Nucleation Behavior ofd-Threonine on Different Faces ofl-Threonine Crystals

2008 ◽  
Vol 8 (8) ◽  
pp. 2716-2720 ◽  
Author(s):  
Akihiko Ito ◽  
Masakuni Matsuoka
Keyword(s):  
Nucleation Behavior

Uncover Cooling Rate and Temperature Dependent on Nucleation Behavior of Nicotinic Acid

2021 ◽  
pp. 126185
Author(s):  
Conghui Zhao ◽  
Di Cao ◽  
Wenli Zhao ◽  
Shijie Xu ◽  
Yanfei Wang
Keyword(s):  
Nicotinic Acid ◽  
Cooling Rate ◽  
Temperature Dependent ◽  
Nucleation Behavior

scholarly journals Nucleation Behavior of a Single Al-20Si Particle Rapidly Solidified in a Fast Scanning Calorimeter

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2920
Author(s):  
Qin Peng ◽  
Bin Yang ◽  
Benjamin Milkereit ◽  
Dongmei Liu ◽  
Armin Springer ◽  
...  
Keyword(s):  
Cooling Rate ◽  
Rapid Solidification ◽  
Heterogeneous Nucleation ◽  
Nucleation Theory ◽  
Classical Nucleation Theory ◽  
Solidification Behavior ◽  
Nucleation Kinetics ◽  
Nucleation Behavior ◽  
Nucleation Undercooling ◽  
Primary Si

Understanding the rapid solidification behavior characteristics, nucleation undercooling, and nucleation mechanism is important for modifying the microstructures and properties of metal alloys. In order to investigate the rapid solidification behavior in-situ, accurate measurements of nucleation undercooling and cooling rate are required in most rapid solidification processes, e.g., in additive manufacturing (AM). In this study, differential fast scanning calorimetry (DFSC) was applied to investigate the nucleation kinetics in a single micro-sized Al-20Si (mass%) particle under a controlled cooling rate of 5000 K/s. The nucleation rates of primary Si and secondary α-Al phases were calculated by a statistical analysis of 300 identical melting/solidification experiments. Applying a model based on the classical nucleation theory (CNT) together with available thermodynamic data, two different heterogeneous nucleation mechanisms of primary Si and secondary α-Al were proposed, i.e., surface heterogeneous nucleation for primary Si and interface heterogenous nucleation for secondary α-Al. The present study introduces a practical method for a detailed investigation of rapid solidification behavior of metal particles to distinguish surface and interface nucleation.

Glass-Forming Ability and Crystallization of High Purity Pd-Cu-Ni-P Alloy

2000 ◽  
Vol 644 ◽  
Author(s):  
Nobuyuki Nishiyama ◽  
Mitsuhide Matsushita ◽  
Akihisa Inoue
Keyword(s):  
High Purity ◽  
Isothermal Annealing ◽  
Glass Forming Ability ◽  
In Situ Tem ◽  
Nucleation Behavior ◽  
Spherical Region ◽  
Glass Forming ◽  
High Purity Alloy ◽  
Nose Temperature

AbstractGlass-forming ability, thermal stability and nucleation behavior of a Pd40Cu30Ni10P20 alloy prepared using a high purity polycrystalline phosphorus are investigated. The critical cooling rate for glass formation for the high purity alloy is the same as that for the previous result, but the improvement of undercooling reaches about 80 K as compared with the fluxed ordinary alloy. In comparison with the non-fluxed alloy, the solidified structure of the present highly purified alloy is significantly different. The non-fluxed sample shows the characteristic “island-like” structure consisted of acicular fcc-Pd2Ni2P solid solution and Cu3Pd intermetallic compound. These acicular phases appear to be caused by the growth of quenched-in nuclei. In the isothermal experiment, nucleus density exhibits time dependence even at 683 K near the nose temperature. It is assumed that the crystallization behavior for the highly purified alloy is closer to homogeneous nucleation from quenched-in nuclei dominant behavior. In order to investigate the nucleation behavior, in-situ TEM observation was carried out. Spherical Pd15P2 particle with a diameter about 15 nm is observed, and this spherical region repeats generation and annihilation during isothermal annealing. The reason for the high glass-forming ability is discussed on the basis of the obtained results.

Interfaces-dominated Li2S nucleation behavior enabled by heterostructure catalyst for fast kinetics Li-S batteries

Nano Energy ◽  
2021 ◽  
Vol 89 ◽  
pp. 106452
Author(s):  
Da-Qian Cai ◽  
Jin-Lin Yang ◽  
Ting Liu ◽  
Shi-Xi Zhao ◽  
Guozhong Cao
Keyword(s):  
Nucleation Behavior ◽  
Fast Kinetics

scholarly journals The Role of Nucleation Behavior in Phase-Field Simulations of the Austenite to Ferrite Transformation

2008 ◽  
Vol 39 (6) ◽  
pp. 1237-1247 ◽  
Author(s):  
M.G. Mecozzi ◽  
M. Militzer ◽  
J. Sietsma ◽  
S. van der Zwaag
Keyword(s):  
Phase Field ◽  
Nucleation Behavior ◽  
Ferrite Transformation

Effect of Cooling Rate on Nucleation Behavior of Milk Fat−Sunflower Oil Blends

2001 ◽  
Vol 49 (7) ◽  
pp. 3223-3229 ◽  
Author(s):  
S. Martini ◽  
M. L. Herrera ◽  
R. W. Hartel
Keyword(s):  
Cooling Rate ◽  
Sunflower Oil ◽  
Milk Fat ◽  
Nucleation Behavior ◽  
Oil Blends

scholarly journals Aerosol-cloud interactions: The representation of heterogeneous ice activation in cloud models

2021 ◽  
Author(s):  
Bernd Kärcher ◽  
Claudia Marcolli
Keyword(s):  
Phase Transitions ◽  
Particle Number ◽  
Water Phase ◽  
Cloud Formation ◽  
Ice Formation ◽  
Ice Crystal ◽  
Nucleation Behavior ◽  
Aerosol Cloud ◽  
Cloud Models ◽  
Aerosol Cloud Interactions

Abstract. The homogeneous nucleation of ice in supercooled liquid water clouds is characterized by time-dependent freezing rates. By contrast, water phase transitions induced heterogeneously by ice nucleating particles (INPs) are described by time-independent ice-active fractions depending on ice supersaturation (s). Laboratory studies report ice-active particle number fractions (AFs) that are cumulative in s. Cloud models budget INP and ice crystal numbers to conserve total particle number during water phase transitions. Here, we show that ice formation from INPs with time-independent nucleation behavior is overpredicted when models budget particle numbers and at the same time derive ice crystal numbers from s-cumulative AFs. This causes a bias towards heterogeneous ice formation in situations where INPs compete with homogeneous droplet freezing during cloud formation. We resolve this issue by introducing differential AFs, moving us one step closer to more robust simulations of aerosol-cloud interactions.

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