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Salt, one of the most commonly consumed food additives worldwide, is produced in many countries. The chemical composition of edible salts is essential information for quality assessment and origin distinction. In this work, a simple laser-induced breakdown spectroscopy instrument was assembled with a diode-pumped solid-state laser and a miniature spectrometer. Its performances in analyzing Mg and Ca in six popular edible sea salts consumed in South Korea and classification of the products were investigated. Each salt was dissolved in water and a tiny amount of the solution was dropped and dried on the hydrophilicity-enhanced silicon wafer substrate, providing homogeneous distribution of salt crystals. Strong Mg II and Ca II emissions were chosen for both quantification and classification. Calibration curves could be constructed with limits-of-detection of 87 mg/kg for Mg and 45 mg/kg for Ca. Also, the Mg II and Ca II emission peak intensities were used in a k-nearest neighbors model providing 98.6% classification accuracy. In both quantification and classification, intensity normalization using a Na I emission line as a reference signal was effective. A concept of interclass distance was introduced, and the increase in the classification accuracy due to the intensity normalization was rationalized based on it. Our methodology will be useful for analyzing major mineral nutrients in various food materials in liquid phase or soluble in water, including salts.
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Millions of tons of plastics enter the oceans yearly, and they can be fragmented by ultraviolet and mechanical means into nanoplastics. Here, we report the direct observation of nanoplastics in global ocean water leveraging a unique shrinking surface bubble deposition (SSBD) technique. SSBD involves optically heating plasmonic nanoparticles to form a surface bubble and leveraging the Marangoni flow to concentrate suspended nanoplastics onto the surface, allowing direct visualization using electron microscopy. With the plasmonic nanoparticles co-deposited in SSBD, the surface-enhanced Raman spectroscopy effect is enabled for direct chemical identification of trace amounts of nanoplastics. In the water samples from two oceans, we observed nanoplastics made of nylon, polystyrene, and polyethylene terephthalate-all common in daily consumables. The plastic particles have diverse morphologies, such as nanofibers, nanoflakes, and ball-stick nanostructures. These nanoplastics may profoundly affect marine organisms, and our results can provide critical information for appropriately designing their toxicity studies.
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Thin-film optical diodes are important elements for miniaturizing photonic systems. However, the design of optical diodes relies on empirical and heuristic approaches. This poses a significant challenge for identifying optimal structural models of optical diodes at given wavelengths. Here, we leverage a quantum annealing-enhanced active learning scheme to automatically identify optimal designs of 130 nm-thick optical diodes. An optical diode is a stratified volume diffractive film discretized into rectangular pixels, where each pixel is assigned to either a metal or dielectric. The proposed scheme identifies the optimal material states of each pixel, maximizing the quality of optical isolation at given wavelengths. Consequently, we successfully identify optimal structures at three specific wavelengths (600, 800, and 1000 nm). In the best-case scenario, when the forward transmissivity is 85%, the backward transmissivity is 0.1%. Electromagnetic field profiles reveal that the designed diode strongly supports surface plasmons coupled across counterintuitive metal-dielectric pixel arrays. Thereby, it yields the transmission of first-order diffracted light with a high amplitude. In contrast, backward transmission has decoupled surface plasmons that redirect Poynting vectors back to the incident medium, resulting in near attenuation of its transmission. In addition, we experimentally verify the optical isolation function of the optical diode.
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Understanding the dynamics of surface bubble formation and growth on heated surfaces holds significant implications for diverse modern technologies. While such investigations are traditionally confined to terrestrial conditions, the expansion of space exploration and economy necessitates insights into thermal bubble phenomena in microgravity. In this work, we conduct experiments in the International Space Station to study surface bubble nucleation and growth in a microgravity environment and compare the results to those on Earth. Our findings reveal significantly accelerated bubble nucleation and growth rates, outpacing the terrestrial rates by up to ~30 times. Our thermofluidic simulations confirm the role of gravity-induced thermal convective flow, which dissipates heat from the substrate surface and thus influences bubble nucleation. In microgravity, the influence of thermal convective flow diminishes, resulting in localized heat at the substrate surface, which leads to faster temperature rise. This unique condition enables quicker bubble nucleation and growth. Moreover, we highlight the influence of surface microstructure geometries on bubble nucleation. Acting as heat-transfer fins, the geometries of the microstructures influence heat transfer from the substrate to the water. Finer microstructures, which have larger specific surface areas, enhance surface-to-liquid heat transfer and thus reduce the rate of surface temperature rise, leading to slower bubble nucleation. Our experimental and simulation results provide insights into thermal bubble dynamics in microgravity, which may help design thermal management solutions and develop bubble-based sensing technologies.
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In this study, we explored magnetic nanoparticles translocating through a nanopore in the presence of an inhomogeneous magnetic field. By detecting the ionic current blockade signals with a silicon nitride nanopore, we found that the translocation velocity that is driven by magnetic and hydrodynamic forces on a single magnetic nanoparticle can be accurately determined and is linearly proportional to the magnetization of the magnetic nanoparticle. Thus, we obtained the magneto-susceptibility of an individual nanoparticle and the average susceptibility over one hundred particles within a few minutes.
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Técnicas Eletroquímicas , Nanopartículas de Magnetita/análise , Nanoporos , Eletrodos , Luz , Campos Magnéticos , Espalhamento de Radiação , Compostos de Silício/químicaRESUMO
The development of aqueous zinc-ion batteries (AZIBs) faces significant challenges because of water-induced side reactions arising from the high water activity in aqueous electrolytes. Herein, a quasi-solid-state electrolyte membrane with low water activity is designed based on a laponite (LP) nanoclay for separator-free AZIBs. The mechanically robust LP-based membrane can perform simultaneously as a separator and a quasi-solid-state electrolyte to inhibit dendrite growth and water-induced side reactions at the Zn/electrolyte interface. A combination of density functional theory calculations, theoretical analyses, and experiments ascertains that the water activities associated with self-dissociation, byproduct formation, and electrochemical decomposition could be substantially suppressed when the water molecules are absorbed by LP. This could be attributed to the high water adsorption and hydration capabilities of LP nanocrystals, resulting from the strong Coulombic and hydrogen-binding interactions between water and LP. Most importantly, the separator-free AZIBs exhibit high capacity retention rates of 94.10% after 2,000 cycles at 1 A/g and 86.32% after 10,000 cycles at 3 A/g, along with enhanced durability and record-low voltage decay rates over a 60-day storage period. This work provides a fundamental understanding of water activity and demonstrates that LP nanoclay is promising for ultrastable separator-free AZIBs for practical energy storage applications.
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Although graphene looks attractive to replace indium tin oxide (ITO) in optoelectronic devices, the luminous efficiency of light emitting diodes (LEDs) with graphene transparent conducting electrodes has been limited by degradation in graphene taking place during device fabrication. In this study, it was found that the quality of graphene after the device fabrication was a critical factor affecting the performance of GaN-based LEDs. In this paper, the qualities of graphene after two different device fabrication processes were evaluated by Raman spectroscopy and atomic force microscopy. It was found that graphene was severely damaged and split into submicrometer-scale islands bounded by less conducting boundaries when graphene was transferred onto LED structures prior to the GaN etching process for p-contact formation. On the other hand, when graphene was transferred after the GaN etch and p-contact metallization, graphene remained intact and the resulting InGaN/GaN LEDs showed electrical and optical properties that were very close to those of LEDs with 200 nm thick ITO films. The forward-voltages and light output powers of LEDs were 3.03 V and 9.36 mW at an injection current of 20 mA, respectively.
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The adsorption and desorption behavior of the refrigerant HFC-134a on pitch-based activated carbon fibers (ACFs) with various Brunauer-Emmett-Teller surface areas was investigated by the flow method. Fixed-bed adsorption experiments performed at 20, 5, -15, -20, and -25 °C showed that the use of lower temperatures resulted in an increase in the adsorption capacity of the ACF. In particular, the complete adsorption time was dramatically increased at -25 °C. Crucially, even after five cycles of adsorption at -20 °C and desorption at 30 °C of HFC-134a in a electrothermal swing adsorption apparatus, significant decreases in the adsorption capability were not observed. The desorption of HFC-134a from saturated ACF was carried out using electric power directly applied to the ACF itself. The electric heating increased the ACF temperature, causing desorption within several minutes. The results of this study show that the regenerative adsorption of HFC-134a by ACF coupled with electric power is possible.
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In this study, the effects of surface roughness and pore characteristics on fatigue lives of laser powder bed fusion (LPBF) Ti-6Al-4V parts were investigated. The 197 fatigue bars were printed using the same laser power but with varied scanning speeds. These actions led to variations in the geometries of microscale pores, and such variations were characterized using micro-computed tomography. To generate differences in surface roughness in fatigue bars, half of the samples were grit-blasted and the other half were machined. Fatigue behaviors were analyzed with respect to surface roughness and statistics of the pores. For the grit-blasted samples, the contour laser scan in the LPBF strategy led to a pore-depletion zone isolating surface and internal pores with different features. For the machined samples, where surface pores resemble internal pores, the fatigue life was highly correlated with the average pore size and projected pore area in the plane perpendicular to the stress direction. Finally, a machine learning model using a drop-out neural network (DONN) was employed to establish a link between surface and pore features to the fatigue data (logN), and good prediction accuracy was demonstrated. Besides predicting fatigue lives, the DONN can also estimate the prediction uncertainty.
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Plasmonic coupling of metallic nanostructures with two-dimensional molybdenum disulfide (MoS2) atomic layers is an important topic because it provides a pathway to manipulate the optoelectronic properties and to overcome the limited optical cross-section of the materials. Plasmonic enhanced light-matter interaction of a MoS2 layer is known to be mainly governed by optical field enhancement and the Purcell effect, while the discrimination of the contribution from each mechanism to the plasmonic enhancement is challenging. Here, we investigate photoluminescence (PL) enhancement from few-layer MoS2 transferred on Au nanostructure arrays with controlled localized surface plasmon resonance (LSPR) spectral positions that were detuned from the excitation wavelengths. Two distinctive regimes in LSPR mode-dependent PL enhancement were revealed showing a maximum enhancement (â¼40-fold) with zero detuning and a modest enhancement (â¼10-fold) with the red-shift detuned LSPR from the excitation wavelength, which were attributed to LSPR-induced optical field enhancement and the Purcell effect, respectively. By applying the experimental parameters into the Purcell effect formalism, an effective mode volume of â¼0.016λ03 was estimated. Our work provides an insight into how to utilize few-layer MoS2 as a base material for optoelectronics by harnessing Purcell-enhanced optical responsivity.
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Fabrication of plasmonic nanostructures in a precise and reliable manner is a topic of huge interest because their structural details significantly affect their plasmonic properties. Herein, we present nanotip indentation lithography (NTIL) based on atomic force microscopy (AFM) indentation for the patterning of plasmonic nanostructures with precisely controlled size and shape. The size of the nanostructures is controlled by varying the indentation force of AFM tips into the mask polymer; while their shapes are determined to be nanodisks (NDs) or nanotriangles (NTs) depending on the shapes of the AFM tip apex. The localized surface plasmon resonance of the NDs is tailored to cover most of the visible-wavelength regime by controlling their size. The NTs show distinct polarization-dependent plasmon modes consistent with full-wave optical simulations. For the demonstration of the light-matter interaction control capability of NTIL nanostructures, we show that photoluminescence enhancement from MoS2 layers can be deliberately controlled by tuning the size of the nanostructures. Our results pave the way for the AFM-indentation-based fabrication of plasmonic nanostructures with a highly precise size and shape controllability and reproducibility.
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We propose three quality control (QC) techniques using machine learning that depend on the type of input data used for training. These include QC based on time series of a single weather element, QC based on time series in conjunction with other weather elements, and QC using spatiotemporal characteristics. We performed machine learning-based QC on each weather element of atmospheric data, such as temperature, acquired from seven types of IoT sensors and applied machine learning algorithms, such as support vector regression, on data with errors to make meaningful estimates from them. By using the root mean squared error (RMSE), we evaluated the performance of the proposed techniques. As a result, the QC done in conjunction with other weather elements had 0.14% lower RMSE on average than QC conducted with only a single weather element. In the case of QC with spatiotemporal characteristic considerations, the QC done via training with AWS data showed performance with 17% lower RMSE than QC done with only raw data.
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Aprendizado de Máquina , Controle de Qualidade , Tempo (Meteorologia)RESUMO
We report the design, construction, and operation results of an 18 T 70 mm cold-bore high temperature superconductor (HTS) no-insulation (NI) magnet, which is developed for an axion haloscope experiment. The magnet consists of 44 double-pancake coils wound with multi-width and multi-thickness REBa2Cu3O7-x (RE = rare earth) tapes. Owing to the NI feature, the magnet is highly compact; is 162 mm in outer diameter and 476 mm tall; and provides an environment of 0.22 T2 m3 within the cold-bore target space of 66 mm in diameter and 200 mm in length. After an initial performance test at SuNAM Co. Ltd., the magnet was installed at the Center for Axion and Precision Physics Research (CAPP) of the Institute for Basic Science in Daejeon, South Korea, in August 2017. The magnet has been successfully operating at the CAPP since then, except for maintenance in October 2018. The magnet may represent the first high field HTS user magnet that experienced long-term operation of over one year.
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Tobramycin is an aminoglycoside-based natural antibiotic derived from Streptomyces tenebrarius, which is primarily used for Gram-negative bacterial infection treatment. Although tobramycin has been utilized in clinical practice for a long time, it has exhibited several side effects, leading to the introduction of more effective antibiotics. Therefore, we conducted our experiments focusing on new possibilities for the clinical use of tobramycin. How tobramycin affects skin melanin formation is unknown. This study used B16F10 melanoma cells to assess the effect of tobramycin on melanin production. After cytotoxicity was assessed by MTT assay, melanin content and tyrosinase activity analyses revealed that tobramycin induces melanin synthesis in B16F10 cells. Next, Western blot analyses were performed to elucidate the mechanism by which tobramycin increases melanin production; phosphorylated p38 protein expression was upregulated. Protein inhibitors have been used to elucidate the mechanism of tobramycin. Kanamycin A and B are structurally similar to tobramycin, and 2-DOS represents the central structure of these antibiotics. The effects of these substances on melanogenesis were evaluated. Kanamycin A reduced melanin production, whereas kanamycin B and 2-DOS had no effect. Overall, our data indicated that tobramycin increases melanin production by promoting p38 protein phosphorylation in B16F10 melanoma cells.
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Removal of gaseous radioactive iodine (131I and 129I) compounds from nuclear facilities is an important issue. Herein we assessed the adsorptive capacity of gaseous non-radioactive methyl iodide (CH3127I) as a simulant on two commercial TEDA-metal impregnated activated carbon(AC)s. The characterizations of the ACs were determined ICP-MS, XPS, and 77 K N2 isotherms. As a result, it was found that one AC has a small amount of TEDA but a well-developed porosity, and the other one was abundant with TEDA, but the porosity was relatively less developed. The methyl iodide removal performances were evaluated under 10 ppm and 400 ppm using breakthrough experiments under various relative humidities (RH). Desorption was also carried out using nitrogen after adsorption to investigate adsorption affinity. Methyl iodide adsorption capacity of TEDA-rich AC decreased significantly as RH increased at 10 ppm. Conversely, performance degradation was clearly observed from less TEDA-impregnated AC with well-developed porosity as RH increased at 400 ppm. It is demonstrated that the amount of physisorbed methyl iodide is decreased as RH increased. Although moisture decreases the adsorption amount, it enhances the adsorption affinity. Also, additional TEDA impregnation to ACs results in improving the performance under severe condition (RH90%, 400 ppm).
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In this study, we proposed a strategy to fabricate vertically stacked subpixel (VSS) micro-light-emitting diodes (µ-LEDs) for future ultrahigh-resolution microdisplays. At first, to vertically stack the LED with different colors, we successfully adopted a bonding-interface-engineered monolithic integration method using SiO2/SiNx distributed Bragg reflectors (DBRs). It was found that an intermediate DBR structure could be used as the bonding layer and color filter, which could reflect and transmit desired wavelengths through the bonding interface. Furthermore, the optically pumped µ-LED array with a pitch of 0.4 µm corresponding to the ultrahigh-resolution of 63 500 PPI could be successfully fabricated using a typical semiconductor process, including electron-beam lithography. Compared with the pick-and-place strategy (limited by machine alignment accuracy), the proposed strategy leads to the fabrication of significantly improved high-density µ-LEDs. Finally, we systematically investigated the effects of surface traps using time-resolved photoluminescence (TRPL) and two-dimensional simulations. The obtained results clearly demonstrated that performance improvements could be possible by employing optimal passivation techniques by diminishing the pixel size for fabricating low-power and highly efficient microdisplays.
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In current nanoscale semiconductor fabrications, high dielectric materials and ultrathin multilayers have been selected to improve the performance of the devices. Thus, interface effects between films and the quantification of surface information are becoming key issues for determining the performance of the semiconductor devices. In this paper, we developed an easy, accurate, and nondestructive diagnosis to investigate the interface effect of hafnium oxide ultrathin films. A roughness scaling method that artificially modified silicon surfaces with a maximum peak-to-valley roughness range of a few nanometers was introduced to examine the effect on the underlayer roughness. The critical overlayer roughness was be defined by the transition of RMS roughness which was 0.18 nm for the 3 nm thick hafnium oxide film. Subsequently, for the inline diagnostic application of semiconductor fabrication, the roughness of a mass produced hafnium film was investigated. Finally, we confirmed that the result was below the threshold set by our critical roughness. The RMS roughness of the mass produced hafnium oxide film was 0.11 nm at a 500 nm field of view. Therefore, we expect that the quantified and standardized critical roughness managements will contribute to improvement of the production yield.
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An independent external stage for low noise atomic force microscope has been developed for mid-range movements so that it aids in measurements of critical dimensions through the low-noise atomic force microscope. The maximum travel length of the external four-axes stage is 10 mm. For image scanning of the specific target region, the sample needs to be moved through two steps: coarse positioning with the external stage and fine positioning with PI XY piezo scanner. Prior to the CD measurements, we confirmed that the position errors caused by the external stage and tip stage were negligible through the reproducibility experiments. In this study, custom-designed software stored the initial position of the probe and then moved it precisely to the sample location to be measured. Subsequently, the sidewalls of an improved vertical parallel structure were measured and the repeatability and reproducibility of the CD measurements were estimated using a CDR30-EBD tip. Finally, we confirmed that tip wear could be minimized by measuring TGX1 samples with undercut structures.
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Equilibrium and breakthrough adsorptions on activated carbon fibers (ACF) were conducted for CO2 and CH4 gas mixtures and the selective separation of CO2 was demonstrated. An electric swing adsorption process (ESA) was exploited to effect the rapid desorption of adsorbed gas at atmospheric pressure. Also, the relationship between the electrical behavior and desorption characteristics of ACF is discussed. In a single component adsorption experiment, the amount of adsorbed CO2 reached up to 40 mg/g-ACF, twice as much as that of adsorbed CH4. Therefore, the separation factor, defined as the ratio of adsorbed CO2 to adsorbed CH4, was 2.0. Multicomponent experiments showed a higher separation factor of 5.2, owing to a roll-up phenomenon. The temperature increase is not linearly proportionate to the power input, while the passage of higher electrical voltage (30 V) caused the ACF temperature to exceed 200 degrees C within 30 s. CO2 desorption at low voltage was well accomplished by heating the ACF to temperatures <60 degrees C. An ACF adsorption bed regenerated with ESA showed a constant regeneration efficiency of over 85% with a regular breakthrough curve. The ESA method increased desorption efficiency by over 20%, compared with the vacuum method.
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We present a customized high content (image-based) and high throughput screening algorithm for the quantification of Trypanosoma cruzi infection in host cells. Based solely on DNA staining and single-channel images, the algorithm precisely segments and identifies the nuclei and cytoplasm of mammalian host cells as well as the intracellular parasites infecting the cells. The algorithm outputs statistical parameters including the total number of cells, number of infected cells and the total number of parasites per image, the average number of parasites per infected cell, and the infection ratio (defined as the number of infected cells divided by the total number of cells). Accurate and precise estimation of these parameters allow for both quantification of compound activity against parasites, as well as the compound cytotoxicity, thus eliminating the need for an additional toxicity-assay, hereby reducing screening costs significantly. We validate the performance of the algorithm using two known drugs against T.cruzi: Benznidazole and Nifurtimox. Also, we have checked the performance of the cell detection with manual inspection of the images. Finally, from the titration of the two compounds, we confirm that the algorithm provides the expected half maximal effective concentration (EC50) of the anti-T. cruzi activity.