Inho Kim

Transition metal‐based conductive‐bridge RAM offers superior non‐volatility and stable low‐resistance states in the MΩ resistance range compared to noble metal (Ag, Cu) counterparts; however, achieving stable multi‐level operation with low read noise under low‐current conditions remains a critical challenge. This study reports a dual‐material engineering strategy altering filament transport by combining a Ru–Pt alloy electrode with an AlO _x switching layer. Pt incorporation suppresses excessive Ru ion injection, while the low‐defect‐density AlO _x matrix stabilizes filament evolution, leading to a nanocluster‐based conductive pathway rather than a continuous metallic filament. Temperature‐dependent electrical measurements reveal thermally activated hopping conduction (Ea ∼0.44 eV), and current–voltage analysis indicates hopping distances of 1.0–1.9 nm across resistance states, confirming gradual inter‐cluster spacing modulation. This filament structure enables 16 distinct conductance states with reduced read noise over TaO _x ‐ and HfO _x ‐based devices. Incorporated into a convolutional spiking neural network framework, the device achieves 80.97% FMNIST inference accuracy (post‐training quantization only) and ultralow inference energy of 0.817 pJ/inference in the FC layer—roughly three orders of magnitude lower than Ag‐ and Cu‐based ECM systems. These results establish a direct link between materials design, filament physics, and system‐level performance, highlighting dual‐material engineering as a pathway toward energy‐efficient, high‐density analog synaptic devices.

Neural circuits in the retina extract motion direction and velocity through asymmetric dendritic processing, but replicating these computations in solid‐state hardware has not been achieved. Herein, a single multi‐gate ion‐gel graphene transistor (MIG‐GFET) is demonstrated to emulate key operations of the direction‐selective ganglion cell (DSGC) and starburst amacrine cell (SAC) microcircuit. Spatially distributed gates created artificial dendritic compartments whose ionic dynamics enabled nonlinear summation of sequential inputs, yielding intrinsic direction selectivity without algorithmic post‐processing. An oppositely biased inhibitory gate reproduced SAC‐like null‐side inhibition and yielded a band‐pass velocity response with a tunable preferred speed—closely mirroring the spatiotemporal filtering properties underlying direction‐ and speed‐dependent firing in biological DSGCs. This velocity selectivity enables the MIG‐GFET to function as an analog motion filter. By suppressing ego‐motion–induced global scene jitter within a defined frequency band, the device achieves on‐sensor image stabilization with lower latency and power consumption than digital post‐processing. Therefore, dendritic‐level computation can be embedded directly into a graphene transistor, offering a path toward vision hardware where sensing and early neural processing are co‐localized at the device level. This compact, low‐power approach is compatible with focal‐plane array integration and broad applications in real‐time motion analysis.

Recently, transparent superhydrophobic surfaces have attracted significant attention for their potential applications in various optical fields. However, superhydrophobicity is typically associated with surface roughness, which is in contrast to transparency. To achieve both properties simultaneously, a specific surface structure is required, often necessitating patterning processes such as photolithography. In this study, we developed a transparent superhydrophobic surface with a water contact angle greater than 153.7° ± 1.6°, without the need for conventional lithographic patterning processes. The superhydrophobicity was achieved via a two-step process involving nanostructure formation and subsequent surface energy reduction through a self-assembled monolayer coating. We used indium, a low-melting metal that forms island-like deposits, and induced the self-catalytic growth of indium oxide through annealing in a controlled oxygen atmosphere. This approach, which involves the use of low-temperature heat treatment and the omission of patterning steps, has resulted in a straightforward and cost-effective method for fabricating transparent superhydrophobic surfaces. While vacuum deposition and plasma treatment are included, these steps rely on standardized large-area processing systems commonly used in display and photovoltaic industries. The omission of lithography significantly reduces process complexity and capital cost compared to conventional nanoscale structuring methods. The graded-index mechanism induced by the unique InO _x nanoshell structure plays a crucial role in simultaneously enhancing both the optical transparency and the superhydrophobic properties. This results from the gradual variation in refractive index, which aids in preserving transparency while promoting superhydrophobicity. The fabricated transparent superhydrophobic surfaces have promising applicants in self-cleaning, anti-icing, anti-fogging and chemical shielding. Furthermore, our approach results in a visible light transmittance of 93.3% ± 0.1%, nearly identical to that of bare glass, showcasing the excellent transparency of the nanostructured surface.

Monolithic perovskite/silicon tandem (PST) solar cells are rapidly emerging as next‐generation solar cells with significant potential for commercialization. This study presents a proof of concept for a silicon diffused junction‐based PST cell, utilizing a passivated emitter rear contact (PERC) cell with a low‐temperature ( V _oc ) improve from 0.58 V to 0.61 V due to the passivation effect, which reduces silicon surface recombination. Perovskite is passivated using ammonium salts with varying alkyl chain lengths, including n‐Butylammonium bromide, n‐Hexylammonium bromide, and n‐Octylammonium bromide (OABr). OABr is the most effective, increasing the V _oc of the perovskite top cell from 1.18 V to 1.22 V by reducing non‐radiative recombination. The best‐performing PST cell achieves a power conversion efficiency (PCE) of 25.71%, with a current density of 17.62 mA cm ^{− 2} , V _oc of 1.810 V, and fill factor of 80.62%. This represents the highest V _oc and PCE reported for PST cells with PERC‐based p‐type silicon bottom cell technology. Even after 1000 hours of damp heat testing at 85 °C and 85% relative humidity, the device with dual passivation maintained 90.70% of its initial PCE.

A deep understanding of neuronal circuitry connectivity is essential to replicate biological functions effectively. Inferring neural connectivity considers the cross-correlation of spike timing. Neuromorphic systems utilize online learning algorithms that leverage the temporal correlations of spikes by utilizing spiking neural networks. This research demonstrates real-time, large-scale neural connectivity inference by implementing the presynaptic spike-driven spike-timing-dependent plasticity method on neuromorphic hardware. We validate the capability of the proposed method to perform advanced neuron connectivity inference using synthetic data generated from leaky integrate-and-fire neurons on a multi-scale. Additionally, we analyzed that the proposed method exhibits invariant high inference performance in sparse networks without burst firing, regardless of transmission delay. Finally, we demonstrate the feasibility of the proposed method in real-time neural connectivity inference in actual in vitro or in vivo contexts by conducting neural connectivity inference simulating in a way closely mirroring in vitro conditions through fluorescence imaging signal data.

Efficient monolithic perovskite/Si tandem solar cells require a robust recombination junction (RJ) with excellent electrical and optical properties. This study introduces an interface engineering method using an organic sacrificial layer to enable effective monolithic integration. An ultrathin layer of poly(3,4-ethylene-dioxythiophene):polystyrene sulfonate (PEDOT:PSS) is inserted between the transparent conductive oxide recombination layer and the hole transport layer (HTL) of a methylammonium lead iodide (MAPbI₃)-based perovskite top cell. This layer restores junction functionality and enables charge transfer between sub-cells via efficient carrier recombination at the RJ, which electrically connects the two cells. Acting as a sacrificial layer, PEDOT:PSS temporarily prevents resistive SiO _x formation and improves interface quality. High-resolution transmission electron microscopy and X-ray photoelectron spectroscopy confirm suppression of SiO _x growth during HTL annealing. Moreover, the Cu-doped NiO _x HTL fabrication method proves critical, where process optimization improves electrical contact. Combined with PEDOT:PSS interface engineering, these enhancements promote efficient recombination by tuning interfacial energy levels and increasing band bending at the RJ. As a result, tandem devices comprising an aluminum back-surface field p-type homojunction Si bottom cell and a p-i-n perovskite top cell achieve 21.95% power conversion efficiency and an 81.3% fill factor —among the highest reported for monolithic perovskite/Si tandem solar cells.