Growth-rate-dependent laterally graded SiGe profiles on insulator by cooling-rate controlled rapid-melting-growth

2012 ◽  
Vol 101 (24) ◽  
pp. 241904 ◽  
Author(s):  
Ryo Matsumura ◽  
Yuki Tojo ◽  
Masashi Kurosawa ◽  
Taizoh Sadoh ◽  
Ichiro Mizushima ◽  
...  
Keyword(s):  
Growth Rate ◽  
Cooling Rate ◽  
Rapid Melting ◽  
Rate Dependent ◽  
Rate Controlled

Laterally Graded SiGe-on-Insulator with Universal Si Profile by Cooling-Rate-Controlled Rapid-Melting-Growth

2012 ◽  
Author(s):  
R. Matsumura ◽  
Y. Tojo ◽  
H. Yokoyama ◽  
M. Kurosawa ◽  
T. Sadoh ◽  
...  
Keyword(s):  
Cooling Rate ◽  
Rapid Melting ◽  
Rate Controlled

scholarly journals Chip-size formation of high-mobility Ge strips on SiN films by cooling rate controlled rapid-melting growth

2011 ◽  
Vol 99 (3) ◽  
pp. 032103 ◽  
Author(s):  
Kaoru Toko ◽  
Yasuharu Ohta ◽  
Takanori Tanaka ◽  
Taizoh Sadoh ◽  
Masanobu Miyao
Keyword(s):  
Cooling Rate ◽  
High Mobility ◽  
Rapid Melting ◽  
Chip Size ◽  
Rate Controlled

Thermal Parameters, Microstructure and Porosity During Transient Solidification of Ternary Al–Cu–Si Alloys

2012 ◽  
Vol 730-732 ◽  
pp. 883-888 ◽  
Author(s):  
Daniel J. Moutinho ◽  
Laércio G. Gomes ◽  
Otávio L. Rocha ◽  
Ivaldo L. Ferreira ◽  
Amauri Garcia
Keyword(s):  
Growth Rate ◽  
Chemical Composition ◽  
Cooling Rate ◽  
Tip Growth ◽  
Thermal Parameters ◽  
Volumetric Fraction ◽  
Dendritic Network ◽  
Intermetallic Particles ◽  
Casting Length

Solidification of ternary Al-Cu-Si alloys begins with the development of a complex dendritic network typified by primary (λ1) and secondary (λ2) dendrite arm spacings which depend on the chemical composition of the alloy and on the casting thermal parameters such as the growth rate and the cooling rate. These thermal parameters control the scale of dendritic arms, the size and distribution of porosity and intermetallic particles in the casting. In this paper, λ1and λ2were correlated with experimental thermal parameters i.e., the tip growth rate and the tip cooling rate. The porosity profile along the casting length has also been experimentally determined. The volumetric fraction of pores increase with the increase in alloying Si and with the increase in Fe concentration at the regions close to the casting cooled surface.

A screen for Neurospora knockout mutants displaying growth rate dependent branch density

2011 ◽  
Vol 115 (3) ◽  
pp. 296-301 ◽  
Author(s):  
Michael K. Watters ◽  
Michael Boersma ◽  
Melodie Johnson ◽  
Ciara Reyes ◽  
Evan Westrick ◽  
...  
Keyword(s):  
Growth Rate ◽  
Rate Dependent ◽  
Knockout Mutants ◽  
Branch Density

Cooling rate dependent undercooling of Bi in a Zn matrix by differential fast scanning calorimetry

2014 ◽  
Vol 30 (2) ◽  
pp. 242-247 ◽  
Author(s):  
Linfang Li ◽  
Bingge Zhao ◽  
Bin Yang ◽  
Quanliang Zhang ◽  
Qijie Zhai ◽  
...  
Keyword(s):  
Cooling Rate ◽  
Scanning Calorimetry ◽  
Rate Dependent ◽  
Fast Scanning Calorimetry ◽  
Image Position

Abstract

Growth-rate dependent regulation of mRNA stability in Escherichia coli

Nature ◽  
1984 ◽  
Vol 312 (5989) ◽  
pp. 75-77 ◽  
Author(s):  
G. Nilsson ◽  
J. G. Belasco ◽  
S. N. Cohen ◽  
A. von Gabain
Keyword(s):  
Escherichia Coli ◽  
Growth Rate ◽  
Mrna Stability ◽  
Rate Dependent

scholarly journals Analysis of isothermal and cooling rate dependent immersion freezing by a unifying stochastic ice nucleation model

2015 ◽  
Vol 15 (9) ◽  
pp. 13109-13166
Author(s):  
P. A. Alpert ◽  
D. A. Knopf
Keyword(s):  
Cooling Rate ◽  
Surface Area ◽  
Ice Nucleation ◽  
Rate Dependence ◽  
Nucleation Theory ◽  
Freezing Process ◽  
Nucleation Kinetics ◽  
Rate Dependent ◽  
Immersion Freezing ◽  
The Impact

Abstract. Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature (T) and relative humidity (RH) at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling rate dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nuclei (IN) all have the same IN surface area (ISA), however the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses physically observable parameters including the total number of droplets (Ntot) and the heterogeneous ice nucleation rate coefficient, Jhet(T). This model is applied to address if (i) a time and ISA dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time dependent isothermal frozen fractions exhibiting non-exponential behavior with time can be readily explained by this model considering varying ISA. An apparent cooling rate dependence ofJhet is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. The model simulations allow for a quantitative experimental uncertainty analysis for parameters Ntot, T, RH, and the ISA variability. In an idealized cloud parcel model applying variability in ISAs for each droplet, the model predicts enhanced immersion freezing temperatures and greater ice crystal production compared to a case when ISAs are uniform in each droplet. The implications of our results for experimental analysis and interpretation of the immersion freezing process are discussed.

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