The ability to manipulate and probe biomolecules at the single-molecule level has become an essential approach for understanding molecular interactions, conformational dynamics, and nanoscale transport phenomena. Advances in experimental techniques have enabled precise control of individual molecules with high spatial resolution and piconewton-level force sensitivity. These developments have significantly expanded the capability of studying biomolecular mechanics and dynamics beyond conventional ensemble measurements. A variety of physical strategies have been developed for single-molecule manipulation, including mechanical-force-based approaches, electric-field-driven methods, and nanoscale structural confinement techniques. Mechanical-force-based methods, such as optical tweezers, magnetic tweezers, and atomic force microscopy, enable direct measurement of molecular mechanical responses. Electric-field-based manipulation, represented by dielectrophoresis, allows noncontact control of particles and biomolecules through polarization effects in non-uniform electric fields. In addition, nanopore-based systems employ nanoscale confinement to regulate molecular transport and residence behavior. This review provides an overview of representative single-molecule manipulation techniques based on mechanical, electrical, and structural control and discusses their fundamental principles and implementation strategies.
The rapid advancement of large-scale language models and artificial intelligence technologies has highlighted the importance of data processing efficiency. This study outlines a measurement optimization method for high-speed pulse equipment to accurately analyze the operating dynamics of ReRAM, a core hardware component for simulating neural networks. An optimized evaluation methodology combining connection compensation and a dual-channel configuration was established to minimize measurement errors caused by parasitic resistance and capacitance during pulse measurements using the Keithley 4200A-SCS and 4225-PMU modules, and to address HRS/LRS measurement errors caused by mismatches between the measurement range and source limits. The proposed precision measurement guidelines can be applied to the evaluation of semiconductor devices that require pulse measurements, such as transistors and DRAM.
GaN nanowire (NW)-based hybrid structures have attracted attention for optoelectronic applications due to their high surface area and efficient carrier transport. However, the optical transparency of GaN NWs is often limited by unintended residual species accumulated on the surface and in the inter-wire regions, as well as defect-related absorption, leading to reduced light transmission. In this work, we demonstrate that thermal annealing significantly improves the optical transparency of GaN NWs grown on indium tin oxide (ITO)/glass substrates. The transmittance increased from 47.9% to 78.5% at 550 nm after rapid thermal annealing at 800oC for 3 min, while a comparable value (~75.5%) was achieved at 600oC for 5 min. PbBr3 was deposited onto the GaN NWs to form hybrid structures, and temperature-dependent photoluminescence (TDPL) measurements revealed enhanced emission stability with suppressed peak shift and reduced spectral broadening. Arrhenius analysis based on a two-channel model revealed that the activation energy of the dominant non-radiative recombination pathway increased from 62 meV in the as-grown sample to 85 meV after thermal annealing, while its relative contribution remained nearly unchanged. In contrast, the shallow trap-assisted pathway exhibited a similar activation energy of approximately 6 meV in both samples, but its contribution decreased from 0.35 to 0.17 after annealing. As a result, the internal quantum efficiency (IQE) improved from 75.9% to 87.4%. These results show that thermal annealing improves optical transparency by removing residuals and suppresses defect-related recombination, leading to enhanced carrier dynamics and improved optical performance of PbBr3-based hybrid structures.
Polymer nanocomposites incorporating inorganic nanofillers have emerged as highly promising electromagnetic interference (EMI) shielding materials, combining mechanical compliance with robust conductive percolation networks. Carbon nanotubes (CNTs) are particularly attractive as conductive fillers because their high aspect ratio facilitates percolation at low loadings. Also, CNTs offer superior mechanical durability under deformation compared to rigid, fracture-prone metal nanowires. For EMI shielding, high electrical conductivity is critical as it enhances both reflection and absorption through efficient charge dissipation and conduction losses. However, achieving highly aligned conductive pathways without degrading the intrinsic electrical properties of CNTs remains a significant challenge. Here, we demonstrate a non-destructive magnetic surface-functionalization and alignment strategy. Using a polydopamine (PDA)-mediated route, pristine multiwalled CNTs are uniformly decorated with Fe3O4 nanoparticles (FMWCNTs). This enables highly effective magnetic field-driven alignment at fields as low as 10 mT, promoting the strategic formation of percolation networks. By optimizing the Fe₃O₄/MWCNT ratio for high saturation magnetization and uniform coverage, the aligned FMWCNTs exhibit significant electrical anisotropy, delivering a 10.7-fold higher electrical conductivity in the parallel configuration compared to the vertical configuration. These findings present a scalable, room-temperature platform for engineering directionally enhanced conductivity in polymer nanocomposites, with broad applicability in advanced EMI shielding, flexible electronics, and advanced packaging technologies.
β-Ga2O3 is an ultra-wide bandgap semiconductor promising for high-power electronic applications; however, heteroepitaxial growth on sapphire is challenging lattice and symmetry mismatch. In this study, β-Ga2O3 thin films were grown on C-plane sapphire substrates with various off-axis angles (0–12°) using mist-CVD, and the influence of substrate miscut on structural and optical properties was investigated. All films grown at 900°C exhibited (-201) oriented β phase. The crystal quality was strongly dependent on the off-axis angle, with intermediate off-axis angles (Δa = 6–8°) showing the narrowest rocking curve width. Off-axis substrates promoted step-aligned growth behavior compared to on-axis growth. Optical measurements revealed enhanced transmittance and wider bandgap values (4.92–4.95 eV) for off-axis samples compared to the on-axis film (4.69 eV). The findings provide practical guidelines for optimizing heteroepitaxial β-Ga2O3 growth on low-cost sapphire substrates for high-performance device applications.
This paper proposes a circular sequential lighting control method to reduce current imbalance and luminance deviation among multiple LED modules in AC-powered LED lighting systems. Conventional fixed-sequence lighting control repeatedly prioritizes the same LED modules in every rectified voltage cycle, which leads to unequal current distribution, luminance non-uniformity, and the accelerated degradation of specific modules during long-term operation. To address these limitations, a circular sequential lighting strategy is introduced, in which the lighting order is cyclically rotated at every rectified cycle, ensuring that all LED modules experience equal lighting opportunities. A prototype AC-LED lighting system consisting of four series-connected LED modules was implemented and experimentally evaluated. The results demonstrate that, while the conventional fixed-sequence method produces a maximum average current deviation of up to 1.6 mA among modules, the proposed method equalizes the average current across all modules to approximately 17.1 mA. Furthermore, the flicker index remains at 0.13, which is comparable to that of the conventional method, indicating that luminance uniformity is improved without degradation of optical performance. The proposed circular sequential lighting control effectively distributes electrical stress, enhances luminance uniformity, and improves long-term reliability, making it a practical and efficient solution for high-quality AC-LED lighting applications.
Organic solar cells based on bulk heterojunction (BHJ) structures have attracted considerable attention because of their low fabrication cost, mechanical flexibility, and compatibility with solution-processing techniques. In BHJ organic photovoltaic devices, nanoscale morphology and crystallinity of the photoactive layer critically influence photovoltaic performance. In this study, the effects of solvent selection and thermal annealing on crystallization evolution and photovoltaic characteristics of P3HT:PCBM organic solar cells were systematically investigated. Three different solvents, including toluene, chlorobenzene (CB), and dichlorobenzene (DCB), were employed for active-layer fabrication, followed by post-thermal annealing treatment. UV–visible absorption spectroscopy revealed solvent-dependent differences in molecular ordering and intermolecular π–π interactions within the active layer. X-ray diffraction analysis confirmed that thermal annealing significantly enhanced crystallinity and lamellar ordering of P3HT domains, particularly for CB-processed films. Electrical characterization demonstrated that solvent evaporation behavior strongly affects photovoltaic performance. Among the investigated devices, the thermally annealed CB-processed device exhibited the highest power conversion efficiency of 1.83% with an enhanced short-circuit current density of 7.057 mA cm⁻². The improved device performance is attributed to optimized crystallization behavior and balanced nanoscale phase separation induced by the moderate evaporation characteristics of CB. In contrast, although DCB-assisted films exhibited relatively strong optical absorption and enhanced crystallinity, excessively slow solvent evaporation likely induced excessive aggregation and coarse phase separation, limiting efficient photovoltaic characteristics. These results demonstrate that solvent engineering combined with thermal annealing is an effective strategy for controlling morphology evolution and crystallization behavior in P3HT:PCBM bulk heterojunction solar cells.
Metamaterials, as artificially engineered structures with unconventional mechanical and acoustic properties, have recently emerged as a transformative platform for enhancing the capabilities of triboelectric nanogenerator (TENG) systems. Since the invention of TENG devices, extensive efforts have been devoted to improving charge density, output stability, and overall performance. Conventional performance optimization strategies mainly rely on device-level improvements such as surface chemistry modification, microstructuring, and nanopatterning. However, limited emphasis has been given to system-level development of smart self-powered intelligent systems. The integration of metamaterials into TENG devices opens a new era by enabling frequency-selective localization, mechanical impedance matching, and controllable deformation pathways. These engineered mechanical structures not only improve energy harvesting efficiency but also introduce new functionalities into the system. This review systematically summarizes recent advances in metamaterial-integrated TENG systems across four major application domains: (i) energy harvesting, (ii) acoustic telecommunication and acoustic-to-electric conversion, (iii) self-powered sensing, and (iv) vibration suppression and monitoring. Overall, the integration of metamaterials into TENG systems will pave the way for next-generation sustainable, intelligent, self-powered devices with diverse functionalities.
The expansion of smart healthcare and wearable electronics has intensified the need for fabric-based sensors that integrate conformally with the human body for continuous bio signal monitoring. However, the heavy reliance of conventional devices on external batteries remains a major obstacle to commercialization, necessitating the development of flexible piezoelectric energy harvesters that convert biomechanical energy into sustainable power. Here, we present a highly flexible and wearable piezoelectric energy harvester (PEH) fabricated by a screen-printing of BaTiO3 nanoparticlePDMS composites onto a fabric substrate. An optimized piezo-ceramic filler concentration of 70 wt% yielded a peak output voltage of 0.52 V and a current of 40 nA under the mechanical bending deformations. The fabricated PEH demonstrated exceptional mechanical and electrical stability, showing no performance degradation of over 5,000 repetitive bending cycles. These results indicate that a PEH can function as a stable self-powered source within complex clothing environments, offering a promising pathway for next-generation autonomous wearable sensor systems.
Dye adsorption is one of the most time-consuming processes in the fabrication of dye-sensitized solar cells (DSSCs), typically requiring approximately 24 h at room temperature. In this study, the effect of adsorption temperature and time on photovoltaic performance of DSSCs was investigated in order to reduce processing time and improve device productivity. Nanoporous TiO2 photoelectrodes were immersed in N719 dye solution at 60°C for 3 h, 10 h, 17 h, and 24 h, and their performance was compared with that of cells sensitized at room temperature for 24 h. Photovoltaic characterization under AM 1.5 illumination showed that DSSCs sensitized at 60°C exhibited improved performance compared to those sensitized at room temperature. The device sensitized at 60°C for 3 h showed comparable or higher conversion efficiency than the reference cell sensitized for 24 h at room temperature. The improvement in device performance is attributed to enhanced dye adsorption kinetics resulting from increased reaction rate between the carboxyl groups of N719 dye molecules and hydroxyl groups on the TiO2 surface. Electrochemical impedance spectroscopy analysis revealed reduced recombination resistance at the TiO2/dye/electrolyte interface for cells sensitized at elevated temperature. UV–Vis absorption analysis confirmed increased dye loading on the TiO2 surface for the 60°C condition. These results demonstrate that elevated temperature dye adsorption significantly reduces processing time while maintaining photovoltaic performance, providing an effective strategy for improving manufacturing efficiency of DSSCs.
With the rapid expansion of electric vehicles (EVs) and energy storage systems (ESS), ensuring the operational safety of lithium-ion batteries has become a critical technical challenge. Conventional battery management systems (BMS) primarily rely on threshold-based rule logic, which is limited in detecting coupled anomalies and early-stage degradation patterns. In this study, a deep learning-based framework for multivariate anomaly detection is proposed using BMS sensor data, including voltage, current, temperature, state of charge (SOC), and state of health (SOH). Five representative fault scenarios were defined, including thermal runaway precursors, cell voltage imbalance, SOC inconsistency, internal resistance increase, and communication delay. The proposed CNN-LSTM model was compared with conventional Rule-based methods and machine learning models, including Isolation Forest, Autoencoder, and LSTM. Experimental results show that the proposed model achieved the highest performance, with an F1-score of 0.885, an AUC of 0.94, and a detection delay of 8.1 s. In contrast, the Rule-based method exhibited a significantly higher false negative rate of 42.0%, indicating limitations in detecting complex anomaly patterns. These results demonstrate that the proposed spatiotemporal deep learning approach can significantly improve the accuracy and responsiveness of battery anomaly detection. Furthermore, the proposed method is expected to contribute to enhancing safety, reliability, and predictive diagnostics in next-generation intelligent BMS platforms.
The development of a large-area solution process for CuO nanowires, which are promising p-type thin film transistors (TFT) channel materials, is required. To overcome the limitations of the existing high-vacuum and high-cost deposition process, a large-area Cu nanowire network was formed on the substrate using the Mayer rod coating method, and a CuO channel was implemented by subsequent thermal annealing. Consequently, p-type TFT with an on/off current ratio of 1.4×104 and a field-effect mobility µFE≈10-4 cm2/(V⋅s). was fabricated and optimized. X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analyses showed that the sample annealed at 200°C exhibited an incomplete oxidation state with a mixed Cu/Cu2O phase and a high fraction of M-OH species (58.78%), resulting in a low on/off current ratio (≈1.2). In contrast, annealing at 450°C leads to a CuOdominant phase, where the fraction of lattice oxygen(O1) increases to 31.11% and the oxygen vacancy (VO) component increases to 7.15%, indicating a significant improvement in hole concentration and charge transport. These phase transitions and surface chemical changes are identified as the key mechanisms for the enhanced TFT switching characteristics. The low-cost, large-area Mayer rodbased solution process proposed in this study provides a basic process platform for p-type TFTs applicable to flexible wearables and display technologies and suggests the possibility of commercialization through additional optimization of bias stability in the future.
The direct utilization of steelmaking by-product gases in solid oxide fuel cells (SOFCs) offers a promising pathway to improve energy efficiency and reduce carbon emissions in the steel industry. In this study, a Sr-deficient and Ni-doped double perovskite oxide, Sr1.95Fe1.35Ni0.15Mo0.5O6-δ (SFNM), was investigated as an anode material for direct Linz-Donawitz converter gas (LDG)-fueled SOFCs. A single-phase double perovskite structure was successfully obtained after calcination at 1,200°C for 12 h, while exsolved metallic Ni nanoparticles were generated on the SFNM surface after reduction at 800°C. Electrochemical performance was evaluated using H2, simulated-LDG, and CO/CO2 (85:15) fuels at 800°C. The maximum power densities achieved were 1.23, 0.70, and 0.40 W cm-2 for H2, simulated-LDG, and CO/CO2 fuels, respectively. Although CO-containing fuels exhibited lower opencircuit voltages and power outputs than H2, the SFNM anode maintained stable operation and appreciable performance under direct simulated-LDG utilization. Impedance analysis revealed that the increased polarization resistance in simulated-LDG and CO/CO2 atmospheres was mainly associated with fuel adsorption/desorption and gas diffusion, while interfacial charge-transfer resistance remained relatively small. The superior performance obtained with simulated-LDG compared to the CO/CO2 mixture was attributed to the presence of a small amount of H2, which facilitated anode reaction kinetics. These results demonstrate that SFNM is a promising mixed ionic-electronic conductor anode for the direct electrochemical conversion of CO-rich steelmaking by-product gases into electricity.
Electrochemical water splitting has emerged as a pivotal technology for green hydrogen production, offering a viable pathway toward a sustainable energy future. Among various electrolysis systems, Anion exchange membrane water electrolysis is particularly noteworthy as a cost-effective solution capable of operating under the fluctuating power inputs typical of renewable energy sources. However, the overall efficiency of water splitting is fundamentally limited by the oxygen evolution reaction, which exhibits sluggish kinetics compared to the hydrogen evolution reaction. While IrO2 and RuO2 serve as current benchmarks, their scarcity and high cost necessitate the development of earth-abundant alternatives. This review provides a comprehensive overview of fundamental OER mechanisms including the adsorbate evolution mechanism, lattice oxygen mechanism, and oxide path mechanism while highlighting how new pathways can circumvent traditional scaling relations. We discuss recent advancements in transition metal-based electrocatalysts, encompassing oxides, hydroxides, chalcogenides, phosphides, nitrides, and carbides, with a focus on innovative design strategies such as defect engineering, heteroatom doping, and heterostructure construction. This paper concludes by addressing current challenges and offering perspectives on future directions for the development of highly efficient and economically viable oxygen evolution electrocatalysts for large-scale applications.
As electric vehicles (EVs) are rapidly adopted worldwide, large numbers are now transported by sea on dedicated car carriers. With this trend, concerns are increasing about fires and explosions caused by battery thermal runaway during marine transport, while existing SOC limits before loading remain largely empirical. This study experimentally investigates gas generation and explosion characteristics of EV lithium-ion cells under thermal runaway conditions representative of enclosed vehicle decks. We identify and quantify the main off-gas components and clarify the flammability behavior and explosion limits of key combustible species. The results provide basic data for assessing EV battery accidents at sea and support the development of safer ventilation and gas-management strategies for ships.
The rapid proliferation of artificial intelligence (AI) servers and high-performance computing systems has significantly elevated the technical and reliability requirements for multilayer ceramic capacitors (MLCCs). In such systems, MLCCs are critical passive components that must deliver high capacitance, fast transient response, and robust insulation performance under high temperature, voltage, and current density. This review examines the material, structural, and process innovations that underpin MLCC performance in AI applications. Key topics include the development of ultrathin dielectric layers (<0.5 μm), rare-earth doped BaTiO₃-based dielectrics with enhanced DC bias stability, and core-shell microstructures designed for temperature and field resilience. The paper also explores insulation degradation mechanisms―such as vacancydriven conduction and demixing―and advanced reliability assessment methodologies, including HALT, TSDC, and the tipping point framework. Comparisons with automotive-grade MLCCs highlight the unique requirements of AI systems, such as ultraminiaturization, high volumetric efficiency, and ppm-level field failure rates. Finally, the review discusses emerging trends in MLCC technology, including particle engineering, interface stabilization, and advanced lamination techniques, and provides insight into the future direction of capacitor development tailored to AI data center environments.
This study investigates the effect of mask material and thickness on the silicon etching profile using a high-density plasma (HDP) etching system, aiming to reduce optical loss in silicon-based optical waveguides. As the mask thickness increased, the etching sidewall angle became steeper. An etching profile angle of 87° was obtained when tetraethyl orthosilicate (TEOS) was used as the mask material, while 80° was obtained for photoresist (PR). This is attributed to electron charging on the mask surface in the plasma. The charged mask modifies the distribution and strength of the electric field depending on its thickness, thereby affecting the trajectory of positive ions accelerated toward the substrate by the bias voltage. Furthermore, Plasma diagnostics using optical emission spectroscopy (OES) and surface composition analysis using field emission Auger electron spectroscopy (FE-AES) revealed that changes in the mask material also alter the reaction pathways and formation characteristics of active species and silicon by-products in the plasma. These results suggest that the mask material influences the overall plasma characteristics, including electron density and ion energy, and plays a critical role in the precise control of silicon etching profiles for high-performance optical device fabrication.
This review systematically examines the structural characteristics, compositional design strategies, and recent research trends of layered double hydroxides (LDHs), which are recognized as promising electrocatalyst materials in electrochemical nitrate-to-ammonia conversion. Despite the rapid growth in related research, achieving simultaneous high selectivity and efficiency remains a significant technical challenge due to the complex mechanisms of the nitrate reduction reaction (NitRR) and its inherent competition with the hydrogen evolution reaction (HER). In this study, we analyzed the structural contributions of LDH catalysts for maximizing nitrate reduction efficiency and systematically established key catalyst design indicators required to ensure optimal performance. Specifically, we provide a detailed investigation of the physicochemical mechanisms for enhancing NH₃ production by precisely regulating the adsorption energies of reaction intermediates and maximizing charge transfer efficiency through compositional control and defect engineering. Furthermore, we discuss advanced structural design strategies, such as core-shell tandem structures, MOF-derived architectures, and interlayer anion control, as effective methods for enhancing catalytic performance and optimizing mass transport processes. These insights offer a strategic roadmap for designing high-performance LDH catalysts and represent a critical step toward the practical implementation of sustainable green ammonia production systems, particularly for integration into high-efficiency membrane electrode assembly (MEA) technologies.
The safety and stability concerns of liquid electrolytes in conventional lithium-ion batteries have accelerated the development of solid-state alternatives. NASICON type ceramics Li1.5Al0.5Ti1.5(PO4)3 (LATP) offer promising properties, including high bulk ionic conductivity and good compatibility with lithium anodes. However, their practical application is hindered by grain boundary resistance and relatively low total ionic conductivity. This study investigates the effect of Ta2O5 doping on LATP to overcome these limitations. Doping with 5 wt% Ta2O5 improved the ionic conductivity to 2.95 × 10-4 S/cm by enhancing lattice structure, reducing grain boundary resistance, and suppressing the formation of secondary phase. Additionally, Ta2O5 positively influenced the sintering behavior, resulting in a denser, and more uniform microstructure. These enhancements suggest that Ta2O5-doped LATP is a strong candidate for next-generation all-solid-state lithium-ion batteries.
Cellulose nanofiber (CNF) has attracted significant attention as a next-generation insulating material due to its ecofriendly nature and outstanding functionalities. However, conventional kraft insulation paper suffers from limited dielectric breakdown strength and long-term reliability under high-voltage conditions, highlighting the need for alternative materials. In this study, kraft pulp was combined with five types of CNFs (A, B, C: wood-based / D, E: non-wood-based) to fabricate composite insulation papers, and their electrical and mechanical properties were systematically evaluated. The results showed that CNF incorporation generally enhanced density and tensile strength, while certain types contributed to lowering dielectric constant and improving breakdown strength. Among the wood-based CNFs, type C exhibited the most balanced performance in terms of dielectric stability and mechanical reinforcement. Among the non-wood-based CNFs, type E demonstrated notable improvements in structural compactness and tensile strength, suggesting favorable reliability. Therefore, this study identifies CNF C among wood-based types and CNF E among non-wood-based types as the most promising candidates for insulation performance enhancement, suggesting their applicability as next-generation insulating materials for power equipment and ecofriendly electronic devices.
