Real-time Neural Connectivity Inference with Presynaptic Spike-driven Spike Timing-Dependent Plasticity.

Brain-like artificial intelligence in electronics can be built efficiently by understanding the connectivity of neuronal circuitry. The concept of neural connectivity inference with a two-dimensional cross-bar structure memristor array is indicated in recent studies; however, large-scale implementation is challenging owing to device variations and the requirement of online parameter adaptation. This study proposes a neural connectivity inference method with one-dimensional spiking neurons using spike timing-dependent plasticity and presynaptic spike-driven spike timing-dependent plasticity learning rules, designed for a large-scale neuromorphic system. The proposed learning process decreases the number of spiking neurons by half. We simulate 12 ground-truth neural networks comprising one-dimensional eight and 64 neurons. We analyze the correlation between the neural connectivity of the ground truth and spiking neural networks using the Matthews correlation coefficient. In addition, we analyze the sensitivity and specificity of inference. Validation using the presynaptic spike-driven spike timing-dependent plasticity learning rule implies a potential approach for large-scale neural network inference with real hardware realization of large-scale neuromorphic systems.

Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing.

Memristors, or memristive devices, have attracted tremendous interest in neuromorphic hardware implementation. However, the high electric-field dependence in conventional filamentary memristors results in either digital-like conductance updates or gradual switching only in a limited dynamic range. Here, we address the switching parameter, the reduction probability of Ag cations in the switching medium, and ultimately demonstrate a cluster-type analogue memristor. Ti nanoclusters are embedded into densified amorphous Si for the following reasons: low standard reduction potential, thermodynamic miscibility with Si, and alloy formation with Ag. These Ti clusters effectively induce the electrochemical reduction activity of Ag cations and allow linear potentiation/depression in tandem with a large conductance range (~244) and long data retention (~99% at 1 hour). Moreover, according to the reduction potentials of incorporated metals (Pt, Ta, W, and Ti), the extent of linearity improvement is selectively tuneable. Image processing simulation proves that the Ti4.8%:a-Si device can fully function with high accuracy as an ideal synaptic model.

Three-Terminal Ovonic Threshold Switch (3T-OTS) with Tunable Threshold Voltage for Versatile Artificial Sensory Neurons.

Inspired by information processing in biological systems, sensor-combined edge-computing systems attract attention requesting artificial sensory neurons as essential ingredients. Here, we introduce a simple and versatile structure of artificial sensory neurons based on a novel three-terminal Ovonic threshold switch (3T-OTS), which features an electrically controllable threshold voltage (Vth). Combined with a sensor driving an output voltage, this 3T-OTS generates spikes with a frequency depending on an external stimulus. As a proof of concept, we have built an artificial retinal ganglion cell (RGC) by combining a 3T-OTS and a photodiode. Furthermore, this artificial RGC is combined with the reservoir-computing technique to perform a classification of chest X-ray images for normal, viral pneumonia, and COVID-19 infections, releasing the recognition accuracy of about 86.5%. These results indicate that the 3T-OTS is highly promising for applications in neuromorphic sensory systems, providing a building block for energy-efficient in-sensor computing devices.

Bottom-Up Evolution of Diamond-Graphite Hybrid Two-Dimensional Nanostructure: Underlying Picture and Electrochemical Activity.

The diamond-graphite hybrid thin film with low-dimensional nanostructure (e.g., nitrogen-included ultrananocrystalline diamond (N-UNCD) or the alike), has been employed in many impactful breakthrough applications. However, the detailed picture behind the bottom-up evolution of such intriguing carbon nanostructure is far from clarified yet. Here, the authors clarify it, through the concerted efforts of microscopic, physical, and electrochemical analyses for a series of samples synthesized by hot-filament chemical vapor deposition using methane-hydrogen precursor gas, based on the hydrogen-dependent surface reconstruction of nanodiamond and on the substrate-temperature-dependent variation of the growth species (atomic hydrogen and methyl radical) concentration near substrate. The clarified picture provides insights for a drastic enhancement in the electrochemical activities of the hybrid thin film, concerning the detection of important biomolecule, that is, ascorbic acid, uric acid, and dopamine: their limits of detections are 490, 35, and 25 nm, respectively, which are among the best of the all-carbon thin film electrodes in the literature. This work also enables a simple and effective way of strongly enhancing AA detection.

Spiking Neural Network (SNN) With Memristor Synapses Having Non-linear Weight Update.

Among many artificial neural networks, the research on Spike Neural Network (SNN), which mimics the energy-efficient signal system in the brain, is drawing much attention. Memristor is a promising candidate as a synaptic component for hardware implementation of SNN, but several non-ideal device properties are making it challengeable. In this work, we conducted an SNN simulation by adding a device model with a non-linear weight update to test the impact on SNN performance. We found that SNN has a strong tolerance for the device non-linearity and the network can keep the accuracy high if a device meets one of the two conditions: 1. symmetric LTP and LTD curves and 2. positive non-linearity factors for both LTP and LTD. The reason was analyzed in terms of the balance between network parameters as well as the variability of weight. The results are considered to be a piece of useful prior information for the future implementation of emerging device-based neuromorphic hardware.

A 2D material-based floating gate device with linear synaptic weight update.

Neuromorphic computing is of great interest among researchers interested in overcoming the von Neumann computing bottleneck. A synaptic device, one of the key components to realize a neuromorphic system, has a weight that indicates the strength of the connection between two neurons, and updating this weight must have linear and symmetric characteristics. Especially, a transistor-type device has a gate terminal, separating the processes of reading and updating the conductivity, used as a synaptic weight to prevent sneak path current issues during synaptic operations. In this study, we fabricate a top-gated flash memory device based on two-dimensional (2D) materials, MoS2 and graphene, as a channel and a floating gate, respectively, and Al2O3 and HfO2 to increase the tunneling efficiency. We demonstrate the linear weight updates and repeatable characteristics of applying negative/positive pulses, and also emulate spike timing-dependent plasticity (STDP), one of the learning rules in a spiking neural network (SNN).

Reversible switching mode change in Ta2O5-based resistive switching memory (ReRAM).

We report the complementary resistive switching (CRS) behaviors in a tantalum-oxide based resistive switching memory device that reversibly changes its switching mode between bipolar switching (BRS) and CRS in a single memory cell depending on the operation (compliance current) and fabrication (oxygen scavenger layer thickness) conditions. In addition, the origin of the switching mode transition was investigated through electrical and optical measurement, where the conductance is believed to be determined by two factors: formation of conductive filament and modulation of Schottky barrier. This result helps design a resistive switching device with desirable and stable switching behavior.

Random nanohole arrays and its application to crystalline Si thin foils produced by proton induced exfoliation for solar cells.

We report high efficiency cell processing technologies for the ultra-thin Si solar cells based on crystalline Si thin foils (below a 50 µm thickness) produced by the proton implant exfoliation (PIE) technique. Shallow textures of submicrometer scale is essential for effective light trapping in crystalline Si thin foil based solar cells. In this study, we report the fabrication process of random Si nanohole arrays of ellipsoids by a facile way using low melting point metal nanoparticles of indium which were vacuum-deposited and dewetted spontaneously at room temperature. Combination of dry and wet etch processes with indium nanoparticles as etch masks enables the fabrication of random Si nanohole arrays of an ellipsoidal shape. The optimized etching processes led to effective light trapping nanostructures comparable to conventional micro-pyramids. We also developed the laser fired contact (LFC) process especially suitable for crystalline Si thin foil based PERC solar cells. The laser processing parameters were optimized to obtain a shallow LFC contact in conjunction with a low contact resistance. Lastly, we applied the random Si nanohole arrays and the LFC process to the crystalline Si thin foils (a 48 µm thickness) produced by the PIE technique and achieved the best efficiency of 17.1% while the planar PERC solar cell without the Si nanohole arrays exhibit 15.6%. Also, we demonstrate the ultra-thin wafer is bendable to have a 16 mm critical bending radius.

Thin Ag Precursor Layer-Assisted Co-Evaporation Process for Low-Temperature Growth of Cu(In,Ga)Se2 Thin Film.

Achieving favorable band profile in low-temperature-grown Cu(In,Ga)Se2 thin films has been challenging due to the lack of thermal diffusion. Here, by employing a thin Ag precursor layer, we demonstrate a simple co-evaporation process that can effectively control the Ga depth profile in CIGS films at low temperature. By tuning the Ag precursor thickness (∼20 nm), typical V-shaped Ga gradient in the copper indium gallium diselenide (CIGS) film could be substantially mitigated along with increased grain sizes, which improved the overall solar cell performance. Structural and compositional analysis suggests that formation of liquid Ag-Se channels along the grain boundaries facilitates Ga diffusion and CIGS recrystallization at low temperatures. Formation of a fine columnar grain structure in the first evaporation stage was beneficial for subsequent Ga diffusion and grain coarsening. Compared to the modified co-evaporation process where the Ga evaporation profile has been directly tuned, the Ag precursor approach offers a convenient route for absorber engineering and is potentially more applicable for roll-to-roll fabrication system.

Enhanced efficiency of crystalline Si solar cells based on kerfless-thin wafers with nanohole arrays.

Several techniques have been proposed for kerfless wafering of thin Si wafers, which is one of the most essential techniques for reducing Si material loss in conventional wafering methods to lower cell cost. Proton induced exfoliation is one of promising kerfless techniques due to the simplicity of the process of implantation and cleaving. However, for application to high efficiency solar cells, it is necessary to cope with some problems such as implantation damage removal and texturing of (111) oriented wafers. This study analyzes the end-of-range defects at both kerfless and donor wafers and ion cutting sites. Thermal treatment and isotropic etching processes allow nearly complete removal of implantation damages in the cleaved-thin wafers. Combining laser interference lithography and a reactive ion etch process, a facile nanoscale texturing process for the kerfless thin wafers of a (111) crystal orientation has been developed. We demonstrate that the introduction of nanohole array textures with an optimal design and complete damage removal lead to an improved efficiency of 15.2% based on the kerfless wafer of a 48 µm thickness using the standard architecture of the Al back surface field.

Scalable excitatory synaptic circuit design using floating gate based leaky integrators.

We propose a scalable synaptic circuit realizing spike timing dependent plasticity (STDP)-compatible with randomly spiking neurons. The feasible working of the circuit was examined by circuit simulation using the BSIM 4.6.0 model. A distinguishable feature of the circuit is the use of floating-gate integrators that provide the compact implementation of biologically plausible relaxation time scale. This relaxation occurs on the basis of charge tunneling that mainly relies upon area-independent tunnel barrier properties (e.g. barrier width and height) rather than capacitance. The circuit simulations feature (i) weight-dependent STDP that spontaneously limits the synaptic weight growth, (ii) competitive synaptic adaptation within both unsupervised and supervised frameworks with randomly spiking neurons. The estimated power consumption is merely 34 pW, perhaps meeting one of the most crucial principles (power-efficiency) of neuromorphic engineering. Finally, a means of fine-tuning the STDP behavior is provided.

Electrical analysis of c-Si/CGSe monolithic tandem solar cells by using a cell-selective light absorption scheme.

A monolithic tandem solar cell consisting of crystalline Si (c-Si)/indium tin oxide (ITO)/CuGaSe2 (CGSe) was demonstrated by stacking a CGSe solar cell on a c-Si/ITO solar cell to obtain a photovoltaic conversion efficiency of about 10%. Electrical analyses based on cell-selective light absorption were applied to individually characterize the photovoltaic performances of the top and bottom subcells. Illumination at a frequency that could be absorbed only by a targeted top or bottom subcell permitted measurement of the open-circuit voltage of the target subcell and the shunt resistance of the non-target subcell. The cell parameters measured from each subcell were very similar to those of the corresponding single cell, confirming the validity of the suggested method. In addition, separating the light absorption intensities at the top and bottom subcells made us measure the bias-dependent photocurrent for each subcell. The series resistance of a c-Si/ITO/CGSe cell subjected to bottom-cell limiting conditions was slightly large, implying that the tunnel junction was a little resistive or slightly beyond ohmic. This analysis demonstrated that aside from producing a slightly resistive tunnel junction, our fabrication processes were successful in monolithically integrating a CGSe cell onto a c-Si/ITO cell without degrading the performances of both cells.

Chameleonic electrochemical metallization cells: dual-layer solid electrolyte-inducing various switching behaviours.

We present 'unusual' resistive switching behaviours in electrochemical metallization (ECM) cells utilizing a dual-layer (SiOx/GeSex: SiOx on GeSex) solid electrolyte (SE). The observed switching behaviour markedly varies with the thickness of the upper SiOx layer and compliance current: (i) monostable switching, (ii) counter-eightwise bipolar switching, and (iii) combination of monostable and eightwise bipolar switching behaviours. Focusing on cases (i) and (iii), electrical and chemical analyses on these chameleonic cells were performed in an attempt to gain clues to the understanding of the observed complexity. The chemical analysis indicated the upper SiOx layer as a chemical potential well for Cu ions-Cu ions were largely confined in the well. This non-uniform distribution of Cu across the SE perhaps hints at the mechanism for the complex behaviour; it may be a 'zero-sum game' between SiOx and GeSex layers, in which the two layers fight over the limited number of Cu atoms/ions.

Inherently-Forced Tensile Strain in Nanodiamond-Derived Onion-like Carbon: Consequences in Defect-Induced Electrochemical Activation.

We analyzed the nanodiamond-derived onion-like carbon (OLC) as function of synthesis temperature (1000~1400 °C), by high-resolution electron microscopy, electron energy loss spectroscopy, visible-Raman spectroscopy, ultraviolet photoemission spectroscopy, impedance spectroscopy, cyclic voltammetry and differential pulse voltammetry. The temperature dependences of the obtained properties (averaged particle size, tensile strain, defect density, density of states, electron transfer kinetics, and electrochemical oxidation current) unanimously coincided: they initially increased and saturated at 1200 °C. It was attributed to the inherent tensile strains arising from (1) the volume expansion associated with the layer-wise diamond-to-graphite transformation of the core, which caused forced dilation of the outer shells during their thermal synthesis; (2) the extreme curvature of the shells. The former origin was dominant over the latter at the outermost shell, of which the relevant evolution in defect density, DOS and electron transfer kinetics determined the electrochemical performances. In detection of dopamine (DA), uric acid (UA) and ascorbic acid (AA) using the OLC as electrode, their oxidation peak currents were enhanced by factors of 15~60 with annealing temperature. Their limit of detection and the linear range of detection, in the post-treatment-free condition, were as excellent as those of the nano-carbon electrodes post-treated by Pt-decoration, N-doping, plasma, or polymer.

Characterization of efficiency-limiting resistance losses in monolithically integrated Cu(In,Ga)Se2 solar modules.

The cell-to-module efficiency gap in Cu(In,Ga)Se2 (CIGS) monolithically integrated solar modules is enhanced by contact resistance between the Al-doped ZnO (AZO) and Mo back contact layers, the P2 contact, which connects adjacent cells. The present work evaluated the P2 contact resistance, in addition to the TCO resistance, using an embedded transmission line structure in a commercial-grade module without using special sample fabrication methods. The AZO layers between cells were not scribed; instead, the CIGS/CdS/i-ZnO/AZO device was patterned in a long stripe to permit measurement of the Mo electrode pair resistance over current paths through two P2 contacts (Mo/AZO) and along the AZO layer. The intercept and slope of the resistance as a function of the electrode interval yielded the P2 contact resistance and the TCO resistance, respectively. Calibration of the parasitic resistances is discussed as a method of improving the measurement accuracy. The contribution of the P2 contact resistance to the series resistance was comparable to that of the TCO resistance, and its origin was attributed to remnant MoSe2 phases in the P2 region, as verified by transmission electron microscopy.

Properties of ZnO thin films co-doped with hydrogen and fluorine.

ZnO films co-doped with fluorine and hydrogen were prepared on Corning glass by radio frequency magnetron sputtering of ZnO targets with varying amounts of ZnF2 in H2/Ar gas mixtures of varying H2 content. The ZnO films' electrical, optical, and structural properties in combination with their compositional properties were investigated. A small addition of H2 to the sputtering gas caused a drastic increase of Hall mobility with a marginal increase in carrier concentration, indicating an effective passivation of grain boundaries due to hydrogenation. For further increase of H2 in sputter gas, the Hall mobility remained at a relatively constant level while the carrier concentration increased steadily. Most of the ZnO films co-doped with fluorine and hydrogen showed average transmittance higher than 83% in the 400-800 nm range, while the average absorption coefficients were lower than 600 cm(-1), implying very low absorption loss in these films. It was discovered that the fabrication of ZnO films with a Hall mobility higher than 40 cm2/Vs and a very low absorption loss in the visible range is possible by co-doping hydrogen and fluorine.

The effects of nitrogen bonding on hardness of AIN/CrN multilayer hard coatings.

AIN/CrN multilayer hard coatings with various bilayer thicknesses were fabricated by a reactive sputtering process. The microstructural and mechanical characterizations of multilayer coatings were investigated through transmission electron microscope (TEM) observations and the hardness measurements by nano indentation. In particular, the variation of chemical bonding states of the bilayer nitrides was elucidated by near edge X-ray absorption fine structure (NEXAFS) spectroscopy. Many broken nitrogen bonds were formed by decreasing the bilayer thickness of AIN/CrN multilayer coatings. Existence of optimum AIN/CrN multilayer coatings thickness for maximum hardness could be explained by the competition of softening by the formation of broken nitrogen bonds and strengthening induced by decreasing bilayer thickness.

Hardness and nitrogen bonding structure of AlxTi1-xN/CrN multilayer hard coating.

AlxTi1-xN/CrN multilayer coatings were fabricated by magnetron sputtering and those hardness variations were studied by observing the crack propagation and measuring the chemical bonding state of nitrides by Ti addition. While AlN/CrN multilayer shown stair-like crack propagation, AlxTi1-xN/CrN multilayer illustrated straight crack propagation. Most interestingly, Ti addition induced more broken nitrogen bonds in the nitride multilayers, leading to the reduction of hardness. However, the hardness of Al0.25Ti0.75N/CrN multilayer, having high Ti contents, increased by the formation of many Ti-N bond again instead of Al-N bond. From these results, we found that linear crack propagation behavior was dominated by broken nitrogen bonds in the AlxTi1-xN/CrN multilayer coatings.