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19 pages, 6812 KB

Open AccessArticle

Evolution of the Radiation Shielding, Optical, and Luminescence Properties of PbO₂-SiO₂ Glass Systems and the Influence of Rare Earth Elements (Eu, Ce, Yb)

by Mioara Zagrai, Ramona-Crina Suciu, Radu Cristian Gavrea and Vasile Rednic

Appl. Sci. 2025, 15(2), 864; https://doi.org/10.3390/app15020864 - 16 Jan 2025

Cited by 3 | Viewed by 2054

Abstract

This study explores the physical, radiation shielding, optical, and photoluminescent properties of PbO₂-SiO₂-based glass systems. Traditional radiation shielding materials, like lead and concrete, face challenges due to toxicity and weight. Glass materials provide an alternative, offering transparency and efficiency. Four glass systems were analyzed: PbO₂-SiO₂ (PS), PbO₂-SiO₂-CeO₂ (PSC), PbO₂-SiO₂-Eu₂O₃ (PSE), and PbO₂-SiO₂-Yb₂O₃ (PSY). The results show that rare earth elements densify the glass network, thereby enhancing radiation attenuation properties, quantified through parameters like the linear attenuation coefficient (μ), the half-value layer (HVL), and the mean free path (MFP). The PSY system exhibited the best shielding properties, demonstrating its potential for use in gamma ray shielding. Samples PS0–PS3 revealed semiconducting behavior and may be considered a promising host matrix for solar cells and w-LED applications. Full article

(This article belongs to the Special Issue Advanced Research on Structure, Properties, and Applications of Glass Materials)

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15 pages, 4784 KB

Open AccessArticle

Effect of Interface Defects on the Electric–Thermal–Stress Coupling Field Distribution of Cable Accessory Insulation

by Xu Lu, Ran Hu, Kongying Guo, Rui Lan, Jie Tian, Yanhui Wei and Guochang Li

Energies 2024, 17(17), 4498; https://doi.org/10.3390/en17174498 - 8 Sep 2024

Cited by 5 | Viewed by 2148

Abstract

The combined insulation interface of a high-voltage cable and accessories is the weakest part of a cable system. In this paper, the parameters of the dielectric constant, thermal conductivity, and elastic modulus of cross-linked polyethylene (XLPE) and silicone rubber (SIR) are obtained experimentally. On this basis, the model of a specific type of 110 kV cable and prefabricated insulation joint is established. A simulation of the electric–thermal–stress coupling field in the presence of typical defects in the main insulation–inner semi-conductive (SEMI) shielding layer (XLPE/SEMI interface) and the main insulation–silicone rubber insulation layer (XLPE/SIR interface) is studied. The simulation results show that at the XLPE/SIR interface, the electric field distortion caused by bubble defects reached 20.17 kV/mm, and the temperature rose to 56.15 °C. The effect of air-gap defects on the interface is similar to that of bubble defects. In addition, the semi-conductive impurity defects induced an increase in temperature to 56.82 °C and an increase in stress to 0.32 MPa. At the XLPE/SEMI interface, the electric field distortion induced by bubble defects was 19.98 kV/mm, and the temperature rose to 61.72 °C. The electric field distortion caused by metallic and semi-conductive defects was 8.44 kV/mm and 8.64 kV/mm, respectively. This study serves as a reference for the fault analysis and the operation and maintenance of cable accessories. Full article

(This article belongs to the Topic Condition Monitoring and Diagnostic Methods for Power Equipment in New Energy Power Systems)

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10 pages, 19843 KB

Open AccessArticle

Role of Materials Chemistry on Transparent Conductivity of Amorphous Nb-Doped SnO₂ Thin Films Prepared by Remote Plasma Deposition

by Angang Song, Yiwen Wang, Suxiang Liu, Qinpu Wang and Junhua Hu

Coatings 2022, 12(8), 1111; https://doi.org/10.3390/coatings12081111 - 4 Aug 2022

Cited by 9 | Viewed by 2855

Abstract

In this study, remote plasma sputtering deposition of niobium-doped SnO₂ transparent conductive oxides on glass substrates was carried out at ambient temperature with no post-deposition annealing. The microstructure, optical, electrical, and surface morphology of the thin films were characterized using a combination of advanced techniques, such as X-ray diffraction (XRD), UV-Vis spectrophotometer, Hall-effect measurements, as well as field emission scanning electron microscope (FESEM), high-resolution transmission electron microscopy, and high-resolution X-ray photoelectron spectroscopy. It was determined that the oxygen defects of the films have a substantial impact on their transparent conductivity. The crystalline films, which were crystallized by annealing at 450 °C, had higher resistivities due to a decreased concentration of oxygen vacancies, which restricted conduction. In comparison, the amorphous films exhibited remarkable conductivity. The best amorphous films (Nb:SnO₂) exhibited a resistivity of less than 4.6 × 10⁻³ Ω·cm, with a 3 × 10²⁰ cm⁻³ carrier concentration and a 4.4 cm²/(V·S) of Hall mobility. X-ray amorphous Nb:SnO₂ films can be used to make conductive and transparent protective layers that can be used to shield semiconducting photoelectrodes used in solar water splitting. These layers can also be used with more conductive TCO films (ITO or AZO) when needed. Full article

(This article belongs to the Special Issue Optical Thin Film and Photovoltaic (PV) Related Technologies)

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14 pages, 2213 KB

Open AccessArticle

Segmenting the Semi-Conductive Shielding Layer of Cable Slice Images Using the Convolutional Neural Network

by Wen Zhu, Fei Dong, Beiping Hou, Wesley Kenniard Takudzwa Gwatidzo, Le Zhou and Gang Li

Polymers 2020, 12(9), 2085; https://doi.org/10.3390/polym12092085 - 14 Sep 2020

Cited by 5 | Viewed by 2908

Abstract

Being an important part of aerial insulated cable, the semiconductive shielding layer is made of a typical polymer material and can improve the cable transmission effects; the structural parameters will affect the cable quality directly. Then, the image processing of the semiconductive layer plays an essential role in the structural parameter measurements. However, the semiconductive layer images are often disturbed by the cutting marks, which affect the measurements seriously. In this paper, a novel method based on the convolutional neural network is proposed for image segmentation. In our proposed strategy, a deep fully convolutional network with a skip connection algorithm is defined as the main framework. The inception structure and residual connection are employed to fuse features extracted from the receptive fields with different sizes. Finally, an improved weighted loss function and refined algorithm are utilized for pixel classification. Experimental results show that our proposed algorithm achieves better performance than the current algorithms. Full article

(This article belongs to the Special Issue Advanced Measurement, Prediction, and Testing Techniques in Polymer Manufacturing, Processing, and End-Use)

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