In this study, we systematically investigated the effects of thermal atomic layer deposition (ALD) conditions on the electrical characteristics of conductive-filament-based volatile threshold switching memristors with a Pt/Al₂O₃/Ag structure. Although volatile threshold switching memristors have attracted significant attention for neuromorphic computing applications such as spiking neural networks, the impact of dielectric deposition conditions on their switching behavior remains relatively unexplored. The number of ALD cycles was varied from 40 to 200, and the deposition temperature was varied from 50 to 250°C to evaluate their effects on threshold voltage (V_th), off-state resistance (R_off), and device yield. Devices fabricated using 75–150 ALD cycles showed clear volatile threshold switching behavior with relatively high device yield, whereas excessively low or high cycle numbers resulted in short-type and open-type failures, respectively. In addition, V_th and R_off tended to increase at higher deposition temperatures, while the device yield significantly degraded above 150°C. These results indicate that the number of ALD cycles and the deposition temperature define a critical process window for achieving volatile threshold switching while suppressing both short-type and open-type failures. This study provides practical guidelines for optimizing dielectric ALD conditions in conductive-filament-based volatile threshold switching memristors for future neuromorphic hardware applications.

Neuromorphic computing, which mimics the energy-efficient parallel processing capabilities of the human brain, has emerged as an alternative to traditional von Neumann architectures that struggle with high power consumption in the era of artificial intelligence (AI). Despite the potential of Si-based neuromorphic chips, they often face fundamental limitations in integration density and biological compatibility, necessitating the development of next-generation devices that can better emulate the ionic signaling of biological systems. This review provides a comprehensive analysis of the recent research trends in artificial synapses and neurons based on organic electrochemical transistors (OECTs), highlighting their unique ability to achieve high transconductance and mixed ionic-electronic conduction at ultra-low operating voltages. We discuss how OECTs successfully replicate diverse synaptic plasticities and complex neuronal spiking behaviors through advanced material engineering and structural optimizations such as vertical architectures. Furthermore, this review discusses the implementation of high-order neural functions, including associative learning and logic operations, which are facilitated by the inherent electrochemical dynamics of organic semiconductors. Finally, overcoming current challenges in reliability and scalability will establish OECTs as a pivotal platform for low-power neuromorphic hardware and bio-integrated electronics.

Citations

• Analysis of Yield and Electrical Characteristics of Ag Electrode-Based Volatile Threshold Switching Memristors with Al2O3 Dielectric Films Under Different ALD Process Conditions
  Wan-Sik Woo, Seung-Jin Lee, Moon-Seok Kim, Seung-Bae Jeon
  Journal of Electrical and Electronic Materials.2026; 39(5): 493.     CrossRef

This review examines the principles, limitations, and recent advancements in elastic modulus measurement using nanoindentation. The importance of accurate contact area prediction is discussed, along with the Oliver-Pharr method and its limitations. The Continuous Stiffness Measurement (CSM) technique is presented as a significant improvement, allowing continuous measurement of mechanical properties throughout the indentation process. For ultra-thin films, the Li and Vlassak method, which incorporates Yu's solution and the concept of effective thickness, is highlighted as a means to correct for substrate effects. Recent developments in artificial neural network-based models for elastic modulus prediction are also explored. These advancements have greatly expanded the applicability of nanoindentation in semiconductor and MEMS device reliability assessment.

Citations

• Material characterization and local mechanical study with nanoindentation on the stainless steel 316L part with embedded optical fiber sensor fabricated with electrical field-assisted sintering technique for severe environment application
  Wei Li, Minoo Tayefeh Kazemi, Afreeda Hossain, Hongbing Lu
  Materials Characterization.2026; 240: 116959.     CrossRef

Neuromorphic computing, inspired by the biological mechanisms of neural signal transmission, has emerged as a promising technology for efficient and parallel data processing with minimal power consumption. In this study, we developed floating-gate organic thin-film transistors (OTFTs) with self-assembled monolayer (SAM)-based tunneling layers to mimic the characteristics of artificial synapses. The tunneling layers were formed using mixed phosphonic acid SAMs with varying ratios of octadecylphosphonic acid (ODPA) and 12-pentafluorophenoxydodecylphosphonic acid (PFPA). The influence of these ratios on the memory and neuromorphic characteristics of the devices was systematically evaluated. Our results revealed that the ODPA ratio significantly impacts the hysteresis window, with higher ODPA content yielding improved memory characteristics. Conversely, the PFPA : ODPA ratio of 2:1 exhibited the lowest non-linearity (NL = 0.48), demonstrating the potential for highly accurate weight updates in neuromorphic devices. Additionally, pulse width modulation studies showed that a pulse width of 100 ms optimized the linearity and stability of long-term potentiation (LTP) and depression (LTD) characteristics. The combination of sol-gel processed AlOx as a floating-gate layer and tailored SAM-based tunneling layers allowed for precise control of device performance. These findings highlight the importance of molecular engineering in designing SAM layers to balance memory retention and neuromorphic functionality. This study provides a pathway for advancing organic floating-gate transistors as a core component in next-generation neuromorphic computing systems.

Post-metallization annealing (PMA) has been employed in silicon-based CMOS fabrication to enhance MOSFET reliability and performance. However, although deuterium annealing can reduce interface traps between the Si and SiO₂ gate dielectric, it remains insufficient to fully passivate these traps. In this context, a multiple PMA process, including additional hydrogen annealing, is proposed to further reduce dangling bonds. Silicon-based MOSFETs are fabricated to verify the proposed annealing process architecture. Electrical characterization of the threshold voltage (VTH), subthreshold swing (SS), on-state current (ION), and carrier mobility (μ_n) is conducted to investigate the impact of the multiple PMA. This study provides a guideline for PMA in MOSFET fabrication, with improvements in both performance and reliability.

We propose a real-time information propagation arithmetic neural network (PANN) that minimizes the loss of power generation output of the system in the event of sudden changes in the module due to strong external typhoons or earthquakes at the solar power generation facility site. In addition, we propose a new double-sided module reflector that can reduce the local loss of power generation efficiency of the single-sided module reflector that is currently widely distributed, as well as the environmental pollution and inconvenience of maintenance work of the existing double-sided module. We present a computational network that can detect the faulty solar panel in real-time by checking the fault status of the installed solar panel and using a real-time computation method through a node-to-node diffusion method. In particular, this method recognizes the power loss part due to sudden changes in the module in real time and can take emergency measures for various nonlinear field facilities through a neural structure that finds the optimal distance up, down, left, and right. To confirm the characteristics of the loss reduction control of the field facility, we confirmed that the system was configured as a 7-degree-of-freedom control model using the PANN neural network learning structure method and improved the power generation output. PANN (Propagation Arithmetic Neural Networks) and various module systems are proposed for the real-time recovery of faulty solar panels and improving module system efficiency.

As complementary metal-oxide semiconductor (CMOS) is scaled down to achieve higher chip density, thin-film layers have been deposited iteratively. The poor film uniformity resulting from deposition or chemical mechanical planarization (CMP) significantly affects chip yield. Therefore, the development of novel fabrication processes to enhance film uniformity is required. In this context, high-pressure deuterium annealing (HPDA) is proposed to reduce the surface roughness resulting from the CMP. The HPDA is carried out in a diluted deuterium atmosphere to achieve cost-effectiveness while maintaining high pressure. To confirm the effectiveness of HPDA, time-of-flight secondary-ion mass spectrometry (ToF-SIMS) and atomic force microscopy (AFM) are employed. It is confirmed that the absorbed deuterium gas facilitates the diffusion of silicon atoms, thereby reducing surface roughness.

The size of semiconductor devices has been scaled down to improve packing density and output performance. However, there is uncontrollable spreading of the dopants that comprise the well, punch-stop, and channel-stop when using hightemperature annealing processes, such as rapid thermal annealing (RTA). In this context, low-temperature deuterium annealing (LTDA) performed at a low temperature of 300℃ is proposed to reduce the thermal budget during CMOS fabrication. The LTDA effectively eliminates the interface trap in the gate dielectric layer, thereby improving the electrical characteristics of devices, such as threshold voltage (VTH), subthreshold swing (SS), on-state current (ION), and off-state current (IOFF). Moreover, the LTDA is perfectly compatible with CMOS processes.

Micro light-emitting diodes (LEDs), with a chip size of 100 micrometers or less, have attracted significant attention in flexible displays, augmented reality/virtual reality (AR/VR), and bio-medical applications as next-generation light sources due to their outstanding electrical, optical, and mechanical performance. In the realm of bio-medical devices, it is crucial to transfer tiny micro LED chips onto desired flexible substrates with low precision errors, high speed, and high yield for practical applications on various parts of the human body, including someone’s face and organs. This paper aims to introduce a fabrication process for flexible micro LED devices and propose micro LED transfer techniques for cosmetic and medical applications. Flexible micro LED technology holds promise for treating skin disorders, cancers, and neurological diseases.

The report reviews recent research efforts in demonstrating a computing system whose operation principle mimics the dynamics of biological neurons. The temporal variation of the membrane potential of neurons is one of the key features that contribute to the information processing in the brain. We first summarize the neuron models that explain the experimentally observed change in the membrane potential. The function of ion channels is briefly introduced to understand such change from the molecular viewpoint. Dedicated circuits that can simulate the neuronal dynamics have been developed to reproduce the charging and discharging dynamics of neurons depending on the input ionic current from presynaptic neurons. Key elements include volatile memristors that can undergo volatile resistance switching depending on the voltage bias. This behavior called the threshold switching has been utilized to reproduce the spikes observed in the biological neurons. Various types of threshold switch have been applied in a different configuration in the hardware demonstration of neurons. Recent studies revealed that the memristor-based circuits could provide energy and space efficient options for the demonstration of neurons using the innate physical properties of materials compared to the options demonstrated with the conventional complementary metal-oxidesemiconductors (CMOS).

High pressure deuterium (HPD) annealing is an advancing technology for the fabrication of modern semiconductor devices. In this work, gate-enclosed FETs are fabricated on a silicon substrate as test vehicles. After a cycle for the HPD annealing, the device parameters such as threshold voltage (V_TH), subthreshold swing (SS), on-state current (I_ON), off-state current (I_OFF), and gate leakage (I_G) were measured and compared depending on the HPD. The HPD annealing can passivate the dangling bonds at Si-SiO₂ interfaces as well as eliminate the bulk trap in SiO₂. It can be concluded that adding the HPD annealing as a fabrication process is very effective in improving device reliability, performance, and variability.

Artificial neuromorphic devices are considered the key component in realizing energy-efficient and brain-inspired computing systems. For the artificial neuromorphic devices, various material candidates and device architectures have been reported, including two-dimensional materials, metal-oxide semiconductors, organic semiconductors, and halide perovskite materials. In addition to conventional electrical neuromorphic devices, optoelectronic neuromorphic devices, which operate under a light stimulus, have received significant interest due to their potential advantages such as low power consumption, parallel processing, and high bandwidth. This article reviews the recent progress in optoelectronic neuromorphic devices using various active materials such as two-dimensional materials, metal-oxide semiconductors, organic semiconductors, and halide perovskites

As industry and technology go through advancement, it is hard to search new materials which satisfy various standards through conventional trial-and-error based research methods. Crystal Graph Convolutional Neural Network(CGCNN) is a neural network which uses material’s features as train data, and predicts the material properties(formation energy, bandgap, etc.) much faster than first-principles calculation. This report introduces how to train the CGCNN model which predicts the formation energy using open database. It is anticipated that with a simple programming skill, readers could construct a model using their data and purpose. Developing machine learning model for materials science is going to help researchers who should explore large chemical and structural space to discover materials efficiently.

The electrical characteristics of single-crystal composite superconductors produced by a melting process were studied by neutron irradiation. In order to improve the current characteristics of the YBa₂Cu₃O_7-y superconductor, it is necessary to form an effective flux pinning center inside the superconductor. In this study, an increase in flux pinning was attempted through neutron irradiation onto YBa₂Cu₃O_7-y superconductors. The neutron irradiation was performed at 30 MeV for 500 sec, The electrical properties of the superconductors were measured in a magnetic field of 5 Tesla at 50 K using a magnetic properties measurement system (MPMS). After neutron irradiation, the critical current density of the YBa₂Cu₃O_7-y superconductor in a 1 Tesla magnetic field was 1×10⁵ A/㎠. Once neutrons were irradiated at 30 MeV and 10 μA for 500 sec, the critical current density was observed to increase significantly. When neutrons are irradiated to a superconductor, micro-defects are created in the superconductor, and they act as flux pinning centers that hold the magnetic field generated when an electric current flows.

This study examines the feasibility of the image deep learning method using convolution neural networks (CNNs) to maintain a porcelain insulator. Data augmentation is performed to prevent over-fitting, and the classification performance is evaluated by training the age, material, region, and pollution level of the insulator using image data in which the background and labelling are removed. Based on the results, it was difficult to predict the age, but it was possible to classify 76% of the materials, 60% of the pollution level, and more than 90% of the regions. From the results of this study, we identified the potential and limitations of the CNN classification for the four groups currently classified. However, it was possible to detect discoloration of the porcelain insulator resulting from physical, chemical, and climatic factors. Based on this, it will be possible to estimate the corrosion of the cap and discoloration of the porcelain caused by environmental deterioration, abnormal voltage, and lightning.

Red phosphor in glasses (PiGs) for automotive light-emitting diode (LED) applications were fabricated with 620-nm CaAlSiN₃:Eu²⁺ phosphor and Pb-free silicate glass. PiGs were synthesized and mounted on high-power blue LED to make a monochromatic red LED. PiGs were simple mixtures of red phosphor and transparent glass powder. After being fabricated with uniaxial press and CIP at 300 MPa for 20 min, the green bodies were thermally treated at 550℃ for 30 min to produce high dense PiGs. As the phosphor content increased, the density of the sintered body decreased and PiGs containing 30% phosphor had a full sintered density. Changes in photoluminescence spectra and color coordination were studied by varying the thickness of plates that were mounted after optical polishing. As a result of the optical spectrum and color coordinates, PiG plate with 210 μm thickness showed a color purity of 99.7%. In order to evaluate the thermal stability, the thermal quenching characteristics were measured at temperatures of 30~150℃. The results showed that the red PIG plates were 30% more thermally stable compared to the AlGaInP red chip.

In this work, we have investigated the effect of a 30-min thermal anneal at 550℃ on the electrical characteristics of neutron-irradiated 4H-SiC MOSFETs. Thermal annealing can recover the on/off characteristics of neutron-irradiated 4H-SiC MOSFETs. After thermal annealing, the interface-trap density decreased and the effective mobility increased in terms of the on-characteristics. This finding could be due to the improvement of the interfacial state from thermal annealing and the reduction in Coulomb scattering due to the reduction in interface traps. Additionally, in terms of the off-characteristics, the thermal annealing resulted in the recovery of the breakdown voltage and leakage current. After the thermal annealing, the number of positive trapped charges at the MOSFET interface was decreased.

We have studied the effects of Ag on the characteristics of Sn₄₃Bi₅₇Ag_x(wt%) lead-free solders for photovoltaic ribbon. Ag atoms in the solder formed an alloy phase of Ag₃Sn after reacting with some part of Sn atoms, while they did not react with Bi atoms, but decreased the mean size of Bi solid phase and the thickness of solder. When Ag atoms of 3.0 wt% was added to eutectic Sn₄₃Bi₅₇(wt%) solder, it showed the optimally useful results that the peel strength of photovoltaic ribbon greatly increased and the sheet resistance of the solder decreased. In the meanwhile, the eutectic Sn₄₃Bi₅₇(wt%) solder showed a low melting temperature of 138.9℃, and showed a very similar result regardless of the added amount of Ag atoms.

The temperature dependent characteristics on the properties of SiC Schottky Diode has beeninvestigated. In this study, the temperature dependent current-voltage characteristics of the SiC Schottkydiode were measured in the range of 300 ∼ 500 K. Divided into pre- and post- irradiated device wasmeasured. The barrier height after irradiation device at 500 K increased 0.15 eV compared to 300 K, thebarrier height of pre- neutron irradiated Schottky diode increased 0.07 eV. The effective barrier heightafter irradiation increased from 0.89 eV to 1.05 eV. And ideality factor of neutron irradiated Schottkydiode at 500 K decreased 0.428 compared to 300 K, the ideality factor of pre- neutron irradiated Schottkydiode decreased 0.354. Also, a slight positive shift in threshold voltage from 0.53 to 0.68 V. we analyzedthe effective barrier height and ideality factor of SiC Schottky diode as function of temperature.

The effect of neutron irradiation on the properties of SiC Schottky Diode has been investigated. SiC Schottky diodes were irradiated under neutron fluences and compared to the reference samples to study the radiation-induced changes in device properties. The condition of neutron irradiation was 3.1×1010n/cm2. The current density after irradiation decreased from 12.7 to 0.75 A/cm2. Also, a slight positive shift (ΔVth= 0.15 V) in threshold voltage from 0.53 to 0.68 V and a positive change (ΔΦB= 0.16 eV) of barrier height from 0.89 to 1.05 eV have been observed by the neutron irradiation, which is attributed to charge damage in the interface between the metal and the SiC layer.

The utilization of a fluoran leuco sensitizer, 2-anilino-6-dibutyl amino-3-methylfluoran (ODB-2), for dye-sensitized solar cells (DSSCs) was investigated through the examination of the adsorption of ODB-2 molecules onto the surfaces of porous titanium dioxide (titania, TiO2) films and the photovoltaic properties of ODB-2-based DSSCs. Despite of the absence of the specific anchoring groups with titania, ODB-2 dye molecules were spontaneously adsorbed onto the titania surfaces because the lactone ring in ODB-2 was opened and changed into the carboxylic acid (-COOH) by releasing protons from the surfaces (TiOH2 +) of titania, which consequently leads to the chemisorption reaction of ODB-2 molecules to the active sites of titania. DSSCs based on ODB-2 exhibited typical photovoltaic properties with an open-circuit voltage (VOC) of 0.19 V, a short-circuit current (JSC) of 0.30 mA·cm-2, a fill factor (FF) of 37%, and a conversion efficiency (PCE) of 0.02%.

Y1-xVO4:Eux 3+ red phosphors were synthesized with changing the mol ratios of Eu3+ ions by using the solid-state reaction method. The crystalline structure of phosphors was found to be a tetragonal system with the maximum diffraction intensity at 25.02°. The grain particles showed the truncated hexagonal patterns with a very homogeneous size distribution at 0.05 mol of Eu3+ ion. The excitation spectra of the phosphor ceramics were composed of a broad band centered at 303 nm and weak narrow multilines peaked in the range of 360-420 nm. The dominant emission spectrum was the strong red emission centered at 619 nm due to the 5D0→7F2 electric dipole transition. The experimental results suggest that the optimum doping mol ratio of Eu3+ ions for preparing the red phosphors is 0.10 mol with the asymmetry ratio of 5.21.

Gd(1-x)VO4:Eu(x)3+ red phosphors were synthesized with changing the concentration of Eu3+ ion by using a solid-state reaction method. The crystal structure, surface morphology, and photoluminescence and photoluminescence excitation properties of the red phosphors were measured by using X-ray diffractometer, field emission-scanning electron microscopy, and florescence spectrometer, respectively. The XRD results showed that the main peak of all the phosphor powders occurs at (200) plane. As for the photoluminescence properties, the maximum excitation spectrum occurred at 306 nm due to the charge transfer band from VO4(3-) to Eu3+ ions and the maximum emission spectrum was the red luminescence peaking at 619 nm when the concentration of Eu3+ ion was 0.10 mol.

This paper is studied for the improvement of the characteristics of gate oxide with 3-nm-thick gate oxide by deuterium ion implantation methode. Deuterium ions were implanted to account for the topography of the overlaying layers and placing the D peak at the top of gate oxide. A short anneal at forming gas to nitrogen was performed to remove the damage of D-implantation. We simulated the deuterium ion implantation to find the optimum condition by SRIM (stopping and range of ions in matter) tool. We got the optimum condition by the results of simulation. We compare the electrical characteristics of the optimum condition with others terms. We also analyzed the electrical characteristics to change the annealing conditions after deuterium ion implantation. The results of the analysis, the breakdown time of the gate oxide was prolonged in the optimum condition. And a variety of annealing, we realized the dielectric property that annealing is good at longer time. However, the high temperature is bad because of thermal stress.

In this study, we intended to design the optimal Fermi filter to apply the k-space date that is knee image of the rheumatoid arthritis patient acquired from the MRI (magnetic resonance imaging) instrument. After deciding the suitable coefficient for the Fermi filter, the results were compared with modified Fermi filter and inverse Chebyshev filter, Chebyshev filter, Elliptic filter and Butterworth filter. Firstly, in comparison to the results, the radiologist confirmed that modified Fermi filter was best decision for boundary of the rheumatoid arthritis images. The number of the black voxels of the histogram showed the quantity of the results. At the proposed filter images, numbers of the blacks voxels were statistically decreased. That meant voxels only appeared the black color were changed to others voxels color. Because the number of the total voxels was fixed, the area appeared block color could be effected to the other areas. If the modified Fermi filter were used for rheumatoid arthritis patient, the result will be better than other filters.

We have proposed a new configuration on the cathode structure to improve a neutron yield without the application of external ion sources in an inertial electrostatic confinement (IEC) device. A neutron yield in the IEC device is closely related to the potential well structure generated inside the cathode and is proportional to the ion current. Therefore, the application of a double grid cathode structure to the IEC device is expected to produce a higher ion current and neutron yield than at a single grid cathode due to a high electric field strength generated around the cathode. These possibilities were verified as compared with the ion current calculated from both shape of the single and double grid cathode. Additionally from the results of ion`s lives and trajectories examined at various outer cathode voltages and grid cathode configurations by using particle simulations, the validity of the double grid cathode was confirmed.