phase relations
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JOM ◽  
2022 ◽  
Author(s):  
Junjie Shi ◽  
Yuchao Qiu ◽  
Xingbang Wan ◽  
Bin Yu ◽  
Min Chen ◽  
...  

Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 593
Author(s):  
Chenbo Li ◽  
Qian Song ◽  
Xianwen Yang ◽  
Yuduo Wei ◽  
Qi Hu ◽  
...  

The phase relations of the Fe-Zr-Y system at 973 K and 1073 K were experimentally investigated by using the equilibrated alloys. New ternary compounds τ3-Fe3ZrY and τ4-Fe10Zr5Y2 were found in this ternary system. The solubility of Y in Fe2Zr was measured to be 3.5 at.% and the third component can hardly dissolve in the other binary intermetallic phases. Experiments have verified that Fe2.9Zr0.5Y0.5 has a solid solubility ranging from Fe73Zr12Y14 to Fe77Zr9Y13.


2021 ◽  
Author(s):  
Melisa Menceloglu ◽  
Marcia Grabowecky ◽  
Satoru Suzuki

Prior research has identified a variety of task-dependent networks that form through inter-regional phase-locking of oscillatory activity as neural correlates of specific behaviors. Despite ample knowledge of task-specific functional networks, general rules governing global phase relations have not been investigated. In order to discover such general rules, we focused on phase modularity, measured as the degree to which global phase relations in EEG comprised distinct synchronized clusters interacting with one another at large phase lags. Synchronized clusters were detected with a standard community-detection algorithm, and the level of phase modularity was quantified by the index q. Our findings suggest that phase modularity is functionally consequential since (1) temporal distribution of q was invariant across a broad range of frequencies (3-50 Hz examined) and behavioral conditions (resting with the eyes closed or watching a silent nature video), and (2) neural interactions (measured as power correlations) in beta-to-gamma bands consistently increased in high-modularity states. Notably, we found that the mechanism controlling phase modularity is remarkably simple. A network comprising anterior-posterior long-distance connectivity coherently shifted phase relations from low-angles (|Δθ| < π/4) in low-modularity states (bottom 5% in q) to high-angles (|Δθ| > 3π/4) in high-modularity states (top 5% in q), accounting for fluctuations in phase modularity. This anterior-posterior network likely plays a fundamental functional role as it controls phase modularity across a broad range of frequencies and behavioral conditions. These results may motivate future investigations into the functional roles of phase modularity as well as the anterior-posterior network that controls it.


2021 ◽  
pp. 1-13
Author(s):  
Alexey N. Kruk ◽  
Alexander A. Korablin ◽  
Alexander G. Sokol ◽  
Yury N. Palyanov
Keyword(s):  

Author(s):  
H. Piet ◽  
K. Leinenweber ◽  
E. Greenberg ◽  
V. B. Prakapenka ◽  
S.‐H. Shim
Keyword(s):  

2021 ◽  
Vol 9 (4) ◽  
pp. 105-110
Author(s):  
Dragoslav R Rakic ◽  
Irena G Basaric Ikodinovic ◽  
Jovana M Jankovic ◽  
Tina D Djuric

JOM ◽  
2021 ◽  
Author(s):  
Min Chen ◽  
Xingbang Wan ◽  
Junjie Shi ◽  
Pekka Taskinen ◽  
Ari Jokilaakso

AbstractWe investigated the phase relations of the SiO2-MgO-TiO2 system in air at 1500°C using the high-temperature isothermal equilibration/quenching technique, followed by x-ray diffraction measurements and direct phase analysis using scanning electron microscopy coupled with x-ray energy dispersive spectrometry. One single liquid phase domain, five two-phase domains (liquid-TiO2, liquid-cristobalite, liquid-MgO·SiO2, liquid-2MgO·SiO2, and liquid-MgO·2TiO2), and five three-phase regions (liquid-TiO2-MgO·2TiO2, liquid-MgO·SiO2-cristobalite, liquid-TiO2-cristobalite, liquid-MgO·SiO2-2MgO·SiO2 and liquid-2MgO·SiO2-MgO·2TiO2) were observed. We constructed a 1500°C isothermal phase diagram based on the experimentally measured liquid compositions. We compared simulations using MTDATA and FactSage thermodynamic software and their databases with the experimental results obtained in this study. These results can be used to provide guidelines for updating the MTDATA and FactSage titania-bearing thermodynamic databases by reassessing the thermodynamic properties of the phase with new experimental data.


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