• Journal of Hydrogen and New Energy
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• v.35 no.2
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• pp.185-194
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• 2024

Fe-Ni nanocatalysts loaded on carbon black were prepared via spontaneous reduction reaction of iron (II) acetylacetonate and nickel (II) acetylacetonate in dry process. Their morphology and elemental analysis were characterized by scanning electron microscopy, transmission electron microscopy (TEM), and energy dispersive X-ray analyzer. The loading weight of the nanocatalysts was measured by thermogravimetric analyze and the surface area was measured by BET analysis. TEM observation showed that Fe and Ni nanoparticles was well dispersed on the carbon black and their average particle size was 4.82 nm. The loading weight of Fe-Ni nanocatalysts on the carbon black was 6.83-7.32 wt%, and the value increased with increasing iron (II) acetylacetonate content. As the Fe-Ni loading weight increased, the specific surface area decreased significantly by more than 50%, because Fe-Ni nanoparticles block the micropores of carbon black. I-V characteristics showed that water electrolysis performance increased with increasing Ni nanocatalyst content.

• Structural Engineering and Mechanics
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• v.90 no.4
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• pp.417-428
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• 2024

Nanocomposite-reinforced concrete systems have gained increasing attention in bridge construction due to their enhanced mechanical properties and durability. Understanding the transient dynamics of these advanced materials is crucial for ensuring the structural integrity and performance of bridge infrastructure under dynamic loading conditions. This paper presents a comprehensive study of the measurement techniques employed for assessing the transient dynamics of nanocompositereinforced concrete systems in bridge construction applications. A numerical method, including modal analysis are discussed in detail, highlighting their advantages, limitations, and applications. Additionally, recent advancements in sensor technologies, data acquisition systems, and signal processing techniques for capturing and analyzing transient responses are explored. The paper also addresses challenges and opportunities in the measurement of transient dynamics, such as the characterization of nanocomposite-reinforced concrete materials, the development of accurate numerical models, and the integration of advanced sensing technologies into bridge monitoring systems. Through a critical review of existing literature and case studies, this paper aims to provide insights into best practices and future directions for the measurement of transient dynamics in nanocompositereinforced concrete systems, ultimately contributing to the design, construction, and maintenance of resilient and sustainable bridge infrastructure.

• Geomechanics and Engineering
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• v.37 no.6
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• pp.539-554
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• 2024

This study explores development of prediction model for seismic site classification through the integration of machine learning techniques with horizontal-to-vertical spectral ratio (HVSR) methodologies. To improve model accuracy, the research employs outlier detection methods and, synthetic minority over-sampling technique (SMOTE) for data balance, and evaluates using seven machine learning models using seismic data from KiK-net. Notably, light gradient boosting method (LGBM), gradient boosting, and decision tree models exhibit improved performance when coupled with SMOTE, while Multiple linear regression (MLR) and Support vector machine (SVM) models show reduced efficacy. Outlier detection techniques significantly enhance accuracy, particularly for LGBM, gradient boosting, and voting boosting. The ensemble of LGBM with the isolation forest and SMOTE achieves the highest accuracy of 0.91, with LGBM and local outlier factor yielding the highest F1-score of 0.79. Consistently outperforming other models, LGBM proves most efficient for seismic site classification when supported by appropriate preprocessing procedures. These findings show the significance of outlier detection and data balancing for precise seismic soil classification prediction, offering insights and highlighting the potential of machine learning in optimizing site classification accuracy.

• Clinical Endoscopy
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• v.57 no.3
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• pp.302-308
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• 2024

With incessant advances in information technology and its implications in all domains of our lives, artificial intelligence (AI) has emerged as a requirement for improved machine performance. This brings forth the query of how this can benefit endoscopists and improve both diagnostic and therapeutic endoscopy in each part of the gastrointestinal tract. Additionally, it also raises the question of the recent benefits and clinical usefulness of this new technology in daily endoscopic practice. There are two main categories of AI systems: computer-assisted detection (CADe) for lesion detection and computer-assisted diagnosis (CADx) for optical biopsy and lesion characterization. Quality assurance is the next step in the complete monitoring of high-quality colonoscopies. In all cases, computer-aided endoscopy is used, as the overall results rely on the physician. Video capsule endoscopy is a unique example in which a computer operates a device, stores multiple images, and performs an accurate diagnosis. While there are many expectations, we need to standardize and assess various software packages. It is important for healthcare providers to support this new development and make its use an obligation in daily clinical practice. In summary, AI represents a breakthrough in digestive endoscopy. Screening for gastric and colonic cancer detection should be improved, particularly outside expert centers. Prospective and multicenter trials are mandatory before introducing new software into clinical practice.

• Archives of Metallurgy and Materials
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• v.64 no.3
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• pp.953-957
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• 2019

U-10wt.%Zr metallic fuel slugs containing rare-earth (RE: a rare-earth alloy comprising 53% Nd, 25% Ce, 16% Pr and 6% La) elements for a sodium-cooled fast reactor were fabricated by modified injection casting as an alternative method. The distribution, size and composition of the RE inclusions in the metallic fuel slugs were investigated according to the content of the RE inclusions. There were no observed casting defects, such as shrunk pipes, micro-shrinkage or hot tears formed during solidification, in the metallic fuel slugs fabricated by modified injection casting. Scanning electron micrographs and energy-dispersive X-ray spectroscopy (SEM-EDS) showed that the Zr and RE inclusions were uniformly distributed in the matrix and the composition of the RE inclusions was similar to that of a charged RE element. The content and the size of the RE inclusions increased slightly according to the charge content of the RE elements. RE inclusions in U-Zr alloys will have a positive effect on fuel performance due to their micro-size and high degree of distribution.

• Applied Microscopy
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• v.50
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• pp.17.1-17.9
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• 2020

Recent advances in fabrication have enabled radial-junction architectures for cost-effective and high-performance optoelectronic devices. Unlike a planar PN junction, a radial-junction geometry maximizes the optical interaction in the three-dimensional (3D) structures, while effectively extracting the generated carriers via the conformal PN junction. In this paper, we report characterizations of radial PN junctions that consist of p-type Si micropillars created by deep reactive-ion etching (DRIE) and an n-type layer formed by phosphorus gas diffusion. We use electron-beam induced current (EBIC) microscopy to access the 3D junction profile from the sidewall of the pillars. Our EBIC images reveal uniform PN junctions conformally constructed on the 3D pillar array. Based on Monte-Carlo simulations and EBIC modeling, we estimate local carrier separation/collection efficiency that reflects the quality of the PN junction. We find the EBIC efficiency of the pillar array increases with the incident electron beam energy, consistent with the EBIC behaviors observed in a high-quality planar PN junction. The magnitude of the EBIC efficiency of our pillar array is about 70% at 10 kV, slightly lower than that of the planar device (≈ 81%). We suggest that this reduction could be attributed to the unpassivated pillar surface and the unintended recombination centers in the pillar cores introduced during the DRIE processes. Our results support that the depth-dependent EBIC approach is ideally suitable for evaluating PN junctions formed on micro/nanostructured semiconductors with various geometry.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.3076-3083
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• 2024

In this work, single photon avalanche diodes (SPADs) were fabricated using the standard 180 nm complementary metal-oxide semiconductor process. Their small size of 15-16 µ m and low operating voltage made it possible to easily integrate them with readout circuits for compact on-chip sensors, particularly those used in the radiation sensor network of a nuclear plant. Four architectures were proposed for the SPADs, with a shallow trench isolation (STI) guard ring and different depletion regions designed to demonstrate the main performance parameters in each experimental configuration. The wide absorption region structure with PSD and a deep N-well could achieve a uniform electric field, resulting in a stable dark count rate (DCR). Additionally, the STI guard ring was implanted to mitigate the premature edge breakdown. A breakdown voltage was achieved for a low operating voltage of 10.75 V. The DCR results showed 286.3 Hz per ㎛² at an excess voltage of 0.04 V. A photon detection probability of 21.48% was obtained at 405 nm.

• Nanomaterials
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• v.11 no.3
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• pp.767-780
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• 2021

Tin sulfide polymorph (π-SnS) nanoparticles exhibit promising optoelectrical characteristics for photovoltaic and hydrogen production performance, mainly because of the possibility of tuning their properties by adjusting the synthesis conditions. This study demonstrates a chemical approach to synthesize π-SnS nanoparticles and the engineering of their properties by altering the Sn precursor concentration (from 0.04 M to 0.20 M). X-ray diffraction and Raman studies confirmed the presence of pure cubic SnS phase nanoparticles with good crystallinity. SEM images indicated the group of cloudy shaped grains, and XPS results confirmed the presence of Sn and S in the synthesized nanoparticles. Optical studies revealed that the estimated energy bandgap values of the as-synthesized π-SnS nanoparticles varied from 1.52 to 1.68 eV. This work highlights the effects of the Sn precursor concentration on the properties of the π-SnS nanoparticles and describes the bandgap engineering process. Optimized π-SnS nanoparticles were used to deposit nanocrystalline π-SnS thin films using the drop-casting technique, and their physical properties were improved by annealing (300 ℃ for 2 h).

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.9
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• pp.1237-1247
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• 2012

The objective of this study was to evaluate the predictions of dry matter intake (DMI) and average daily gain (ADG) of Vietnamese Yellow (Vang) purebred and crossbred (Vang with Red Sindhi or Brahman) bulls fed under Vietnamese conditions using two levels of solution (1 and 2) of the large ruminant nutrition system (LRNS) model. Animal information and feed chemical characterization were obtained from five studies. The initial mean body weight (BW) of the animals was 186, with standard deviation ${\pm}33.2$ kg. Animals were fed ad libitum commonly available feedstuffs, including cassava powder, corn grain, Napier grass, rice straw and bran, and minerals and vitamins, for 50 to 80 d. Adequacy of the predictions was assessed with the Model Evaluation System using the root of mean square error of prediction (RMSEP), accuracy (Cb), coefficient of determination ($r^2$), and mean bias (MB). When all treatment means were used, both levels of solution predicted DMI similarly with low precision ($r^2$ of 0.389 and 0.45 for level 1 and 2, respectively) and medium accuracy (Cb of 0.827 and 0.859, respectively). The LRNS clearly over-predicted the intake of one study. When this study was removed from the comparison, the precision and accuracy considerably increased for the level 1 solution. Metabolisable protein was limiting ADG for more than 68% of the treatment averages. Both levels differed regarding precision and accuracy. While level 1 solution had the least MB compared with level 2 (0.058 and 0.159 kg/d, respectively), the precision was greater for level 2 than level 1 (0.89 and 0.70, respectively). The accuracy (Cb) was similar between level 1 and level 2 (p = 0.8997; 0.977 and 0.871, respectively). The RMSEP indicated that both levels were on average under-or over-predicted by about 190 g/d, suggesting that even though the accuracy (Cb) was greater for level 1 compared to level 2, both levels are likely to wrongly predict ADG by the same amount. Our analyses indicated that the level 1 solution can predict DMI reasonably well for this type of animal, but it was not entirely clear if animals consumed at their voluntary intake and/or if the roughness of the diet decreased DMI. A deficit of ruminally-undegradable protein and/or a lack of microbial protein may have limited the performance of these animals. Based on these evaluations, the LRNS level 1 solution may be an alternative to predict animal performance when, under specific circumstances, the fractional degradation rates of the carbohydrate and protein fractions are not known.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.2
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• pp.211-220
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• 2017

Objective: The aim of the present study was to investigate the effect of yeast with bacteriocin and Lactobacillus cultures (mixture of Lactobacillus agilis BCRC 10436 and Lactobacillus reuteri BCRC 17476) supplements, alone or in combination, on broiler chicken performance. Methods: A total of 300, 1-d-old healthy broiler chickens were randomly divided into five treatment groups: i) basal diet (control), ii) basal diet+0.25% yeast (Saccharomyces cerevisiae) (YC), iii) basal diet+0.25% yeast with bacteriocin (BA), iv) basal diet+Lactobacillus cultures (LAB), and v) basal diet +0.25% yeast with bacteriocin+Lactobacillus cultures (BA+LAB). Growth performance, cecal microbiota, cecal fermentation products, and blood biochemistry parameters were determined when chickens were 21 and 35 d old. Results: The supplementation of YC, BA, and BA+LAB resulted in a significantly better feed conversion rate (FCR) than that of the control group during 1 to 21 d (p<0.05). The LAB supplementation had a significant effect on the presence of Lactobacillus in the ceca at 35 d. None of the supplements had an effect on relative numbers of L. agilis and L. reuter at 21 d, but the BA supplementation resulted in the decrease of both Lactobacillus strains at 35 d. The BA+LAB supplementation resulted in higher short chain fatty acid (SCFA) in the ceca, but LAB supplementation significantly decreased the SCFA at 35 d (p<0.05). All treatments tended to decrease ammonia concentration in the ceca at 21 d, especially in the LAB treatment group. The BA supplementation alone decreased the triacylglycerol (TG) concentration significantly at 21 d (p<0.05), but the synergistic effect of BA and LAB supplementation was required to reduce the TG concentration at 35 d. The YC supplementation tended to increase the plasma cholesterol at 21 d and 35 d. However, the BA supplementation significantly decreased the cholesterol and low density lipoprotein cholesterol level at 35 d. In conclusion, the BA+LAB supplementation was beneficial to body weight gain and FCR of broiler chickens. Conclusion: The effect of BA and LAB supplementation may be a result of the growth of lactic acid bacteria enhancement and physiological characterization of bacteriocin, and it suggests that the BA and LAB supplementation level or Lactobacillus strain selection should be integrated in future supplementation designs.