses and program them though thermal oxidation [5]. As the researchers point out graphene's low atomic mobility, high chemical resistance to oxidation and excellent electrical conductivity make it well suited as archival data storage fuse material. They also highlight a number of attractive attributes in the devices as a whole: 'graphene WORM devices can be read and written electronically, can potentially have the very high data densities of flash memory, appear to be highly stable in both the on and off states, have a high on/off current ratio, and can be programmed with low voltages and powers'.In fuses an electrical connection is destroyed by an applied voltage. The process sounds destructive yet fuses are incredibly useful. Edison once famously commented, 'Just because something does not do what you planned it to do does not mean it is useless' [13]. There are synergies of this philosophy throughout nanotechnology research where apparently awkward behaviour is put to good use. Adding the dynamical nature of nanodevices to the list of obstacles to scalability, Snider rounded up his assessment, 'So we are faced with the challenge of computing with devices that are not only crummy, but dynamical as well'. Yet it was that dynamic behaviour that he went on to exploit in his demonstration of robust self-organizing networks using memristor devices. Successful research is by nature continually revealing behaviour that is unexpected or unusual. Thework described here is just some of the many examples of how successful development in research does not tolerate the unexpected, but embraces it.

The memtransistor constructed using the emerging two-dimensional tellurene material has demonstrated significant potential for application in artificial synaptic devices and image recognition. However, conventional device fabrication processes, such as dry transfer, restrict tellurene's further application in flexibility and wearable electronics. Here, a fully printed, flexible tellurene field-effect transistor (FET) is demonstrated, consisting of a channel, gate dielectric layer, and contact electrodes, all of which are prepared using functional inks that include tellurene, h-BN, and graphene, respectively. Such a device integrates scalable ink formulations and neuromorphic functionality for advanced electronics, exhibiting relatively stable electrical performance even after 10,000 bending cycles at a curvature radius of 11.05 mm. Applying electric stimulation to the h-BN layer enables the realization of a bioinspired memtransistor, achieving paired-pulse facilitation, reconfigurable short-term plasticity to long-term plasticity transitions, and synaptic weight updates. Moreover, image recognition simulation using an artificial neural network achieves 93.91% accuracy on the Modified National Institute of Standards and Technology database, which can maintain 78.33% accuracy after introducing σ = 0.7 Gaussian noise. These results position printed tellurene FETs as promising, noise-resilient building blocks for scalable, flexible neuromorphic systems.

The important role of surface sensitive characterization techniques such as Auger electron spectroscopy (AES), X-ray photo electron spectroscopy (XPS), time of flight scanning ion mass spectrometry (TOF-SIMS) and High resolution transmission electron microscopy (HRTEM) for the characterization of different phosphor materials is discussed in this short review by giving selective examples from previous obtained results. AES is used to monitor surface reactions during electron bombardment and also to determine the elemental composition of the surfaces of the materials, while XPS and TOF-SIMS are used for determining the surface chemical composition and valence state of the dopants. The role of XPS to determine the presence of defects in the phosphor matrix is also stated with the different examples. The role of HRTEM in combination with Energy dispersive spectroscopy (EDS) for nanoparticle characterization is also pointed out.

Memristive devices with both electrically and optically induced synaptic dynamic behaviors will be crucial to the accomplishment of brain-inspired neuromorphic computing systems, in which the resistive materials and device architectures are two of the most important cornerstones, but still under challenge. Herein, kuramite Cu3SnS4 is newly introduced into poly-methacrylate as the switching medium to construct memristive devices, and the expected high-performance bio-mimicry of diverse optoelectronic synaptic plasticity is demonstrated. In addition to the excellent basic performances, such as stable bipolar resistive switching with On/Off ratio of ∼486, Set/Reset voltage of ∼-0.88/+0.96V, and good retention feature of up to 104s, the new designs of memristors possess not only the multi-level controllable resistive-switching memory property but also the capability of mimicking optoelectronic synaptic plasticity, including electrically and visible/near-infrared light-induced excitatory postsynaptic currents, short-/long-term memory, spike-timing-dependent plasticity, long-term plasticity/depression, short-term plasticity, paired-pulse facilitation, and "learning-forgetting-learning" behavior as well. Predictably, as a new class of switching medium material, such proposed kuramite-based artificial optoelectronic synaptic device has great potential to be applied to construct neuromorphic architectures in simulating human brain functions.

Auger Electron Spectroscopy (AES) and x-ray photoelectron spectroscopy (XPS) have many aspects in common. Therefore, tests of aspects for one spectroscopy, applicable to the other, should be validated for both. Digital databases of elemental spectra for both AES and XPS have thus been measured using an electron spectrometer that has been fully calibrated for its intensity and energy axes. These databases of true spectra give absolute Auger electron yields and relative photoelectron yields. The AES data are measured for both 5 and 10 keV electron beam energies, whereas the XPS data are measured for both Al and Mg unmonochromated x rays at the magic angle. In addition to these we have measured reflected electron energy loss spectroscopy (REELS) data to provide a third database. The combination of these databases allows a refinement of the theories to obtain an overall convergence between theory and experiment. Improvements to the theory have been obtained by identifying three classes of parameter, those (i) for both AES and XPS, such as electron transport, the methodology of evaluation of peak areas, and the spectrometer response function, (ii) for AES only, such as the electron ionization cross section, backscattering, and specific electron backgrounds, and (iii) for XPS only, such as the photon-ionization cross section. Additionally, the use of REELS data for background subtraction seems significantly better than the use of any one single Tougaard universal cross section in the determination of the AES and XPS intensities in the databases. The formalism for quantitative analysis in AES and XPS, using relative sensitivity factors, has been revised to develop an accurate matrix-less formalism that is very simple for use by the analyst. This formalism, involving “average matrix sensitivity factors” rather than “pure element sensitivity factors,” has the same accuracy as the matrix formalism but its simplicity permits ready extension to systems beyond binary.

Si/O/N-doped single-walled carbon nanotubes (SWNTs) are synthesized using aerosol-assisted chemical vapor deposition (AACVD). The samples are characterized by Raman spectroscopy, high-resolution transmission electron microscopy (HRTEM), electron energy loss spectroscopy (EELS), energy-dispersive X-ray spectroscopy (EDS), Auger electron spectroscopy (AES), and X-ray photoelectron spectroscopy (XPS). HRTEM and Raman spectroscopy studies indicate that doping plays a crucial role in the generation of stable small diameter SWNTs. In order to elucidate the role of the heterodoping (Si/N, O/N, and Si/O) on the electronic properties and stability of SWNTs, density functional theory (DFT) computations on semiconductor (10,0), semimetallic (9,0), and metallic (5,5) SWNTs are performed. It is found that in the heterodoped SWNTs substitutional nitrogen makes the inclusion of Si and O atoms more energetically favorable within the carbon lattice. Heterodoping with Si/O/N may have an important impact in the chemistry of SWNTs as they could be used for anchoring polymer chains, clusters, molecules, etc., thus leading to advanced composites and sensors.

Redox-based memristive devices (ReRAM) are considered for future energy-efficient non-volatile memory. Memristive cells enable high speed data access, low power consumption and high scalability, which is a key requirement for their use as artificial synapses in neuromorphic computing. Applications in networks of up to 106 devices require a scaling of the cell volume to about 103 nm3. For a typical valence-change-mechanism (VCM)-type switching cell with a metal oxide, like HfO2, sandwiched between two metal electrodes of different oxidation enthalpy, this means that the individual layer thickness is in the range of a few nanometers. Therefore, a control of the device properties demands for a control of interfacial reactions during device fabrication. Here, we are going to present a careful analysis of the oxidation of an Hf electrode layer during atomic layer deposition (ALD) of different metal oxides, these are Al2O3, TiO2, and HfO2. The in-situ encapsulation of a reactive metal electrode by means of an ALD metal oxide layer enables a better process control compared to stack structures formed by breaking the vacuum conditions.In this study, plasma and thermal ALD processes were used to grow ultrathin layers of Al2O3, TiO2, and HfO2 on top of Hf metal films, after transfer under UHV conditions. The growth of homogeneous metal oxide films of a few nanometer in thickness enabled a systematic analysis of the HfO2 formation at the Hf/metal oxide interface by means of angle dependent X-ray photoelectron spectroscopy (XPS). The results show that the properties of the interfacial HfO2 layer can be controlled by the metal oxide deposited on top as well as by the process chemistry and deposition temperature. In contrast to the TiO2 film, the Al2O3 layer clearly serves as oxidation barrier. In addition, the chemistry and structure of the HfO2 interfacial layer were analyzed from XPS and transmission electron microscopy analysis.Memristive device were fabricated from the Hf/HfO2/MOx stacks by depositing Pt top electrodes. The initial current of the devices scales with the pad size indicating the high quality of the insulating oxide layers. Consistent with VCM-type memristive devices the cells required an electroforming voltage to enable bipolar-type resistive switching. In this presentation, the trade-off between the two functionalities of oxidation protection versus enabling of a low electroforming voltage will be discussed.

Memristive devices for neuromorphic computing have been attracting ever growing attention over the last couple of years. In neuromorphic electronics, memristive devices with multi‐level resistance states are required to accurately reproduce synaptic weights. Here, a memristive device based on a multilayer oxide system (Nb/NbOx/Al2O3/HfO2/Au), which features a filamentary‐free, homogenous interfacial resistive switching mechanism, is investigated. To gain a deeper insight into the switching mechanism, impedance spectroscopy (ImpSpec), X‐ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM) are exploited. While this work focuses on the analysis of impedance and current‐voltage characteristics, XPS and TEM investigations can be found in a companion paper (Zahari et al.). In the course of this investigation, potentiodynamic impedance spectroscopy (PD‐ImpSpec) and time resolved impedance spectroscopy (TR‐ImpSpec) in combination with transient analysis are used. Evidence is presented of switching kinetics at voltages above 2.1 V directly related to changes in Schottky barrier resistance. These switching kinetics can in turn be interpreted by the charging and discharging of double positively charged oxygen vacancies ≈ 0.9 eV. The results of the impedance analysis are translated into a more general model for memristive devices to map the physical processes during switching.

Artificial neural networks (ANNs) based on synaptic devices, which can simultaneously perform processing and storage of data, have superior computing performance compared to conventional von Neumann architectures. Here, we present a ferroelectric coupled artificial synaptic device with reliable weight update and storage properties for ANNs. The artificial synaptic device, which is based on a ferroelectric polymer capacitively coupled with an oxide dielectric via an electric-field-permeable, semiconducting single-walled carbon-nanotube channel, is successfully fabricated by inkjet printing. By controlling the ferroelectric polarization, synaptic dynamics, such as excitatory and inhibitory postsynaptic currents and long-term potentiation/depression characteristics, is successfully implemented in the artificial synaptic device. Furthermore, the constructed ANN, which is designed in consideration of the device-to-device variation within the synaptic array, efficiently executes the tasks of learning and recognition of the Modified National Institute of Standards and Technology numerical patterns.

Microstructure and properties of low friction TiCC nanocomposite coatings deposited by magnetron sputtering

Artificial light-emitting synaptic devices, serving as the fundamental hardware foundation for building brain-inspired computers and artificial intelligence systems, have made significant strides in achieving high-efficiency, low-power neuromorphic computing by emulating the optoelectronic cooperative plasticity of biological synapses. These devices integrate the high-speed transmission and parallel processing advantages of optical signals with the precise modulation capabilities of electrical signals, offering a revolutionary solution to overcome the “memory wall” bottleneck inherent in traditional von Neumann architectures. This review summarizes the latest research progress in artificial light-emitting synaptic devices, with a focus on analyzing the design principles and performance characteristics of representative devices, including long-afterglow organic light-emitting transistors (LAOLETs), light-emitting electrochemical artificial synapses (LEEASs), quantum dot-based light-emitting synapses, and lightemitting memristors (LEMs). These devices not only successfully replicate core synaptic functionalities such as short-term/long-term plasticity and spike-timing-dependent plasticity (STDP) but also enable integrated information processing and display through dual optoelectronic outputs, laying the hardware groundwork for braininspired intelligent systems that merge sensing, memory, computing, and display functions. Although challenges remain in device stability, large-scale integration, and inhibitory synaptic emulation, artificial lightemitting synaptic devices have demonstrated immense potential in applications such as biomimetic vision and neuromorphic displays. Future advancements in material optimization, structural innovation, and system integration, along with the development of optically reconfigurable synapses and multimodal cooperative modulation technologies, will drive brain-inspired computing hardware toward higher levels of intelligence and adaptability, providing core hardware support for next-generation artificial intelligence systems.

Artificial synaptic devices are the cornerstone of neuromorphic electronics. The development of new artificial synaptic devices and the simulation of biological synaptic computational functions are important tasks in the field of neuromorphic electronics. Although two-terminal memristors and three-terminal synaptic transistors have exhibited significant capabilities in the artificial synapse, more stable devices and simpler integration are needed in practical applications. Combining the configuration advantages of memristors and transistors, a novel pseudo-transistor is proposed. Here, recent advances in the development of pseudo-transistor-based neuromorphic electronics in recent years are reviewed. The working mechanisms, device structures and materials of three typical pseudo-transistors, including tunneling random access memory (TRAM), memflash and memtransistor, are comprehensively discussed. Finally, the future development and challenges in this field are emphasized.

In 1925, P. Auger first observed the so-called Auger electrons in a Wilson cloud chamber. He explained this occurrence as being due to a radiationless transition in atoms excited by a primary x-ray photon source. In 1953, Lander first pointed out that Auger electrons arising from solid samples can be detected in the energy distribution curve of secondary electrons from surfaces subjected to electron bombardment. Moreover, low-energy Auger electrons (∼1 keV kinetic energy) can escape from only the first several atomic layers of a surface since they are strongly absorbed by even a monolayer of atoms. Thus Auger electron spectroscopy (AES) possesses high surface sensitivity. This is one characteristic that makes AES very useful for the study of thin films. For such applications, an important development in AES occurred when Harris showed that the sensitivity of the detection of Auger electrons can be improved by differentiating the electron energy distribution curve with respect to the energy. Furthermore, Weber and Johnson demonstrated that, provided the Auger line profile does not change, the peak-to-peak height in the differentiated energy distribution curves is proportional to the Auger current in the peak. Therefore, in addition to its surface sensitivity, AES also can be used for quantitative studies of thin films.Like AES, x-ray photoelectron spectroscopy (XPS) is a surface-sensitive technique that uses the energy distribution of electrons ejected from a thin film for quantitative analysis. However, in many ways the information provided by AES and XPS is complementary.

Results concerning the calibration and use of a new ultrahigh vacuum (UHV) surface preparation and analysis system are reported. This Sample Preparation Evaluation Analysis and Reaction (SPEAR) side chamber system replaces an older surface side chamber that was attached to a Hitachi UHV H-9000 microscope. The system combines the ability to prepare clean surfaces using sample heating, cooling, ion milling, or thin film growth with surface analytical tools such as Auger electron spectroscopy (AES), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM), along with atomic surface structure information available from high-resolution transmission electron microscopy (HREM). The chemical sensitivity of the XPS and AES are demonstrated in preliminary studies of catalytic and semiconductor samples. In addition, the surface preparation capabilities are also demonstrated for the Si(100) and Ge(100) surfaces, including the ability to acquire secondary electron images during milling. During operation, the entire system is capable of maintaining the UHV conditions necessary for surface studies.