We have studied the phase and structure evolution of the Ti33Cu67 amorphous alloy subjected to electrical pulses of high current density. By varying the pulse parameters, different stages of crystallization could be observed in the samples. Partial polymorphic nanocrystallization resulting in the formation of 5- to 8-nm crystallites of the TiCu2 intermetallic in the residual amorphous matrix occurred when the maximum current density reached 9.7·108 A m-2 and the pulse duration was 140 μs, though the calculated temperature increase due to Joule heating was not enough to reach the crystallization temperature of the alloy. Samples subjected to higher current densities and higher values of the evolved Joule heat per unit mass fully crystallized and contained the Ti2Cu3 and TiCu3 phases. A common feature of the crystallized ribbons was their non-uniform microstructure with regions that experienced local melting and rapid solidification.PACS: 81; 81.05.Bx; 81.05.Kf.
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http://dx.doi.org/10.1186/1556-276X-6-512 | DOI Listing |
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Electrophysiology Laboratory and Arrhythmia Unit, Centro Integral de Enfermedades Cardiovasculares, Hospital Monteprincipe, Grupo HM Hospitales, Madrid, Spain. Electronic address:
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January 2025
Bakken Research Center, Maastricht, The Netherlands. Electronic address:
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Sensors (Basel)
December 2024
College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
The design and study of pulsed eddy current sensors for detecting surface defects in small-diameter rods are highly significant. Accurate detection and identification of surface defects in small-diameter rods may be attained by the ongoing optimization of sensor design and enhancement of detection technologies. This article presents the construction of a non-coaxial differential eddy current sensor (Tx-Rx sensor) and examines the detection of surface defects in a small diameter bar.
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December 2024
College of Electrical Engineering, Sichuan University, Chengdu 610065, China.
Remote photo-plethysmography (rPPG) is a useful camera-based health motioning method that can measure the heart rhythm from facial videos. Many well-established deep learning models can provide highly accurate and robust results in measuring heart rate (HR) and heart rate variability (HRV). However, these methods are unable to effectively eliminate illumination variation and motion artifact disturbances, and their substantial computational resource requirements significantly limit their applicability in real-world scenarios.
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December 2024
Hangzhou Institute of Technology, Xidian University, Hangzhou 311200, China.
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