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In the southeast and east coasts of the Republic of Korea, it is essential to monitor mercury accumulation in coastal organisms in view of the higher mercury distribution in sediments and human samples. However, mercury pollution monitoring in organisms, especially higher trophic-level organisms that can exhibit high mercury accumulation, is limited. Here, we examined the applicability of the eggs of the black-tailed gull (Larus crassirostris), which belongs to a high trophic level, for mercury monitoring in coastal areas. Breeding sites were selected in West, Southeast, and East Seas with different mercury concentrations in other matrices (sediment and biological samples of residents). The 5-year mean total mercury concentration in eggs collected during the breeding seasons from 2016 to 2020 was lower in Baengnyeongdo (705 ± 81 ng/g dry weight (dry), West Sea) than in Hongdo (1,207 ± 214 ng/g dry, Southeast Sea) and Ulleungdo (1,095 ± 95 ng/g dry, East Sea). The different patterns of mercury concentration in gull eggs among the breeding sites was consistent with those in the other matrices among the coastal areas. These results support the applicability of the black-tailed gull egg as an indicator for establishing a monitoring framework in the coastal areas of the Republic of Korea. [Display omitted] • Black-tailed gull eggs are used as an indicator sample for monitoring Hg pollution. • Different patterns of Hg concentrations were observed in three breeding sites. • Sea birds with high trophic levels can biomagnify environmental Hg. [ABSTRACT FROM AUTHOR]

Accurate predictions of extreme water temperatures are criticalto understanding the variability of the marine environment and reducing marine disasters maximized by global warming. In this study, we propose a two-pathway framework with separated spatial and temporal encoders for accurate prediction of water temperature, especially extremely high water temperature, through effective spatiotemporal representation learning. The spatial and temporal encoder networks based on the Transformer's self-attention mechanism performs the task of predicting the water temperature time series at the 16 coastal locations around the Korean Peninsula for the seven consecutive days ahead at daily intervals with various combinations of patch embedding methods, positional embedding for spatial features. Comparative experiments with conventional deep convolutional and recurrent networks are also conducted for comparison. By comparing and assessing these results, the proposed two-pathway framework can improve the predictability of extremely high coastal water temperature by better capturing spatiotemporal interrelationships and long-range dependencies from open ocean and regional sea, and further determines the optimal architectural details of self-attention-based spatial and temporal encoders. Furthermore, to examine the explainability of the proposed model and its consistency with domain knowledge, spatial and temporal attention maps are visualized and analyzed that represents weights for spatiotemporal input sequences that are more relevant to predict for future predictions. • Development of two-pathway spatiotemporal representation learning framework for consecutive multi-step-ahead SST prediction. • Spatiotemporal representation learning to capture the temporally correlated regional to local spatial dependencies. • Notable predictability of extreme coastal SST for consecutive 7-day ahead spatiotemporal forecasts. • Visualization of attention map to secure domain knowledge-based validity and explainability of model predictions. • Discovering spatiotemporal teleconnections of SST variability and its consistency with ocean dynamics. [ABSTRACT FROM AUTHOR]

This paper proposes a spatiotemporal graph neural network capable of effective representation learning of the spatiotemporal interrelationships and interdependencies of in-situ observation data from multiple locations for multivariate multi-step ahead time-series forecasting. The propose model is largely composed of graph learning, spatial encoder, and temporal decoder, and ablation studies on variants of the three modules and comparative experiments with state-of-the-art deep neural networks for sequence modeling were also performed extensively. The proposed model showed improved predictability than conventional numerical model-based approaches or state-of-the-art models by applying consecutive multi-step ahead time-series prediction of sea surface temperature at multiple locations along the coast. For more rigorous performance evaluation, not only the overall performance of the test data, but also the performance of extreme cases included in the test data based on historical records were separately assessed. The prediction rationales were also presented through quantified relative contributions between neighbor locations using the trained adjacency matrix obtained through graph learning. The results showed that it is well consistent with the ocean physics and geographical domain knowledge, demonstrating the feasibility and reliability of the proposed method. Therefore, the proposed method shows sufficient potential to be used as a scientific tool for decision-making in extreme events such as marine heat waves or for operational ocean forecasting. [ABSTRACT FROM AUTHOR]

Abstract By utilizing a novel design of an electronic device with microfabricated through-etched slits for transmission electron microscopy (TEM), single-walled carbon nanotubes (SWNTs) suspended over two metal electrodes were successfully characterized. A semiconducting-semiconducting intramolecular junction (IMJ) was found from a change in chirality along the tube. Interestingly non-linear current-voltage characteristic was found despite almost negligible difference in the band-gap energy (13 meV). The non-linear electrical transport property can be caused by asymmetric defect states positioned in the band-gap of two semiconducting tubes, which make one as donor (similar to a p-type semiconductor) and the other as acceptor (similar to n-type semiconductor). The strain by deformation along the tube can also cause the electrical non-linearity. Graphical abstract Image 1 [ABSTRACT FROM AUTHOR]

A patchable triboelectric nanogenerator (TENG) is highly promising for self-powered human-motion detection, but it may undergo repeated stretching/releasing cycles during daily activities of a human, which may lead to mechanical fracture of each component and degradation in electrical output performance of the TENG device. Here, we report a fully stretchable and durable triboelectric nanogenerator (TENG) with gold (Au) nanosheets (NSs) embedded into both PDMS matrix and micropyramid-patterned PDMS. It was found that a new design of the Au NS electrodes dramatically improves the mechanical flexibility and stretchability, enabling to achieve the outstanding output stability of the Au NS electrode-based TENG (Au NS-TENG) during 10,000 cycles of repeated pushing and stretching tests. Our fully stretchable and durable Au NS-TENGs were successfully applied to the hand joints that can be used in the self-powered human-motion detection processes for wearable applications. [ABSTRACT FROM AUTHOR]

Degradation of Ir based blue phosphorescent emitters was analyzed from the viewpoint of triplet-polaron annihilation (TPA) of the emitters. Two different classes of Ir emitters, F substituted phenylpyridine type Ir emitter and F substituted phenylimidazole type Ir emitter, were compared as the blue emitters. Aging test of singlet carrier devices of the Ir emitters under polaron, exciton, and exciton-polaron revealed that the phenylimidazole type Ir emitter was relatively more resistant to the TPA degradation than the phenylpyridine type Ir emitter and extended the lifetime of blue phosphorescent organic light-emitting diodes. In addition, the lifetime and degradation of the short-living blue phosphorescent devices were improved by the host material suppressing the TPA under negative polaron using an electron scattering emitting layer structure. [ABSTRACT FROM AUTHOR]

This study proposes a spatio-temporal geographical information-guided neural network to predict multi-step ahead space-time series of ocean waves. The network is designed to learn the ocean wave dynamics from external atmospheric forcing and internal wave processes. It also captures the nonlinear relationships in multiple input and at the spatial and temporal levels and shares their dependencies. The model learns these dependencies through a convoluted encoded latent feature, while a decoder predicts the space-time series of ocean waves from the latent representations. The model is trained on 35 years of a state-of-the-art global reanalysis dataset produced at 1-hour temporal and 25 km spatial resolutions around the Korean Peninsula. It is evaluated by predicting the same resolution's multi-step ahead space-time series of ocean waves for a 48-hour forecast lead time for the 5 years not used for training. We conducted an ablation experiment to determine the optimal model architecture, input variable, and training period. The prediction results are compared and analyzed with the in-situ ocean wave measurements at the 18 observation stations. We consider the prediction results according to the start time of prediction with the in-situ measurements and hindcast results to examine the performance on the high waves that caused wave-induced disaster. • STG-OceanWaveNet is developed to accurately predict waves by emulating wave dynamics. • The RMSE of 48-hours ahead SWH and MWP is 0.4 m and 0.5 sec. for the 5 years. • Compared with in-situ measurements, the RMSE for SWH and MWP are 0.35 m and 0.55 sec. • The deep learning approach is feasible to predict ocean waves with reliable accuracy. [ABSTRACT FROM AUTHOR]

Durable drag-reduction surfaces have recently received much attention, due to energy-saving and power-consumption issues associated with harsh environment applications, such as those experienced by piping infrastructure, ships, aviation, underwater vehicles, and high-speed ground vehicles. In this study, a durable, metallic surface with highly ordered hierarchical structures was used to enhance drag-reduction properties, by combining two passive drag-reduction strategies: an air-layer effect induced by nanostructures and secondary vortex generation by micro-riblet structures. The nanostructures and micro-riblet structures were designed to increase slip length. The top–down fabrication method used to form the metallic hierarchical structures combined laser interference lithography, photolithography, thermal reflow, nanoimprinting, and pulse-reverse-current electrochemical deposition. The surfaces were formed from nickel, which has high hardness and corrosion resistance, making it suitable for use in harsh environments. The drag-reduction properties of various metal surfaces were investigated based on the surface structure: a bare surface, a nanostructured surface, a micro-riblet surface, and a hierarchically structured surface of nanostructures on micro-riblets. [ABSTRACT FROM AUTHOR]

Recently, the development of durable hydrophobic surfaces has received much attention, with anti-icing applications in harsh environments such as aircrafts, wind turbines, power lines, and marine vessels. In this paper we describe a design methodology employing a lattice Boltzmann method to determine the optimal geometry of microstructures to achieve superhydrophobicity. We describe a top-down fabrication method to form superhydrophobic micro-hierarchical metal surface using photolithography, nanoimprinting, and continuous metal-to-metal replication using pulse-reverse-current electrochemical deposition. The surfaces were formed of nickel, which has a large hardness and is resistant to corrosion, making it suitable for use in harsh external conditions. We compared the measured wettability of fabricated micro-hierarchical metal surface with that from numerical simulations. The contact angle and contact angle hysteresis of four metal surfaces were measured (i.e., a bare surface, a random nanostructured surface, an engineered nanostructured surface, and an engineered hierarchical structured surface), and the anti-icing properties of these four metal surfaces were investigated. [ABSTRACT FROM AUTHOR]

• A novel measurement sensitivity analysis method is suggested for DUV scatterfield microscopy.- Parametric measurement coefficient maps are presented for partial coherence and duty ratio. • Parametric measurement coefficient maps are presented for partial coherence and duty ratio. • Efficient illumination is enabled based on the optimized partial coherence. • This can be applied to high resolution imaging, biomedical imaging, and scattering-based dimensional measurement. The deep ultraviolet (DUV) scatterfield imaging microscopy technique enables accurate dimensional measurements of periodic nanostructures with sub-nanometer sensitivity to support semiconductor device manufacturing. A parametric sensitivity analysis for targets with uneven duty ratios is essential as the duty ratios of many periodic nanostructures vary in practice. This paper presents an experimental implementation to optimize illumination conditions for nanoscale multi-line targets on a Molybdenum Silicide (MoSi) photomask with duty ratios of 0.43 to 0.68 using a scatterfield imaging microscope with 193 nm wavelength laser designed for angle-resolved illumination at the sample. Measurement sensitivities are analyzed using sensitivity coefficient maps parameterized by partial coherence factor, duty ratio of the target, and incident polarization. [ABSTRACT FROM AUTHOR]

Abstract: We present the design and operation of a transmission electron microscopy (TEM)-compatible carbon nanotube (CNT) field-effect transistor (FET). The device is configured with microfabricated slits, which allows direct observation of CNTs in a FET using TEM and measurement of electrical transport while inside the TEM. As demonstrations of the device architecture, two examples are presented. The first example is an in situ electrical transport measurement of a bundle of carbon nanotubes. The second example is a study of electron beam radiation effect on CNT bundles using a 200keV electron beam. In situ electrical transport measurement during the beam irradiation shows a signature of wall- or tube-breakdown. Stepwise current drops were observed when a high intensity electron beam was used to cut individual CNT bundles in a device with multiple bundles. [Copyright &y& Elsevier]

Transition metal layered double hydroxides (LDHs) have received much attention as high-performance oxygen evolution reaction (OER) catalysts due to their large number of active sites with favorable adsorption/desorption energies for intermittent reactants. However, the relatively sluggish charge transfer kinetics of transition metal LDHs due to their intrinsically low conductivity often hinders their use in practical applications as high-performance water oxidation catalysts. Here, we disclose a novel strategy of metalloid incorporation into transition metal LDHs, allowing us to simultaneously optimize surface electronic configuration and charge transfer between adsorbed reactants and catalyst surface. Importantly, incorporated metalloid can enhance the density of states (DOS) near the Fermi level and alter the nature of the chemical bonds in the catalytically active atoms, resulting in fast reaction kinetics. Thus, metalloid incorporation into transition metal LDHs can substantially improve the overall reaction kinetics and thermodynamics for water oxidation due to a large number of active sites and high conductivity, boosting OER performance of transition metal LDHs. The metalloid-incorporated transition metal LDHs far outperform their counterpart transition metal LDHs and even the noble metal catalyst RuO 2. Metalloid incorporation into transition metal LDHs can be a promising strategy for designing highly efficient and robust electrocatalysts for alkaline OER. Image 1 • Atomic scale engineering using metalloid elements for transition metal layered double hydroxides (LDHs) is firstly developed. • Strategic tellerium (Te) incorporation at the atomic level on edge cobalt (Co) sites is found to be crucial for the improvement of electrical conductivity. • Tailored d-band electronic structure occured via p-d hybridization when Te incorporates into NiCo-LDHs leading to enhanced water oxidation properties. • Te-NiCo LDHs shows very low overpotential of 190 mV at a current density of 10 mA cm-2, respectively, with the lowest Tafel slope of 23.38 mVdec-1 for water oxidation. • Density functional theory (DFT) calculations revealed individual roles of elements in Te-NiCo LDHs for water oxidation. [ABSTRACT FROM AUTHOR]

A biomimetic-villus structure that has been fabricated using a three-dimensional (3D) printer, which is a high-resolution additive-manufacturing process, is here introduced for the realizing of a large increase of the surface area beyond the structural limitations, and the intestinal-villus structure that can be produced only by a 3D printer is imitated. The surface area of the 3D-printed biomimetic-villus structure was increased by approximately 300% compared with the planar structure, and to achieve the full contact of this increased surface area, polytetrafluoroethylene (PTFE) powder was used as the triboelectric material, resulting in fivefold and fourfold increases of the electric power output performance in the vertical-direction mode and the rotational-direction mode, respectively. In addition, a dust-filtration system was designed using the large electrostatic charge that formed between an acrylonitrile butadien styrene (ABS) surface and PTFE powders, and dust particles of various sizes were efficiently adsorbed. Further, because of the use of the polymer-based ABS and the PTFE powers, the dust filter is stable and easily reusable, and it was experimentally confirmed after a washing that the filtration efficiency of 41% is nondecreasing. As a result, a successful validation of the use of the 3D-printed biomimetic-villus structure with the maximized surface area as an ecofriendly dust-adsorption system as well as a triboelectric nanogenerator was achieved. We report a complex biomimetic-villus structure that would be extremely difficult to synthesize without the aid of 3D printing technology, and thereof system exhibits 300% increase in surface area. Given feature is favorable for TENG, with a polytetrafluoroethylene powder gets in contact aiming to reach superior level of triboelectrification. We verifies not only theoretically but also experimentally that 3D printing technology provides a key to improve performance of TENG, and also presents it develops new class of application, dust filter. Image 1 • We report 3D printed biomimetic villus (BV) structure with high surface area (~300%) forming strong electrostatic charge. • Our findings reveal that 3D printed BV-PTFE pair allows mechanical energy harvesting and fine dust filtering application. • We demonstrate that 3D printed TENG is driven by mechanical energy, where the vertical/rotational motions are employed. • We confirmed that level of electrostatic charge is formed in dust collection, and durability after washing was verified. [ABSTRACT FROM AUTHOR]

Comprehensive study to understand the degradation mechanism of high efficiency blue organic light-emitting diodes by charge transport layers was carried out by managing the device parameters and charge transport materials. Although it has been generally accepted that the charge transport layers are important for long lifetime, the degradation mechanism was not clear. From this work, it was revealed that exciton quenching of emitters by the degradation products of charge transport layers is the main degradation pathway of blue phosphorescent and thermally activated delayed fluorescent organic light-emitting diodes. It was described that the degradation of the blue devices by the charge transport layers would be largely avoided by separating the exciton generating emitters from the charge transport layers by shifting the exciton formation zone to the center of the emitting layer. Eventually, the lifetime of the blue devices with the emission zone fall apart from the charge transport layers was not affected by the charge transport layers because exciton quenching by the degradation products of the charge transport layers was suppressed. [ABSTRACT FROM AUTHOR]

The pursuit of hybridized local and charge transfer (HLCT) excited state-based emitters is a promising strategy to achieve high external quantum efficiency in blue organic light-emitting diodes (OLEDs). Two isomeric dimethyl-dihydroindenocarbazole-anthracene-phenanthroimidazole-based emissive molecules (PhAnsIn and PhAnoIn) were designed and explored based on the HLCT scheme. All molecules possessed the HLCT excited-state characters, according to the photophysical investigation and density functional theory calculations. Consequently, PhAnsIn and PhAnoIn showed good blue emission with peaks at 457 and 464 nm and photoluminescence quantum yield of 80.6% and 56.5% in neat films, respectively. The fabricated blue OLEDs with PhAnsIn and PhAnoIn as emitters also realized the corresponding blue emission with electroluminescence peaks at 458 and 457 nm, respectively. The nondoped devices based on PhAnsIn and PhAnoIn exhibited maximum external quantum efficiencies of 8.2% and 8.5% with CIE coordinates of (0.14, 0.12) and (0.14, 0.11), respectively. • Hybridized local and charge transfer excited state based blue fluorescence emitter. • High photoluminescence quantum yield of 80.6% in a neat film. • Non-doped blue fluorescence organic light-emitting diodes with external quantum efficiency of 8.2%. [ABSTRACT FROM AUTHOR]

"Hot-exciton" materials exhibiting high-lying reverse intersystem crossing (hRISC) are promising candidates for organic light-emitting diode (OLED) materials owing to their improved exciton utilization efficiency and efficiency roll-off. To investigate the excited-state structure–property relationship in anthracene/benzophenone-based materials, we designed and prepared three anthracene-benzophenone derivatives by varying substituents at peripheral benzophenone units, namely, AnBP-F , AnBP-H , and AnBP-OMe. Systematic investigation of the excited-state properties of these compounds and DFT calculations showed that they have hybridized local and charge-transfer (HLCT) characteristics in their emissive transitions. All prepared compounds were adapted in a non-doped OLED device, which exhibited an external quantum efficiency (EQE) of up to 2.88%. To further study the exciton dynamics in the device, magnetoelectroluminescence was measured, which exhibits the combined characteristics of triplet–triplet annihilation (TTA) and HLCT mechanisms. [Display omitted] • Anthracene/benzophenone-based HLCT emitters were prepared by varying substituents at peripheral benzophenone units. • Substituents help to tune the nature of the excited state. • Non-doped OLEDs achieved EQE max of 2.88%. • Studies on the exciton dynamics of the device indicate that the TTA and HLCT mechanisms concurrently exist. [ABSTRACT FROM AUTHOR]

We demonstrate the use of a parallel detection system with a nanograting-based microarray to accomplish high-throughput analysis of bio-molecular interactions in a label-free manner. Well-type label-free microarrays were fabricated to eliminate the risk of cross-contamination and to minimize sample volumes. Parallel analysis without the use of spectrometer arrays or a moving platform was accomplished by using scanning multiple optical probes generated by a spatial light modulator and microlens array. Additionally, multiple optical probe spots focused by the microlens array reduced detection errors while enhancing the signal-to-noise ratio within a high-density microarray. Finally, we verified the feasibility of the parallel detection system by analyzing the peak wavelength value (PWV) shift of human salivary cortisol and anti-cortisol in a competitive binding experiment. [ABSTRACT FROM AUTHOR]

Abstract: Combustion measurements were conducted to investigate the combustion characteristics of blends of biomass and coals of different ranks. A laboratory-scale slit burner, which more accurately represents the conditions for a practical flame with a high heating rate and jet velocity, was adopted in the present work based on thermal analytical results. The results of a thermogravimetric analysis revealed that the great amount of volatile matter in the biomass and the rapid emission of this volatile matter under low temperature, which contribute to the accelerated ignition at a lower temperature, increased the particle surface temperature and enhanced the reactivity on the surface of a low-rank coal. The combustion performance of a low-rank coal could be improved with a biomass addition, while the biomass addition had no apparent impact on the combustion performance of a high-rank coal. In addition, combustion characteristics such as the mean flame temperature and reaction region were investigated using a laboratory-scale slit burner. Adding 10% biomass to the blends improved the combustion efficiency of a low-rank coal. In the co-combustion of a low-rank coal and biomass, this 10% biomass addition enhanced the ignition and promoted reactivity in the volatile reaction region through a synergetic effect between the low-rank coal and biomass. [Copyright &y& Elsevier]

Abstract: Materials inspired by nature comprise a running theme of modern science. Among the crystals that can be formed, diamond is perhaps most emblematic. In the conventional thinking, natural diamonds form only under high-pressure and high-temperature conditions. Here we show a new, natural form of diamond crystals of high quality that are epitaxial with their ruby substrate. Diamonds in rubies are rare; heteroepitaxial diamonds are twice as unexpected. Epitaxy suggests that the natural diamonds in the rubies were formed after ruby crystallization in a thermodynamically diamond stable region. This striking natural control over diamond epitaxy suggests a general strategy by which to form naturally-inspired, gem-quality crystals. [Copyright &y& Elsevier]

Summary Dynamic coupling of microtubule ends to kinetochores, built on the centromeres of chromosomes, directs chromosome segregation during cell division. Here, we report that the evolutionarily ancient kinetochore-microtubule coupling machine, the KMN (Knl1/Mis12/Ndc80-complex) network, plays a critical role in neuronal morphogenesis. We show that the KMN network concentrates in microtubule-rich dendrites of developing sensory neurons that collectively extend in a multicellular morphogenetic event that occurs during C. elegans embryogenesis. Post-mitotic degradation of KMN components in sensory neurons disrupts dendritic extension, leading to patterning and functional defects in the sensory nervous system. Structure-guided mutations revealed that the molecular interface that couples kinetochores to spindle microtubules also functions in neuronal development. These results identify a cell-division-independent function for the chromosome-segregation machinery and define a microtubule-coupling-dependent event in sensory nervous system morphogenesis. Graphical Abstract Highlights • Kinetochore-microtubule coupling machinery acts in developing post-mitotic neurons • Post-mitotic removal of kinetochore components disrupts the sensory nervous system • Kinetochore components concentrate in sensory dendrites and promote their extension • The microtubule-coupling interface in developing neurons and mitosis is similar The conserved Knl1/Mis12/Ndc80 (KMN) network constitutes the microtubule-coupling interface at kinetochores in mitosis. Cheerambathur et al. find that the KMN network also acts in the developing sensory nervous system. KMN components concentrate in dendrites of developing neurons and promote their extension, employing the same microtubule-coupling interface that acts in mitosis. [ABSTRACT FROM AUTHOR]