Quantum dots (QDs) are semiconductor nanocrystals with sizes on the order of several nanometers, whose bandgaps can be tuned by controlling the particle size. Owing to this bandgap tunability, QDs can absorb near-infrared (NIR) and short-wave infrared (SWIR) light, spectral regions that are difficult to access with conventional silicon-based devices. However, colloidal QDbased infrared photodetectors still suffer from intrinsically high dark current, trap-induced noise, and limited response speed. As a result, they exhibit fundamental performance gaps in terms of detectivity and speed–bandwidth product compared to epitaxial infrared detectors, highlighting the need for structural and architectural design strategies to overcome these limitations. In this review, we discuss recent advances in enhancing the spectral selectivity and sensitivity of infrared photodetectors through three-dimensional optical architectures, including metasurfaces and metamaterials. We focus in particular on design strategies and the underlying mechanisms responsible for performance enhancement, and we outline how structural approaches can be leveraged to effectively control the sensitivity and wavelength selectivity of QD-based infrared detectors.

This review offers a critical overview of recent developments in lead-free piezoelectric materials and flexible device architectures for self-powered wearable and Internet of Things systems. It examines the scientific and technological rationale for replacing conventional battery-dependent power sources with ambient mechanical energy harvesters, and it evaluates the relative merits of inorganic ceramics, organic polymers, and composite systems in achieving efficient electromechanical conversion under practical operating conditions. The discussion further considers compositional tuning, phase boundary engineering, microstructural optimization, and device-level integration as key strategies for improving piezoelectric output, mechanical compliance, durability, and manufacturability. By connecting fundamental materials design with application-driven device requirements, the review identifies the principal challenges and emerging directions necessary for the realization of reliable, scalable, and sustainable electronic platforms.

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.

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.

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.

Humidity monitoring of exhaled breath has emerged as a vital approach for noninvasive respiratory health assessment, underscoring the need for sensitive and reliable humidity sensors. Despite its high conductivity and hydrophilic functional groups, reduced graphene oxide (rGO) often undergoes irreversible moisture adsorption and gradual oxidation by residual water, resulting in sensitivity degradation and long-term instability during cycling. In this study, a montmorillonite/reduced graphene oxide (MMT/rGO) composite is developed as a room-temperature humidity-sensing material, exhibiting an optimized response of 115%, more than 14 times higher than that of pristine rGO. This superior performance originates from the synergistic interaction between the reversible MMT swelling and the conductive rGO network near the electrical percolation transition, which ensures excellent stability and repeatability under repeated humidity cycles. These findings suggest that the MMT/rGO composite provides a cost-effective and biocompatible platform for next-generation wearable humidity sensors capable of continuous respiratory monitoring.

The continuous and long-lasting monitoring of physiological signals induced from the human body is crucial for health monitoring, disease diagnosis, and treatment. In this study, we have reported the Seebeck effect-based flexible selfpowered temperature sensor which can convert the electric signals from lateral temperature difference. For demonstrating temperature sensor arrays, the p-type thermoelectric (TE) composite films were fabricated by dispersing the Bi_0.5Sb_1.5Te₃ (BST) powders inside poly-vinylidene fluoride matrix and subsequently attached to the patterned electrode foils. The inorganic BST powders-embedded TE composite films with activated area of 0.5 × 1 cm² harvest a maximum voltage of 1.7 mV, a maximum current of 5.6 mA, and an output power of 2.6 nW from the temperature gradient (ΔT) of 20 K. Finally, the fabricated selfpowered temperature sensor array well detected the pattern images of external thermal source of ΔT = 20 K. This study manifests flexible temperature sensor array which paves the way for further advancements in this field.

The growing demand for miniaturized, lightweight, and sustainable electronic devices has intensified the need for advanced bonding materials. Existing electrically conductive adhesives (ECAs) often rely on high silver (Ag) content, resulting in elevated costs and environmental concerns. This study successfully developed a novel ECA with significantly reduced Ag content without compromising essential electrical conductivity and adhesion performance. Experimental results revealed that the optimized ECA demonstrates electrical conductivity comparable to that of commercial products, with notable advantages in cost reduction and eco-friendliness. These advancements position the developed ECA as a promising solution for next-generation electronic manufacturing, contributing to low-carbon technologies and sustainable practices. Future applications could further broaden its use across diverse electronic systems, driving progress in environmentally conscious technologies.

Cu₂O metal oxide was synthesized using NaBH₄ as a reducing agent in this study. The transformation of Cu composite with the pH adjustment was investigated, and the conditions for Cu₂O synthesis were analyzed. As pH of the solution was changed, the synthesized Cu composite evolved into Cu/Cu₂O and Cu/Cu₂O/CuO composites. The Cu₂O composite synthesized under conditions closest to pure Cu₂O was heat-treated at 200℃. The remaining minor Cu metal was oxidized, resulting in pure Cu₂O particles with enhanced crystallinity. The synthesized Cu₂O exhibited various morphology with particle sizes of about 160~720 nm, and the shape and size of the Cu₂O particles remained significantly unchanged after heat treatment. Surface analysis was conducted to compare the changes before and after heat treatment. No significant changes were observed, except for those attributed to water evaporation. The Cu₂O synthesized via this simple chemical reduction method can be utilized in various application fields, including catalysts, optical devices, and sensors.

Energy harvesting technology offers an innovative solution for providing self-sustaining power to wearable and implantable electronic devices. However, traditional energy harvesters face limitations in operating within electrolytic environments or at low motion speeds. To overcome these challenges, a mechano-electrochemical energy harvester using carbon nanotubes has been developed. This technology relies on electrochemical ion movement to induce changes in electrochemical double-layer capacitance, enabling operation within electrolytes and optimizing performance at low deformation speeds. This environmentally friendly and sustainable energy solution is expected to play a crucial role in the advancement of future smart systems and wearable technologies.

Hazardous gas leakage incidents rank among the most serious safety accidents, leading to significant loss of life, extensive property damage, and severe environmental pollution. This paper describes an innovative IoT-based Assembly Double Pipe System (IADPS) designed for the prevention, early detection, and automated isolation of toxic gas leaks. The proposed system features a double-layered pipe design, with nitrogen charged between the inner and outer pipes, and gas detectors installed at strategic locations. This configuration is intended to prevent pipe corrosion, suppress ignition caused by escaping gas, and facilitate the early detection of gas leaks, thereby mitigating the risk of safety accidents. Furthermore, the system includes a comprehensive real-time monitoring system for pipe integrity and gas leakage, as well as an automated gas leakage detection and isolation system to quickly respond to any incidents.

The search for sustainable and efficient energy conversion technologies is becoming increasingly critical in response to global energy and environmental challenges. Traditional lead-based piezoelectric materials, such as lead zirconate titanate (PZT), have high piezoelectric constant but present significant health problems and environmental risks due to their hazardous metal contaminants. This study addresses these concerns by investigating barium titanate (BTO), a lead-free alternative, and enhancing its performance using anisotropic nanowires (NWs) structures. BTO NWs were synthesized via a two-step hydrothermal method and incorporated into a poly(vinylidene fluoride-trifluoroethylene) [P(VDF-TrFE)] matrix to fabricate a piezoelectric composite film. The resulting device demonstrated a notable increase in electrical output compared to devices based on isotropic morphology of BTO nanoparticles, exhibiting enhanced performance. These findings suggest that BTO NWs hold significant promise for applications in flexible and wearable electronics, paving the way for further advancements in sustainable energy technology.

Oxygen evolution reaction is a critical bottleneck for the development of efficient electrochemical hydrogen production because of its sluggish reaction. Among various catalysts, transition metal-based layered double hydroxide has drawn significant attention due to their excellent catalytic properties and cost-effectiveness. This paper begins with basic crystal structures, and then conventional adsorbate evolution mechanism of layered double hydroxide. Strategies for enhancing catalytic properties based on adsorbate evolution mechanism and lattice oxygen mechanism that could surpass theoretical limit of adsorbate evolution mechanism are discussed. This paper ends with a brief discussion on the challenges and future directions of layered double hydroxide-based oxygen evolution reaction catalysts.

This research explores the development of [100]-textured barium titanate (BaTiO₃, BT) ceramics using sodium bismuth titanate (Na_0.5Bi_4.5Ti₄O₁₅, NBiT) templates, aimed at leveraging the inherent high dielectric property of BT. However, the attempted texturing was unsuccessful, primarily due to bismuth diffusion from the NBiT templates into the BT matrix below the sintering temperature, at 1,000℃. Systematical exploration about the cause of the failure is involved and alternative approaches are proposed in detail to overcome the challenge. These findings contribute to the understanding of techniques and conditions for textured ceramic fabrication and highlight the need for further research in this area.

In this paper, in order to analyze the PMU data of the accident section, we collected the raw data of a total of 35 PMU installed at the Yeonggwang substation and tried to find a way to analyze the data, and analyzed the data using Excel format and formula. As a result, the three-phase voltage and current data of the PMU were calculated using formulas in Excel and interpreted as effective and reactive power, and it was possible to check the effective and reactive power of the accident section through the graph to see why it was different from before the accident. As a result, it was confirmed that each power was greatly reduced in the graph of the effective and reactive power of the accident section, and it was confirmed that the loss occurred as the power of the accident section was greatly reduced.

The Internet of Things (IoT) device is a key component for Industry 4.0, which is the network in homes, factories, buildings, and infrastructures to monitor and control the systems. To demonstrate the IoT network, batteries are widely utilized as power sources, and the batteries inevitably require repeated replacement due to their limited capacity. Magneto-mechanoelectric (MME) generators are one of the candidate to develop self-powered IoT systems since MME generators can harvest electricity from stray alternating current (AC) magnetic fields arising from electric power cables. Herein, we report a magnetomechano- triboelectric generator enabled by a ferromagnetic-ferroelectric composite. In the triboelectric nylon matrix, a ferromagnetic carbonyl iron powder (CIP) was introduced to induce magnetic force near the AC magnetic field for MME harvesting. Additionally, a ferroelectric ceramic powder was also added to the MME composite material to enhance the chargetrapping capability during triboelectric harvesting. The final ferromagnetic-ferroelectric composite-based MME triboelectric harvester can generate an open-circuit voltage and a short-circuit current of 110 V and 8 μA, respectively, which were enough to turn on a light emitting diode (LED) and charge a capacitor. These results verify the feasibility of the MME triboelectric generator for not only harvesting electricity from an AC magnetic field but also for various self-powered IoT applications.

Multilayered actuators using Pb(Mg_1/3Nb_2/3)O₃-Pb(In_1/2Nb_1/2)O₃-PbTiO₃ (PMN-PIN-PT) crystals have demonstrated excellent properties, but are costly and lack mechanical strength. Textured PMN-PIN-PT ceramics exhibit robust mechanical strength and comparable properties to their single crystals form. However, the development of multilayered actuators using textured PMN-PIN-PT ceramics has not been achieved until now. This study presents the development of a multilayered actuator using textured 0.37PMN-0.29PIN-0.34PT ceramics with an Ag0.9/Pd0.1 inner electrode, co-fired at 950℃. A random 0.37PMN- 0.29PIN-0.34PT ceramics multilayered actuator was also developed for comparison. The multilayered actuator consisted of 9 ceramic layers (36 μm thickness) with an overall actuator thickness of 0.401 mm. The textured and random 0.37PMN-0.29PIN- 0.34PT ceramics-based multilayered actuators achieved displacements of 0.61 μm (0.15% strain) and 0.23 μm (0.057% strain) at a low applied peak voltage of 100 V. These results suggest that the developed multilayered actuator using high-performance textured 0.37PMN-0.29PIN-0.34PT ceramics has the potential to replace expensive single crystal-based actuators costeffectively.

This paper is a study on frequency analysis and electronic noise reduction of energy storage system (ESS). We acquired 4 necessary data for about 2 minutes and 4 seconds using a sampling frequency of 10,000 Hz in ESS. Fast Fourier transform (FFT) was used for electronic noise analysis from the acquired data. As a result, it was confirmed that DC component, fundamental wave, second and higher harmonic component exist. For the attenuation of harmonics, low-pass filter (LPF) was applied. We confirmed that an attenuation of approximately 59.3% appears from the second harmonic. The presence of many harmonic components in the data of the ESS was expected to occur due to the insufficiency of optimization among the modules inside the ESS. Therefore, we propose that a national certification system for ESS should be introduced to settle down the issue properly.

Energy storage capacitors based on dielectric ceramics with superior polarization properties and dielectric constant can provide much higher output power density due to their very fast energy charging/discharging rates, which are particularly suitable for operating pulsed-power devices. For an outstanding energy storage performance of dielectric capacitor, a large recoverable energy density could be derived by introducing a slim polarization-electric field hysteresis loop into dielectric materials by various technical approaches. Many research teams have explored various dielectric capacitor technologies to demonstrate high output power density and ultrafast charging/discharging behavior. This article reviews the recent research progress in high-performance dielectric capacitors for pulsed-power electronic applications.

The internet of things (IoT) technology is a key component for the advent of 4^th industrial revolution, which is the network of home appliances, infrastructures, and vehicles to remotely investigate these systems. For the operation of compact IoT devices, batteries are widely used as electric power, and the limited lifetime of batteries inevitably leads to periodic replacement. Magneto-mechano-electric (MME) generators may be alternatives to batteries inside the IoT devices by converting stray magnetic field into electric energy, since we are always surrounded by ambient alternating current (AC) magnetic fields induced from electric power transmission lines everywhere. This article reviews the recent domestic research progress in high-performance MME generators and their application field for IoT and electronic devices.

In this study, we fabricated multilayer graphene on a glass substrate by stacking the monolayer graphene synthesized via chemical vapor deposition. The electrical sheet resistance and optical transmittance were evaluated to confirm the quality of the stacked multilayer graphene. Using the fabricated multilayer graphene/glass structure, we characterized its thermal radiative property in terms of the integrated emissivity. The integrated emissivity of the multilayer graphene/glass structure was tuned from 0.91 to 0.72 when the number of graphene layers was changed from 1 to 12. We also demonstrated that the emissivity tunability provided a way to control the apparent temperature of an object that can be used in infrared stealth applications.

In this study, we tried finding new materials to improve the stain resistance properties of polymer insulating materials. Using the filtered vacuum arc source (FVAS) with a graphite target source, DLC thin films were deposited on silicon and polymer insulator substrates depending on their thickness to confirm the surface properties, physical properties, and structural properties of the thin films. Subsequently, the possibility of using a DLC thin film as a protective coating material for polymer insulators was confirmed. DLC thin films manufactured in accordance with the thickness of various thin films exhibited a very smooth and uniform surface. As the thin film thickness increased, the surface roughness value decreased and the contact angle value increased. In addition, the elastic modulus and hardness of the DLC thin film slightly increased, and the maximum values of elastic modulus and hardness were 214.5 GPa and 19.8 GPa, respectively. In addition, the DLC thin film showed a very low leakage current value, thereby exhibiting electrical insulation properties.

In this study, we created a DBD plasma device and a MnO₂ catalyst mesh filter for evaluating ozone reduction of devices via the catalyst method. The DBD plasma device was manufactured by applying MnO₂ paste to soda lime glass via the screen-printing method. The MnO₂ catalyst mesh filter was manufactured by mixing MnO₂ powder with binder with a 10% difference in concentration from 10% to 50% and then applying it using the dip-coating method. Finally, we sintered a MnO₂ catalyst mesh filter in an electric furnace. We evaluated the characteristics of ozone generation according to the MnO₂ gas flow of DBD plasma devices, the opening ratio, and ozone reduction performance of the MnO₂ catalyst filters. Ozone reduction performance was approximately 20.4% at MnO₂10 wt%, 37.8% at MnO₂ 30 wt% and 50% at MnO₂ 50 wt%.

Heterolayered K(Ta,Nb)O₃/Pb(Zr,Ti)O₃ thin films on Pt/Ti/SiO₂/Si substrates were prepared by a sol-gel process and spin-coating method. The structural and electrical properties were measured to investigate the possibility of application as an electrocaloric effect device. All specimens exhibited dense and uniform cross-sectional structures without pores, and the average thickness of the specimen coated six times was approximately 394 nm. Curie temperatures were observed at 5℃ or less in type-Ⅰ and 10℃ in type-Ⅱ specimens, respectively. Type-Ⅱ specimens coated 6 times showed a relative dielectric constant of 758 and remanent polarization of 9.71 μC/cm₂ at room temperature. The maximum electrocaloric effect occurred between 20 and 25℃, slightly higher than their Curie temperature, and the electrocaloric property (ΔT) of the type-Ⅱ specimens coated 6 times was approximately 1.2℃ at room temperature.

An increase in the temperature of photovoltaic (PV) modules causes reduced power output and shorter lifetime. Because of these characteristics, demands for the heat dissipation of PV modules are increasing. In this study, we attached a heat dissipation sheet to the back sheet of a shingled PV module and observed the temperature changes. The PV shingled module was tested under Standard Test Conditions (STCs; irradiance: 1,000 W/m², temperature: 25℃, air mass: 1.5) using a solar radiation tester, wherein the temperature of the PV module was measured by irradiating light for a certain duration. As a result, the temperature of the PV module with the heat dissipation sheet decreased by 3℃ compared to that without a heat dissipation sheet. This indicated that the power loss was caused by a temperature increase of the PV module. In addition, it was confirmed that the primary parameter contributing to the reduced PV module output power was the open circuit voltage (Voc).

Radiation noise due to EMI noise generated by the driving circuits of LED lighting devices in a medical imaging room was reduced by decreasing the noise source in the driving circuits and changing the number of corrections in EMI filters. Noise attenuation and filter changes enabled driving circuits that reduced the electromagnetic waves. Such circuits were efficiently designed by using capacitors and inverters in a given space. Therefore, the malfunction of radiation devices can be minimized by using EMI-reduction filter circuits, and reliable operation of medical devices can be expected by blocking electromagnetic waves.

The facile synthesis of shape-controlled Pd nanoparticles (PdNPs) with ascorbic acid as a reducing agent and cetyltrimethylammonium bromide (CTAB) as a capping agent is presented in this study. The synthesized PdNPs were characterized by UV-vis spectroscopy, transmission electron microscopy (TEM), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Raman Spectroscopy. The prepared PdNPs show efficient surface-enhanced Raman scattering (SERS) properties. SERS studies on the adsorption characteristics of 1,4-phenylene diisocyanide (1,4-PDI) on colloidal PdNPs have revealed that the relative peak intensity of the (NC)_free and (NC)_bound modes distinctly depends on the 1,4-PDI concentration as well as the shape of the PdNPs. Furthermore, we found that the PdNPs are also efficient photoelectron emitters such that the SERS spectrum of 4-nitrobenzenethiol (4-NBT) on PdNPs is readily converted to that of 4-aminobenzenethiol (4-ABT) under 632.8 nm radiation.

In this work, the magnetic arc reduction phenomena encountered in AC relay contacts were analyzed. To this end, arc duration, instantaneous voltage, and current changes due to changes in the magnetic field were observed. The arc generated at the contact point was affected by the magnitude of the applied magnetic field; the voltage and current waveforms rapidly intersected, resulting in a decrease in arc duration and arc energy. Furthermore, the orientation of the N pole of the magnetic field was found to play a role in the effectiveness of potential arc prevention.

A pressure sensor is a device that converts an applied physical pressure into an electrical signal. Such sensors have a range of applications depending on the pressure level, from low to high pressure. Sensors that use physical pressure, when compared to those operating under air pressure, are not widely applied as they are inefficient. To solve this problem, graphene oxide, which exhibits good mechanical and electrical characteristics, was used to increase the efficiency of these pressure sensors. Graphene oxide has properties that control the movement of charges within the dielectric. Exploiting these properties, we evaluated the change in electrical characteristics when pressure was applied according to the ratio and thickness of the oxidation graph added to the pressure sensor.

Because of the rapidly changing environment and high uncertainties, the semiconductor industry is in need of appropriate forecasting technology. In particular, both the cost and time in the test process are increasing because the process becomes complicated and there are more factors to consider. In this paper, we propose a prediction model that predicts a final “good” or “bad” on the basis of preconditioning test data generated in the semiconductor test process. The proposed prediction model solves the classification and regression problems that are often dealt with in the semiconductor process and constructs a reliable prediction model. We also implemented a prediction model through various machine learning algorithms. We compared the performance of the prediction models constructed through each algorithm. Actual data of the semiconductor test process was used for accurate prediction model construction and effective test verification.