Enhancement of On-Current and Reliability in InGaZnO Thin-Film Transistors for Synaptic Circuit Applications through Gate Insulator Stack Engineering.

A nanometer-scale multilayer gate insulator (GI) engineering strategy is introduced to simultaneously enhance the on-current and bias stability of amorphous InGaZnO thin-film transistors (a-IGZO TFTs). Atomic layer deposition supercycle modifications employ alternating layers of AlO, TiO, and SiO to optimize the gate-oxide stack. Each GI material is strategically selected for complementary functionalities: AlO improves the interfacial quality at both the GI/semiconductor and GI/metal interfaces, thereby enhancing device stability and performance; TiO increases the overall dielectric constant; and SiO suppresses leakage current by serving as a high-energy barrier between AlO and TiO.

High-Detectivity Organic Photodetector with InP Quantum Dots in PTB7-Th:PCBM Ternary Bulk Heterojunction.

Organic photodetectors (OPDs) offer considerable promise for low-power, solution-processable biosensing and imaging applications; however, their performance remains limited by spectral mismatch and interfacial trap states. In this study, a highly sensitive polymer photodiode was developed via trace incorporation (0.8 wt%) of InP/ZnSe/ZnS quantum dots (QDs) into a PTB7-Th:PCBM bulk heterojunction (BHJ) matrix.

Versatile High-Performance SWNT Electrodes Enabled by Glycerol-Doped PEDOT:PSS Interfacial Engineering.

This paper reports improvements made to the performance of single-walled carbon nanotube (SWNT) electrodes by integrating a glycerol-doped PEDOT:PSS (PEGL) layer, resulting in a novel material termed SWGL. The PEGL layer addresses key challenges in SWNT electrodes, including poor adhesion, low work function, and limited catalytic activity, by acting as an adhesive interface, carrier injection layer, and catalyst. Through a series of spin-coating and rinsing processes, SWGL films are prepared, exhibiting significantly improved adhesion to inorganic substrates, enhanced electrical conductivity, and stability under thermal treatment.

Learning Long-Range Interactions in Equivariant Machine Learning Interatomic Potentials via Electronic Degrees of Freedom.

Machine learning interatomic potentials (MLIPs) provide a computationally efficient alternative to quantum mechanical simulations for predicting material properties. Message-passing graph neural networks, commonly used in these MLIPs, rely on local descriptor-based symmetry functions to model atomic interactions. However, such local descriptor-based approaches struggle with systems exhibiting long-range interactions, charge transfer, and compositional heterogeneity.

A genome-wide study on gene-nutrient interactions for hyperuricemia in a large Korean cohort (KoGES).

This study aimed to identify novel genetic variants associated with hyperuricemia risk across multiple nutrients by assessing significant gene-nutrient interactions using large-scale genome-wide association study (GWAS) data in the Korean population. A total of 48,007 individuals from the Korean Genome and Epidemiology Study dataset were included in the GWAS. Dietary intake was evaluated using a food frequency questionnaire.

Achromatic beam deflector with electrodynamic phased arrays.

Since flat optics has the feature to implement a compact system, they are widely used in various applications to replace bulky refractive optics. However, they suffer from chromatic aberrations due to dispersion, limiting their effectiveness to a narrow wavelength range. Consequently, diffractive optics has been applied for dynamic beam steering within a specific wavelength region or for static steering across multiple wavelengths.

Ferroelectric NAND for efficient hardware bayesian neural networks.

The rapid advancement of artificial intelligence has enabled breakthroughs in diverse fields, including autonomous systems and medical diagnostics. However, conventional deterministic neural networks struggle to capture uncertainty, limiting their reliability when handling real-world data, which are often noisy, imbalanced, or scarce. Bayesian neural networks address this limitation by representing weights as probabilistic distributions, allowing for natural uncertainty quantification and improved robustness.

Enhancement of Efficiency in an Ex Situ Coprecipitation Method for Superparamagnetic Bacterial Cellulose Hybrid Materials.

Superparamagnetic magnetite nanoparticles (FeO) have garnered considerable interest due to their unique magnetic properties and potential for integration into multifunctional biomaterials. In particular, their incorporation into bacterial cellulose (BC) matrices offers a promising route for developing sustainable and high-performance magnetic composites. Numerous studies have explored BC-magnetite systems; however, innovations combining ex situ coprecipitation synthesis within BC matrices, tailored reagent molar ratios, stirring protocols, and purification processes remain limited.

Enhanced Reliability of Ultra-Scaled Interconnects Using Interlayer-Doped Aligned Carbon Nanotube-Metal Composites.

The continuous scaling of electronic devices, coupled with the recent rise of 3D stacked circuits and packaging technology, presents ongoing challenges for today's metal-based interconnects. This study introduces a metal-interlayer-carbon composite as a high-performance alternative to conventional copper-based interconnects, effectively addressing the prevalent issues of increased electrical resistivity and electromigration in scaled-down technology nodes. Initially, the study explores the use of alternative CMOS-compatible metals such as Ruthenium (Ru) and Palladium (Pd), which exhibit better reliability and less electromigration in miniaturized environments compared to copper (Cu).

Boosting Inversion Symmetry Breaking in Epitaxial Tetragonal ZrO Via Atomic Layer Deposition.

The stabilization of intermediate polar phases in fluorite-structured oxides is critical for advancing ferroelectric and antiferroelectric applications. Here, we report the stabilization of epitaxial polar tetragonal (T) ZrO. Epitaxial HfZrO thin films (x = 1, 0.

Efficient Configuration Sampling for Hybrid Functional DFT Calculations to Train Machine-Learning Potentials: Application to Atmospheric Chemistry.

Machine-learning potentials (MLPs), trained to predict energies from quantum chemical calculations, are widely employed to conduct large-scale MD simulations. However, MLPs are mostly trained on computationally inexpensive local/semilocal functionals, as generating training datasets using higher-accuracy theories, such as hybrid functionals, is challenging due to their high computational cost. Here, an active transfer learning scheme is developed to efficiently sample configurations for hybrid functional calculations.

1-nm-thick epitaxial AlN passivation for highly efficient flexible InGaN red micro-LEDs.

Highly efficient, ultrahigh-density inorganic micro-LED displays are gaining a strong position in the market for use in augmented reality glasses. When applied to electronic contact lenses with an eye-adaptive form factor, the micro-LED displays evolve into next generation augmented reality viewers. Here, we report 1-nm-thick epitaxial AlN passivation for 1.

Direct observation of 3D nitrogen distribution in silicon-based dielectrics using atom probe tomography.

The distribution of nitrogen in semiconductor devices plays a crucial role in tuning their physical and electrical properties. However, direct observation and precise quantification of nitrogen remain challenging because of analytical limitations, particularly at critical interfaces in silicon-based semiconductors. Although atom probe tomography has emerged as a powerful tool, distinguishing nitrogen from silicon without isotope doping is persistently difficult.

A scalable neural network emulator with MRAM-based mixed-signal circuits.

In this study, we present a mixed-signal framework that utilizes MRAM (Magneto-resistive Random Access Memory) technology to emulate behaviors observed in biological neural networks on silicon substrates. While modern technology increasingly draws inspiration from biological neural networks, fully understanding these complex systems remains a significant challenge. Our framework integrates multi-bit MRAM synapse arrays and analog circuits to replicate essential neural functions, including Leaky Integrate and Fire (LIF) dynamics, Excitatory and Inhibitory Postsynaptic Potentials (EPSP and IPSP), the refractory period, and the lateral inhibition.

Enhanced Nonvolatile Electrochemical Random-Access Memory and Artificial Synapse Characteristics through Oxygen Ion-Exchange Engineering in an Atomic-Layer-Deposited HfO Gate Insulator and a Zinc Oxide Channel Layer.

Enhanced nonvolatile memory and artificial synapse characteristics are achieved in oxygen ion-based ECRAM consisting of a low-temperature atomic layer-deposited (ALD) oxygen-deficient hafnium oxide (HfO) ion-exchange layer and zinc oxide (ZnO) channel layer. The drain current modulation of the device reaches a few orders of magnitude upon application of positive programming and negative erasing gate bias. Also, the device exhibits nonvolatile retention of modulated current up to >10 higher than the initial value for 24 h.

Diindolocarbazole as a Core Structure for Narrow-Emitting and Highly Efficient Blue Organic Light-Emitting Diodes.

In this study, a molecular design approach inducing high efficiency and narrow emission in blue organic light-emitting diodes (OLEDs) using indolocarbazole and diindolocarbazole backbone structures are proposed. The indolocarbazole and diindolocarbazole backbone structures are used as a core structure and the indole is protected with spiro configured fluorene for rigidity and suppressed intermolecular interaction. The indolocarbazole and diindolocarbazole derived compounds show multiple resonance-thermally activated delayed fluorescence emission even without any electron deficient unit within the molecular structure and narrow emission spectrum with a full width at half maximum (FWHM) of less than 20 nm.

Genome-wide approach to study gene-nutrient intake interactions in type 2 diabetes mellitus in a large Korean cohort.

Introduction: A comprehensive understanding of gene-diet interactions is necessary to establish proper dietary guidelines for the prevention and management of type 2 diabetes mellitus (T2DM). We examined the roles of genetic variants and their interactions with T2DM-associated nutrients in a large-scale genome-wide association study of Korean adults.

Methods: A total of 50,808 participants from a Korean genome and epidemiology study were included.

Disturbance-Aware On-Chip Training with Mitigation Schemes for Massively Parallel Computing in Analog Deep Learning Accelerator.

On-chip training in analog in-memory computing (AIMC) holds great promise for reducing data latency and enabling user-specific learning. However, analog synaptic devices face significant challenges, particularly during parallel weight updates in crossbar arrays, where non-uniform programming and disturbances often arise. Despite their importance, the disturbances that occur during training are difficult to quantify based on a clear mechanism, and as a result, their impact on training performance remains underexplored.

Accelerating ion transport in polycrystalline conductors: On pores and grain boundaries.

Polycrystalline ion conductors are widely used as solid electrolytes in energy storage technologies. However, they often exhibit poor ion transport across grain boundaries and pores. This work demonstrates that strategically tuning the mesoscale microstructures, including pore size, pore distribution, and chemical compositions of grain boundaries, can improve ion transport.

Sub-4 nanometer porous membrane enables highly efficient electrodialytic fractionation of dyes and inorganic salts.

During the synthesis of dyes, desalination of high-salinity dye-containing waste liquor is a critical premise for high-quality, clean dye production. Conventional membrane processes, such as electrodialysis, nanofiltration and ultrafiltration, are inevitably subjected to serious membrane fouling, deteriorating the dye/salt fractionation efficacy. Integrating the technical merits of electrodialysis and pressure-driven membrane separation, we devise an electro-driven filtration process using a tight ultrafiltration membrane as alternative to conventional anion exchange membrane for rapid anion transfer, in view of dye desalination and purification.

Analytical and empirical correlation between magnetic domain wall creep behavior and fundamental magnetic properties.

Magnetic domain walls (DWs) often exhibit creep motion, a form of collective dynamics observed in weak magnetic fields. In this study, we investigate the correlation between magnetic DW creep behavior and fundamental magnetic properties through analytical analysis and experimental demonstration. Specifically, we examined DW creep motion in a series of Pt/Co/X heterostructures, where X represents various non-magnetic layers (Ta, Ti, Ru, and Au) that are critical for inducing magnetic chirality.

Resetting the Drift of Oxygen Vacancies in Ultrathin HZO Ferroelectric Memories by Electrical Pulse Engineering.

Ferroelectric HfO-based films incorporated in nonvolatile memory devices offer a low-energy, high-speed alternative to conventional memory systems. Oxygen vacancies have been rigorously cited in literature to be pivotal in stabilizing the polar noncentrosymmetric phase responsible for ferroelectricity in HfO-based films. Thus, the ability to regulate and control oxygen vacancy migration in operando in such materials would potentially offer step changing new functionalities, tunable electrical properties, and enhanced device lifespan.

Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop.

In synthesis planning, identifying and optimizing chemical reactions are important for the successful design of synthetic pathways to target substances. Chemical reaction databases assist chemists in gaining insights into this process. Traditionally, searching for relevant records from a reaction database has relied on the manual formulation of queries by chemists based on their search purposes, which is challenging without explicit knowledge of what they are searching for.

Disorder-driven sintering-free garnet-type solid electrolytes.

Oxide ceramic electrolytes for realization of high-energy lithium metal batteries typically require high-temperature processes to achieve the desired phase formation and inter-particle sintering. However, such high-temperature processing can lead to compositional changes or mechanical deformation, compromising material reliability. Here, we introduce a disorder-driven, sintering-free approach to synthesize garnet-type solid electrolyte via the creation of an amorphous matrix followed by a single-step mild heat-treatment.

Analysis of the Ambipolar Conduction of Tin Monoxide Thin-Film Transistors with Indium Tin Oxide Electrodes.

This study investigates the hole and electron conduction properties of thin-film transistors (TFTs) with a tin monoxide (SnO) channel and indium tin oxide (ITO) source/drain (S/D) electrodes, considering the adoption to three-dimensional (3D) NAND Flash. Compared to SnO TFTs with gold (Au) S/D electrodes, significant enhancement of electron conduction was observed when adopting ITO S/D electrodes. The ITO electrodes decreased the Schottky barrier height for electron injection, enhancing electron conduction and consequently inducing ambipolar conduction behavior.