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Manipulating the spontaneous emission rate of fluorophores is vital in creating bright incoherent illumination for optical sensing and imaging, as well as fast single-photon sources for quantum technology applications. This can be done via increasing the Purcell effect by using non-monolithic optical nanocavities; however, achieving the desired performance is challenging due to difficulties in fabrication, precise positioning, and frequency tuning of cavity-emitter coupling. Here, we demonstrate a simple approach to achieve a wavelength-dependent photoluminescence (PL) lifetime modification using monolithic organic molecular aggregates films. These single monolithic organic films are designed to have a Lorentzian dispersion, including epsilon-near-zero (ENZ) and epsilon-near-pole (ENP) spectral regions with increased and decreased photonic density of states, respectively. This dispersion leads to enhanced and depressed PL decay rates at different wavelengths. Both time-resolved photoluminescence (TRPL) and fluorescence lifetime imaging microscopy (FLIM) measurements are implemented to verify the validity of this approach. This approach offers a promising way to design dual-functional optical sources for a variety of applications, including bioimaging, sensing, data communications, and quantum photonics applications. [ABSTRACT FROM AUTHOR]

This study has developed new features necessary for condition monitoring and diagnosis of rotating machinery. These features are developed using the phase change of vibration signal, which is characteristic of blade rubbing fault. These developed features are intended to identify the fault's correct condition and severity of the rotating machinery. The difference between normal and blade rubbing fault was compared through experiments. The experimental model was produced to simulate a blade rubbing fault. The data were acquired through the experimental model and calculated using the developed features. Fault detection was confirmed by using genetic algorithm and machine learning that failure detection was possible using the developed features, it is expected that such study can evaluate the health of the rotating machinery. [ABSTRACT FROM AUTHOR]

Recently, with the development of the 4th industrial technology such as big data, cloud computing, and IoT, technologies that automatically perform specific tasks without human intervention are being applied in many industrial sites. In the case of rotating equipment diagnosis, features are extracted based on the shape and statistical information of the time and frequency signals of the vibration data for each location, and the acquired data is classified as normal or defective by learning it. However, since this method used the shape and statistical information of the vibration signals, the physical meaning is blurred and the information is not meaningful for actual diagnosis, resulting in inconsistent learning models even in the same facility. In this study, the possibility of classifying normal and fault condition were confirmed by generating images considering the fault component and sensor location of the vibration signal and applying to CNN-based deep learning technology. As a method of performing image processing, STFT is performed on the acquired vibration signal data for each position to generate an image. In addition, converting each sensor position attached to red, green, and blue to express location information, resynthesis was performed to configure learning data and create a classification model. In order to verify this method, verification was performed based on the data acquired for the gearbox system to confirm the possibility of classifying the fault condition. [ABSTRACT FROM AUTHOR]

Single-molecule localization microscopies have gained much attention for their efficient realization of a sub-diffraction-limit imaging with the resolution down to the 10-nm range. In contrast to conventional localization microscopes, which rely on particular fluorescent probes in specific conditions, metamaterial-assisted super-resolution microscopies can be implemented with any fluorescent dye under general conditions. Here, we present a systematic study of fluorescence engineering in metamaterial assisted localization microscopy by using cyclic group metasurfaces coated with a fluorescent film. Tailored variations are clearly demonstrated in both the photoluminescence intensity and the photobleaching lifetime of fluorophores based on the spatially varied Purcell effect near the metasurfaces. The enhanced emissions and blinking dynamics of the fluorophores on these metasurfaces lead to an increased signal-to-noise ratio, and therefore give rise to a super-resolution localization image with 0.9-nm localization accuracy. Our results are not only beneficial for super-resolution localization imaging but also push the control of light–matter interactions beyond the diffraction limit. [ABSTRACT FROM AUTHOR]

Industrial plant machines have a significantly lower frequency of defective data than the frequency of normal data. For this reason, machine learning is often applied using only some obtained state data. However, the low frequency of defect data does not guarantee that novel data occur, which is why detection of novelty class is required. This paper studies the novelty class detection method in multi-classification. Multi-class support vector machine was used for multi-classification. Cluster-based local outlier factor, histogram-based outlier score, outlier detection with minimum covariance deTerminant, isolation forest, and one-class support vector machine applied novelty class detection. Anomaly detection algorithms used the hard voting ensemble method. A feature engineering method that is advantageous for novelty class detection was confirmed by comparing the genetic algorithm (GA)-based feature selection and principal component analysis (PCA). Findings show that creating a model using GA-based feature selection for multi-classification and independent PCA for each class for novelty class detection is advantageous. With the use of an independent PCA, the problem was simplified to perform detection on a novelty class with a condition similar to the trained class. [ABSTRACT FROM AUTHOR]

Coaxial type piezoelectric energy generator (C-PEG) nanofiber was fabricated by a self-designed continuous electrospinning deposition system. Piezoelectric PVDF-TrFE nanofiber as an electroactive material was electrospun at a discharge voltage of 9–12 kV onto a simultaneously rotating and transverse moving Cu metal wire at an angular velocity of ωg = 60–120 RPM. The piezoelectric coefficient d33 of the PVDF-TrFE nanofiber was approximately −20 pm V−1. The generated output voltage (VG) increased according to the relationship exp(-αP) (α = 0.41– 0.57) as the pressure (P) increased from 30 to 500 kpa. The VG values for ten and twenty pieces of C-PEG were VG = 3.9 V and 9.5 V at P = 100 kpa, respectively, relatively high output voltages compared to previously reported values. The high VG for the C-PEG stems from the fact that it can generate a fairly high VG due to the increased number of voltage collection points compared to a conventional two-dimensional (2-dim) capacitor type of piezoelectric film or fiber device. C-PEG yarn was also fabricated via the dip-coating of a PDMS polymer solution, followed by winding with Ag-coated nylon fiber as an outer electrode. The current and power density of ten pieces of C-PEG yarn were correspondingly 22 nA cm−2 and 8.6 μW cm−3 at VG = 1.97 V, higher than previously reported values of 5.54 and 6 μW cm−3. The C-PEG yarn, which can generate high voltage compared to the conventional film/nanofiber mat type, is expected to be very useful as a wearable energy generator system. [ABSTRACT FROM AUTHOR]

In this study, a useful solution is proposed for assessing the safety of the ship's hull damaged by grounding in Northern Sea Route (NSR) or Arctic sea. In particular, the residual ultimate longitudinal strength of grounding damaged ship can be predicted by the grounding damage index (GDI) concept. Due to the global warming effects, the Arctic glaciers have been gradually melting, and it may bring us the new North Pole routes. However, there are uncertainties on many causes that can lead to grounding accident of the commercial vessels. In this regard, residual ultimate longitudinal strength of grounding damaged commercial ship in Arctic sea is investigated. Five (5) temperatures: room temperature (RT), −20°C, −40°C, −60°C and −80°C were adopted to consider the cold temperature effect in NSR. The Panamax class oil tanker was selected for the investigation of residual ultimate longitudinal strength of grounding damaged ship. Fifty (50) reliable damage scenarios were adopted for the evaluation of structural health by utilising Residual strength versus GDI (R-D) diagram method. From this study, a modified R-D diagram is proposed which can consider grounding damage with cold temperature effect. The obtained outcome will be useful for assessing the safety of the grounded ships in Arctic sea region by measuring the grounding damage amount and surrounding air temperature. [ABSTRACT FROM AUTHOR]

For the management of rotating machines, machine learning (ML) has been researched with the use of feature parameters that have physical and statistical meanings of vibration signals. Genetic algorithm (GA) and principal component analysis (PCA) are the algorithms used for the selection or extraction process of the features; equipment condition. This study proposes a new method to maximize the advantages of the extraction and selection algorithms, thereby improving the fault classification performance. The proposed method is estimated in a variety of equipment conditions by selecting and extracting the effective features for status classification. To evaluate the performance of the fault classification through feature selection and extraction of the ML, a comparative analysis with the proposed method and the original method is also performed. With Lab-scale gearbox, several types of fault tests are conducted, and seven different fault types of equipment conditions, including the normal status, are simulated. The results of the experiments show that, the performance of classification of GA for feature selection is 85%, while PCA for feature extraction is 53%. The performance result of the proposed method for fault classification is 95%, meaning that the performance of fault diagnosis is more efficient in terms of discriminative learning than the original method. Therefore, the proposed method with feature extraction and selection algorithm can improve the fault classification performance by 10% and more for fault diagnosis through ML. [ABSTRACT FROM AUTHOR]

Indium-free ZTO/Ag/ZTO multilayer electrodes were deposited on glass by RF sputtering of zinc tin oxide (ZTO) and pulsed DC sputtering of silver (Ag) at room temperature in the specially designed Inline sputtering system and evaluated as transparent electrode of organic photovoltaic cells (OPVs). The dependence of the electrical and optical properties of ZTO films on the O2/Ar + O2 ratio was investigated. We fabricated the ZTO/Ag/ZTO multilayer electrode with a sheet resistance of 8.38-10.18 Ω sq−1 and average transmittance of 84.4-85.5% in the visible region ( λ = 380-770 nm), which is compatible with commercial indium tin oxide (ITO). As an application, organic solar cells fabricated on the ZTO/Ag/ZTO multilayer electrodes with the conventional device architecture were compared with those on commercial ITO electrodes. The bulk heterojunction OPVs fabricated on the multilayer electrodes exhibited a short-circuit current ( JSC) of 7.06 mA cm−2, a fill factor (FF) of 0.62, an open-circuit voltage of ( VOC) of 0.64 V, and a power-conversion efficiency of 2.80%. This indicates that ZTO/Ag/ZTO multilayer electrode is a promising electrode scheme for bulk heterojunction organic photovoltaic cells (BHJ-OPVs). [ABSTRACT FROM AUTHOR]

Hybrid nanostructures combining inorganic materials and graphene are being developed for applications such as fuel cells, batteries, photovoltaics and sensors. However, the absence of a bandgap in graphene has restricted the electrical and optical characteristics of these hybrids, particularly their emissive properties. Here, we use a simple solution method to prepare emissive hybrid quantum dots consisting of a ZnO core wrapped in a shell of single-layer graphene. We then use these quantum dots to make a white-light-emitting diode with a brightness of 798 cd m?2. The strain introduced by curvature opens an electronic bandgap of 250 meV in the graphene, and two additional blue emission peaks are observed in the luminescent spectrum of the quantum dot. Density functional theory calculations reveal that these additional peaks result from a splitting of the lowest unoccupied orbitals of the graphene into three orbitals with distinct energy levels. White emission is achieved by combining the quantum dots with other emissive materials in a multilayer light-emitting diode. [ABSTRACT FROM AUTHOR]

A nonparametric inversion method has been employed to obtain the detailed attenuation characteristics of horizontal shear-wave Fourier spectra at high frequencies based on the large spectral dataset mostly from small earthquakes occurring at shallow depths in the southern part of the Korean Peninsula. Nonparametric expressions of the spectral attenuation were evaluated for 59 frequency bands in the range of 1 Hz ≤ f ≤ 30 Hz and hypocentral distance ranging from 10 to 400 km by applying the nonparametric inversion method to the observed spectral dataset. Based on the nonparametric expressions, three linear regions roughly separated at 60 and 110 km in distance could be identified and the use of the conventional functional form of Q 0 f η assuming the geometrical spreading of R−0.5 could be validated for 3 Hz ≤ f ≤ 30 Hz and R ≥ 190 km with the best fitting result of 292 f0.53. In the near-source region of R < 70 km, the spectral attenuation due to the geometrical spreading ranged from R−1.3 to R−1.5 irrespective of the Q-values. The distance-attenuation trend of the recent observed dataset from a moderate inland earthquake in Korea was also well predicted by the inverted nonparametric path term. [ABSTRACT FROM AUTHOR]

Ion source with closed drift, which is caused by E×B field, and extended acceleration region is discussed. Though conventional circular-type closed drift ion source has advantages of high efficiency of gas ionization and low ion beam energy, there is a limitation in enlarging the beam size. Linear ion source with horse-track shape with 270 mm ceramic channel width is newly designed and tested. Inert gas (Ar) and reactive gas (O2) are discharged. Discharge is ignited with voltage of 90 V. Discharge current is proportional to discharge voltage and increases up to 16.3 A in argon and 15.6 A in oxygen at discharge voltage of 320 V. Extracted ion beam current is also proportional to discharge voltage and is saturated after 280 V for both gases. It is measured up to 0.78 mA/cm2 in argon beam and 0.73 mA/cm2 in oxygen beam at a distance of 100 mm from the ion source. Argon ion beam shows better space uniformity than oxygen across the beam extraction region. [ABSTRACT FROM AUTHOR]

The effect of electrode materials on resistance switching was evaluated on the Pt/NiO/electrode (EL) structures where the EL contacts were Pt, Al, and indium–tin-oxide (ITO). It was confirmed that ohmic Pt contact needs to induce the effective electric field for resistance switching across the NiO film. For the Pt/NiO/Al structure, the barrier height of the Al Schottky contact was measured as 0.66 eV and no resistance switching was observed owing to a large voltage drop at the rectifying interface induced by the reduction of NiO resulting from the formation of Al oxide. In the ITO (EL)/NiO/Pt structure, the barrier height of the Schottky contact between ITO and NiO was about 0.52 eV and it did not show any resistance switching, either. Through the depth-profile study by X-ray photoelectron spectroscopy, chemical reactions at the interface ITO/NiO was identified to be not too much evolved compared with that of NiO/Al, which might due to be abundant oxygen on the ITO surface. Such Schottky barrier heights 0.52–0.66 eV were considered too high to induce a sufficient electric field in the NiO film causing the resistance switching. [ABSTRACT FROM AUTHOR]

We fabricated the organic photovoltaic (OPV) cells on the transparent and low resistive multilayer electrode of a few nm Ag layer embedded Al doped zinc oxide film (AZO/Ag/AZO) on a glass. AZO and Ag consisting of the continuous multilayer were fabricated using rf magnetron at room temperature successively. AZO (45 nm)/Ag (11 nm)/AZO (45 nm) electrode shows an electrical resistivity of 6.56×10-5 Ω cm, optical transmittance of 89.3% at 550 nm and figure of merit (FOM) value of 4.94×10-2 Ω-1. An inverted structure OPV was fabricated on AZO/Ag/AZO transparent electrode in which TiOx and PEDOT:PSS were used as an electron transport and hole transport layer respectively. The OPVs showed power conversion efficiency and fill factor as high as 2.07%, 0.51 respectively. [ABSTRACT FROM AUTHOR]

A hybrid polymer-quantum dots (QDs) white light-emitting diode (WLEDs) device with a multi-layer structure by all solution processing is simply fabricated by using a spin coating technique. From transmission electron microscopy (TEM) study, red–green–blue (RGB) CdSe/ZnS QDs are mainly distributed along with the circumference of poly(N-vinylcarbazole) (PVK) surfaces, resulting in core–shell hybrid polymer-QDs of [RGB CdSe/ZnS QDs]/PVK. The Al/Cs2CO3/[RGB CdSe/ZnS QDs+PVK]/poly[(N,N '-bis(4-butylphenyl)-N,N '-bis(phenyl)benzidine)] (poly-TPD)/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS)/indium–tin-oxide (ITO)/glass WLEDs shows electroluminescence (EL) centered at around 474, 544, and 629 nm with CIE coordinates, (0.44,0.32) at the forward bias +11 V, which clearly reveals that CdSe/ZnS QDs existing at the interface between PVK plays as a recombination center of exciton. [ABSTRACT FROM AUTHOR]