Stacking faults in Zr(Fe, Cr)2 Laves structured secondary phase particle in Zircaloy-4 alloy

Nanoscale ◽  
2018 ◽  
Vol 10 (5) ◽  
pp. 2249-2254 ◽  
Author(s):  
Chengze Liu ◽  
Geping Li ◽  
Fusen Yuan ◽  
Fuzhou Han ◽  
Yingdong Zhang ◽  
...  
Keyword(s):  
Formation Mechanism ◽  
Phase Particle ◽  
Stacking Faults ◽  
Secondary Phase ◽  
Secondary Phase Particle

Understanding the formation mechanism of stacking faults in secondary phase particles.

Effects of Secondary Phase Particle Dissolution on the In-Reactor Performance of BWR Cladding

2011 ◽  
Vol 8 (2) ◽  
pp. 103025 ◽  
Author(s):  
S. Valizadeh ◽  
G. Ledergerber ◽  
S. Abolhassan ◽  
D. Jädernäs ◽  
M. Dahlbäck ◽  
...  
Keyword(s):  
Phase Particle ◽  
Secondary Phase ◽  
Reactor Performance ◽  
Secondary Phase Particle ◽  
Particle Dissolution

scholarly journals Influence of Cooling Rate on Microsegregation Behavior of Magnesium Alloys

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Md. Imran Khan ◽  
Ahmad O. Mostafa ◽  
Mohammad Aljarrah ◽  
Elhachmi Essadiqi ◽  
Mamoun Medraj
Keyword(s):  
Particle Size ◽  
Cooling Rate ◽  
Magnesium Alloys ◽  
Phase Particle ◽  
Secondary Phase ◽  
Composition Analysis ◽  
Minimum Concentration ◽  
Secondary Phase Particle ◽  
Electron Microscopes ◽  
Area Percentage

The effect of cooling rate on microstructure and microsegregation of three commercially important magnesium alloys was investigated using Wedge (V-shaped) castings of AZ91D, AM60B, and AE44 alloys. Thermocouples were distributed to measure the cooling rate at six different locations of the wedge casts. Solute redistribution profiles were drawn based on the chemical composition analysis obtained by EDS/WDS analysis. Microstructural and morphological features such as dendrite arm spacing and secondary phase particle size were analyzed using both optical and scanning electron microscopes. Dendritic arm spacing and secondary phase particle size showed an increasing trend with decreasing cooling rate for the three alloys. Area percentage of secondary phase particles decreased with decreasing cooling rate for AE44 alloy. The trend was different for AZ91D and AM60B alloys, for both alloys, area percentage of β-Mg17Al12 increased with decreasing cooling rate up to location 4 and then decreased slightly. The tendency for microsegregation was more severe at slower cooling rates, possibly due to prolonged back diffusion. At slower cooling rate, the minimum concentration of aluminum at the dendritic core was lower compared to faster cooled locations. The segregation deviation parameter and the partition coefficient were calculated from the experimentally obtained data.

Effects of Secondary Phase Particle Dissolution on the In-Reactor Performance of BWR Cladding

2011 ◽  
pp. 729-753 ◽  
Author(s):  
S. Valizadeh ◽  
G. Ledergerber ◽  
S. Abolhassani ◽  
D. Jädernäs ◽  
M. Dahlbäck ◽  
...  
Keyword(s):  
Phase Particle ◽  
Secondary Phase ◽  
Reactor Performance ◽  
Secondary Phase Particle ◽  
Particle Dissolution

Effects of Secondary Phase Particle Dissolution on the In-Reactor Performance of BWR Cladding

2011 ◽  
pp. 729-753 ◽  
Author(s):  
S. Valizadeh ◽  
G. Ledergerber ◽  
S. Abolhassani ◽  
D. Jädernäs ◽  
M. Dahlbäck ◽  
...  
Keyword(s):  
Phase Particle ◽  
Secondary Phase ◽  
Reactor Performance ◽  
Secondary Phase Particle ◽  
Particle Dissolution

The Hayashi-nishi Method for Measurement of Mixing:Computer-Generated Morphologies and Impact-Modified Polymers

1998 ◽  
Vol 4 (S2) ◽  
pp. 830-831
Author(s):  
M. R. Tant ◽  
D. B. Calvert ◽  
P. S. Wehner
Keyword(s):  
Phase Particle ◽  
Secondary Phase ◽  
The State ◽  
Polymeric Matrix ◽  
Core Shell ◽  
Secondary Phase Particle ◽  
Modified Polymers ◽  
Impact Modifier ◽  
Image Position ◽  
The Impact

In this work we apply the Hayashi-Nishi method for quantitatively analyzing the state of mixing of a secondary component in a polymeric matrix. We (1) evaluate the method using computer-generated morphologies and (2) compare the state of mixing of a core-shell impact modifier in polymers having differing affinity for the impact modifier. In the Hayashi-Nishi method two numbers, related to dispersion and distribution, are required to quantify the state of mixing of a secondary phase in a polymeric matrix. The 5-parameter in the Hayashi-Nishi method is defined asThe Ai's are the areas of each individual secondary phase particle or aggregate and nis the number of such particles in the image. S is related to the size distribution of these aggregate areas and is a measure of dispersion of the secondary phase in that particular image.

Direct observation of Face-centered cubic zirconium phase growth-induced stacking faults in Zr3Ge secondary phase nanoparticle

2022 ◽  
Vol 210 ◽  
pp. 114461
Author(s):  
Fuzhou Han ◽  
Geping Li ◽  
Fusen Yuan ◽  
Yingdong Zhang ◽  
Wenbin Guo ◽  
...  
Keyword(s):  
Direct Observation ◽  
Stacking Faults ◽  
Secondary Phase ◽  
Face Centered Cubic ◽  
Phase Growth ◽  
Face Centered

Similarity analysis of stacking sequences in a SiC nanowire pair grown from the same catalyst nanoparticle using Levenshtein distance

Microscopy ◽  
2020 ◽  
Vol 69 (4) ◽  
pp. 234-239
Author(s):  
Takayuki Kataoka ◽  
Takumi Noguchi ◽  
Hideo Kohno
Keyword(s):  
Formation Mechanism ◽  
Stacking Faults ◽  
Surrogate Data ◽  
Binary Sequences ◽  
Metal Catalyst ◽  
Similarity Analysis ◽  
Levenshtein Distance ◽  
Proof Of Concept ◽  
Sic Nanowires ◽  
Catalyst Nanoparticle

Abstract Stacking faults are easily formed in silicon carbide (SiC) crystals, and this is also the case for SiC nanowires. The stacking faults exercise influences on SiC’s properties, therefore it is important to understand their formation mechanism and to control their formation for applications of SiC and its nanowires. In this study, we propose a method for investigating stacking faults’ formation mechanism in nanowires and provide its proof of concept. Stacking sequences in a pair of SiC nanowires that were grown from the same metal catalyst nanoparticle were quantified as a pair of binary sequences, and Levenshtein distances between partial sequences extracted from the two sequences were measured to detect similarity between them, and the result was compared with that obtained using a surrogate data of one sequence. The similarity analysis using Levenshtein distances works as a probe for investigating possible influences of some phenomena in the catalyst nanoparticle on the formation of stacking faults. The analysis did not detect a correlation between the two sequences. Although a possibility that the formation of stacking faults in the nanowires were owing to some phenomena in the catalyst nanoparticle cannot be denied, the extrinsic cause in the catalyst nanoparticle was not detected through our analysis in this case.

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