501 research outputs found

    Constraints on the Spacetime Variation of the Fine-structure Constant Using DESI Emission-line Galaxies

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    Linhua Jiang et al.The DESI CollaborationWe present strong constraints on the spacetime variation of the fine-structure constant α using the Dark Energy Spectroscopic Instrument (DESI). In this pilot work, we utilize ∼110,000 galaxies with strong and narrow [O iii] λ λ4959, 5007 emission lines to measure the relative variation Δα/α in space and time. The [O iii] doublet is arguably the best choice for this purpose owing to its wide wavelength separation between the two lines and its strong emission in many galaxies. Our galaxy sample spans a redshift range of 0 < z < 0.95, covering half of all cosmic time. We divide the sample into subsamples in 10 redshift bins (Δz = 0.1), and calculate Δα/α for the individual subsamples. The uncertainties of the measured Δα/α are roughly between 2 × 10−6 and 2 × 10−5. We find an apparent α variation with redshift at a level of Δα/α = (2-3) × 10−5. This is highly likely to be caused by systematics associated with wavelength calibration, since such small systematics can be caused by a wavelength distortion of 0.002-0.003 Å, which is beyond the accuracy that the current DESI data can achieve. We refine the wavelength calibration using sky lines for a small fraction of the galaxies, but this does not change our main results. We further probe the spatial variation of α in small redshift ranges, and do not find obvious, large-scale structures in the spatial distribution of Δα/α. As DESI is ongoing, we will include more galaxies, and by improving the wavelength calibration, we expect to obtain a better constraint that is comparable to the strongest current constraint.We acknowledge support from the National Science Foundation of China (12225301) and the National Key R&D Program of China (2022YFF0503401). This research used data obtained with the Dark Energy Spectroscopic Instrument (DESI). DESI construction and operations is managed by the Lawrence Berkeley National Laboratory. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of High-Energy Physics, under Contract No. DE-AC02-05CH11231, and by the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility under the same contract. Additional support for DESI was provided by the U.S. National Science Foundation (NSF), Division of Astronomical Sciences under Contract No. AST-0950945 to the NSF's National Optical-Infrared Astronomy Research Laboratory; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the National Council of Science and Technology of Mexico (CONACYT); the Ministry of Science and Innovation of Spain (MICINN), and by the DESI Member Institutions: www.desi.lbl.gov/collaborating-institutions. The DESI collaboration is honored to be permitted to conduct scientific research on Iolkam Du'ag (Kitt Peak), a mountain with particular significance to the Tohono O'odham Nation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the U.S. National Science Foundation, the U.S. Department of Energy, or any of the listed funding agencies.Peer reviewe

    Open-set marine object instance segmentation with prototype learning

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    The ocean world is full of Unknown Marine Objects (UMOs), making it difficult to deal with unknown ocean targets using the traditional instance segmentation model. This is because the traditional instance segmentation networks are trained on a closed dataset, assuming that all detected objects are Known Marine Objects (KMOs). Consequently, traditional closed-set networks often misclassify UMOs as KMOs. To address this problem, this paper proposes a new open-set instance segmentation model for object instance segmentation in marine environments with UMOs. Specifically, we integrate two learning modules in the model, namely a prototype module and an unknown learning module. Through the learnable prototype, the prototype module improves the class's compactness and boundary detection capabilities while also increasing the classification accuracy. Through the uncertainty of low probability samples, the unknown learning module forecasts the unknown probability. Experimental results illustrate that the proposed method has competitive known class recognition accuracy compared to existing instance segmentation models, and can accurately distinguish unknown targets

    Direct synthesis and structural characteristics of ordered SBA-15 mesoporous silica containing tungsten oxides and tungsten carbides

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    A series Of WO3-SBA-15 materials with different Si/W ratios have been hydrothermally synthesized using tetraethyl orthosilicate (TEOS) as silica precursor, ammonium paratungstate as tungsten precursor, and EO20PO70EO20 (P] 23) as structure-directing reagent. After temperature-programmed carburization (TPC) in flowing CH4/H-2 (20/80 v/v mixture), the materials were converted to the corresponding WxC-SBA- 15 materials. The structure of the oxide and carbide materials has been characterized using X-ray diffraction (XRD), X-ray fluorescence (XRF), nitrogen adsorption -desorption measurements, Si-29 magic-angle spinning (MAS) NMR spectroscopy, Fourier transform infrared (FTIR) spectroscopy, transmission electron microscopy (TEM), and thermogravimetric and differential scanning calorimetric analysis (TG-DSC) measurements. The results show that after hydrothermal synthesis using different amounts of tungsten and subsequent carburization, the materials retain the mesopore structure of SBA- 15. When Si/W = 30-15, the majority of the tungsten is dispersed in the channels of SBA-15 with the remainder being incorporated into the framework of SBA-15 with the formation of Si-O-W bonds. The tungsten carbide exists as a single W2C phase after carburization. At higher tungsten content (Si/W = 7.5), the amount of tungsten in the framework of SBA-15 increases with the formation of both Si-O-W bonds and W-O-W bonds. The tungsten carbide formed after carburization exists as a mixture Of W2C and WC phases. A model for the distribution of tungsten in SBA-15 is proposed involving three different tungsten species: alpha-W inside SBA-15 channels, beta-W embedded in the internal surfaces of the SBA- 15 channels, and gamma-W inside the framework of SBA- 15. After temperature-programmed carburization, alpha-W sites are transformed into W2C, whereas beta-W sites afford WC; in contrast, gamma-W sites show little change after carburization.A series Of WO3-SBA-15 materials with different Si/W ratios have been hydrothermally synthesized using tetraethyl orthosilicate (TEOS) as silica precursor, ammonium paratungstate as tungsten precursor, and EO20PO70EO20 (P] 23) as structure-directing reagent. After temperature-programmed carburization (TPC) in flowing CH4/H-2 (20/80 v/v mixture), the materials were converted to the corresponding WxC-SBA- 15 materials. The structure of the oxide and carbide materials has been characterized using X-ray diffraction (XRD), X-ray fluorescence (XRF), nitrogen adsorption -desorption measurements, Si-29 magic-angle spinning (MAS) NMR spectroscopy, Fourier transform infrared (FTIR) spectroscopy, transmission electron microscopy (TEM), and thermogravimetric and differential scanning calorimetric analysis (TG-DSC) measurements. The results show that after hydrothermal synthesis using different amounts of tungsten and subsequent carburization, the materials retain the mesopore structure of SBA- 15. When Si/W = 30-15, the majority of the tungsten is dispersed in the channels of SBA-15 with the remainder being incorporated into the framework of SBA-15 with the formation of Si-O-W bonds. The tungsten carbide exists as a single W2C phase after carburization. At higher tungsten content (Si/W = 7.5), the amount of tungsten in the framework of SBA-15 increases with the formation of both Si-O-W bonds and W-O-W bonds. The tungsten carbide formed after carburization exists as a mixture Of W2C and WC phases. A model for the distribution of tungsten in SBA-15 is proposed involving three different tungsten species: alpha-W inside SBA-15 channels, beta-W embedded in the internal surfaces of the SBA- 15 channels, and gamma-W inside the framework of SBA- 15. After temperature-programmed carburization, alpha-W sites are transformed into W2C, whereas beta-W sites afford WC; in contrast, gamma-W sites show little change after carburization

    High Performance Dye-Sensitized Solar Cells with Enhanced Light-Harvesting Efficiency Based on Polyvinylpyrrolidone-Coated Au-TiO2 Microspheres

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    Surface plasmon resonance using noble metal nanoparticles is regarded as an attractive and viable strategy to improve the optical absorption and/or photocurrent in dye-sensitized solar cells (DSSCs). However, no significant improvement in device performance has been observed. The bottleneck is the stability of the noble-metal nanoparticles caused by chemical corrosion. Here, we propose a simple method to synthesize high-performance DSSCs based on polyvinylpyrrolidone-coated Au-TiO2 microspheres that utilize the merits of TiO2 microspheres and promote the coupling of surface plasmons with visible light. When 0.4wt% Au nanoparticles were embedded into the TiO2 microspheres, the device achieved a power conversion efficiency (PCE) as high as 10.49%, a 7.9% increase compared with pure TiO2 microsphere-based devices. Simulation results theoretically confirmed that the improvement of the PCE is caused by the enhancement of the absorption cross-section of dye molecules and photocurrent

    Synergistic effect of TiO2 hierarchical submicrospheres for high performance dye-sensitized solar cells

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    The performance of dye-sensitized solar cells (DSCs) could be improved by using rationally designed mesoporous film structure for electron collection, dye adsorption and light scattering. The development of a novel double layer film prepared by TiO2 hierarchical submicrospheres and nanoparticles was reported in this article. The submicrospheres were composed of rutile nanorods of 10 nm diameter and the length of 150-250 nm, which facilitated fast electron transport, charge collection and light scattering. Using a double layer structure consisting of the 10 wt% film as a dye loading layer and the 50 wt% film as the light scattering layer, C101 sensitizer and liquid electrolyte, DSC yielded power conversion efficiency of 9.68% under 1 sun illumination

    Influence of Hydrostatic Pressure and Cationic Type on the Diffusion Behavior of Chloride in Concrete

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    The durability of the concrete in underground and marine engineering is affected by the underground and ocean environment. Chloride diffusion coefficient under hydrostatic pressure is a key parameter of concrete durability design under corresponding conditions. Therefore, this paper studies the diffusion behavior of chloride in different diffusion source solutions by experiment and simulation. Based on the experimental results, this paper proposes a new chloride diffusion model under the coupling effect of diffusion and convection. The interaction of ions and compounds in the diffusion source solutions, concrete pore fluid, and concrete material are considered in the new chloride diffusion model. The experimental results show that chloride diffusion rate is significantly affected by hydrostatic pressure, which increases with the increase of hydrostatic pressure. The chloride diffusion coefficient shows a certain difference in difference diffusion source solutions. The chloride diffusion coefficient in divalent cationic diffusion source solutions is the largest, the chloride diffusion coefficient in the divalent and monovalent cationic compound ones is in the middle, and the chloride diffusion coefficient in the monovalent cationic ones is the smallest. There is a linear relationship between the chloride diffusion coefficient and the hydrostatic pressure whether in single or combined cationic diffusion source solutions
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