scholarly journals Crystal Chemistry of High-Temperature Borates

Molecules ◽  
2020 ◽  
Vol 25 (10) ◽  
pp. 2450 ◽  
Author(s):  
Nikolay I. Leonyuk ◽  
Victor V. Maltsev ◽  
Elena A. Volkova
Keyword(s):  
High Temperature ◽  
Crystal Chemistry ◽  
Structural Type ◽  
Practical Applications ◽  
Synthesis Conditions ◽  
Metal Atoms ◽  
Cation Type ◽  
Substantial Interest ◽  
Cation Charge

In recent years borate-based crystals has attracted substantial interest among the research community. The overall importance of this family of materials is reflected in miscellaneous articles and several reviews that have been published over the years. Crystalline borate materials exhibit numerous interesting physical properties, which make them promising for further practical applications. Diversity of functional characteristics results from their high structural flexibility caused in the linkage of planar/non–planar BO3 groups and BO4 tetrahedra, which can occur as isolated or condensed structural units. This report is a brief review on crystal chemistry and structure features of anhydrous/high-temperature borates. Polymorphism of boron-oxygen radicals has been considered basing on cations’ nature and synthesis conditions. Analysis of the laws governing borates structures and general principles of their systematics was discussed. As a result, an alternative classification of anhydrous compounds has been considered. It is based on four orders of their subdivision: (1) by the variety of anion formers, (2) by the cation charge, (3) by the N = NM:NB, i.e., ratio of metal atoms number to the ratio of boron atoms number (N-factor) value indicating the borate structural type (if it is known), (4) by the cation type and size.

Colorimetric Optical Thermometry of Host-Sensitized Pr3+-Doped Niobate Phosphors based on Electronic-Rich-Site Strategy

2021 ◽  
Author(s):  
Yao Wang ◽  
Ning Guo ◽  
Yanmei Xin ◽  
Jing Li ◽  
Ruizhuo Ouyang ◽  
...  
Keyword(s):  
High Temperature ◽  
Charge Migration ◽  
Temperature Synthesis ◽  
Synthesis Conditions ◽  
Reducing Atmosphere ◽  
High Temperature Synthesis ◽  
Optical Thermometry

Most praseodymium-doped red-emitting phosphors need high-temperature synthesis conditions with reducing atmosphere. The niobate matrix selected in this paper provides sufficient electron-rich-site environment for praseodymium through charge migration, and praseodymium can...

Effect of bismuth substitution on crystal chemistry, photocatalysis and conductivity in Sr3V2O8: a new structural type in palmierite class

RSC Advances ◽  
2012 ◽  
Vol 2 (28) ◽  
pp. 10505 ◽  
Author(s):  
Dipankar Saha ◽  
Prangya Parimita Sahoo ◽  
Giridhar Madras ◽  
Tayur N. Guru Row
Keyword(s):  
Crystal Chemistry ◽  
Structural Type

Progress of Research on Welding for Molybdenum Alloys

2014 ◽  
Vol 33 (3) ◽  
pp. 193-200 ◽  
Author(s):  
Jiteng Wang ◽  
Juan Wang ◽  
Yajiang Li ◽  
Deshuang Zheng
Keyword(s):  
High Temperature ◽  
Elevated Temperature ◽  
Low Temperature ◽  
Welded Joint ◽  
Structural Materials ◽  
Practical Applications ◽  
Traditional Technology ◽  
Molybdenum Alloys ◽  
Resistance To Oxidation ◽  
Temperature Applications

AbstractMolybdenum and molybdenum alloys are considered to be attractive structural materials for high-temperature applications. However, molybdenum alloys are sensitive to gas impurities and have the characteristics of low temperature embrittlement and less resistance to oxidation at elevated temperature. The toughness and strength of welded joint is not easy to be ensured by traditional technology. Recently, many efforts have been made to join molybdenum and its alloys. In this paper, we present the result of investigations on welding methods of molybdenum and its alloys and overview the practical applications in engineering. The key of joining molybdenum alloys is to improve the toughness of welded joint and prevent the generation of pores and cracks.

Classification of High-Temperature PEM Fuel Cell Degradation Mechanisms Using Equivalent Circuits

2015 ◽  
Vol 62 (8) ◽  
pp. 5265-5274 ◽  
Author(s):  
Chris de Beer ◽  
Paul S. Barendse ◽  
Pragasen Pillay ◽  
Brian Bullecks ◽  
Raghunathan Rengaswamy
Keyword(s):  
High Temperature ◽  
Fuel Cell ◽  
Pem Fuel Cell ◽  
Equivalent Circuits ◽  
Degradation Mechanisms ◽  
High Temperature Pem

scholarly journals Application of self organizing map in construction, geology and petroleum industry

2017 ◽  
Vol 20 (K4) ◽  
pp. 30-38
Author(s):  
Tung Son Pham ◽  
Huy Minh Truong ◽  
Tuan Ba Pham
Keyword(s):  
Industrial Revolution ◽  
Human Life ◽  
Petroleum Industry ◽  
Self Organizing Map ◽  
Practical Applications ◽  
Fourth Industrial Revolution ◽  
Som Algorithm ◽  
Clustering Data ◽  
Self Organizing

In recent years, Artificial Intelligence (AI) has become an emerging subject and been recognized as the flagship of the Fourth Industrial Revolution. AI is subtly growing and becoming vital in our daily life. Particularly, Self-Organizing Map (SOM), one of the major branches of AI, is a useful tool for clustering data and has been applied successfully and widespread in various aspects of human life such as psychology, economic, medical and technical fields like mechanical, construction and geology. In this paper, the primary purpose of the authors is to introduce SOM algorithm and its practical applications in geology and construction. The results are classification of rock facies versus depth in geology and clustering two sets of construction prices indices and building material costs indice.

scholarly journals Fast Drivable Areas Estimation with Multi-Task Learning for Real-Time Autonomous Driving Assistant

2021 ◽  
Vol 11 (22) ◽  
pp. 10713
Author(s):  
Dong-Gyu Lee
Keyword(s):  
Real Time ◽  
Computational Efficiency ◽  
Autonomous Driving ◽  
Learning Approaches ◽  
Practical Applications ◽  
Task Learning ◽  
Lane Line ◽  
High Level ◽  
Time Autonomous

Autonomous driving is a safety-critical application that requires a high-level understanding of computer vision with real-time inference. In this study, we focus on the computational efficiency of an important factor by improving the running time and performing multiple tasks simultaneously for practical applications. We propose a fast and accurate multi-task learning-based architecture for joint segmentation of drivable area, lane line, and classification of the scene. An encoder-decoder architecture efficiently handles input frames through shared representation. A comprehensive understanding of the driving environment is improved by generalization and regularization from different tasks. The proposed method learns end-to-end through multi-task learning on a very challenging Berkeley Deep Drive dataset and shows its robustness for three tasks in autonomous driving. Experimental results show that the proposed method outperforms other multi-task learning approaches in both speed and accuracy. The computational efficiency of the method was over 93.81 fps at inference, enabling execution in real-time.

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