Faculty Opinions recommendation of Critical nucleus size for disease-related polyglutamine aggregation is repeat-length dependent.

2011 ◽  
Author(s):  
Nikolay Dokholyan ◽  
Feng Ding
Keyword(s):  
Critical Nucleus ◽  
Repeat Length ◽  
Nucleus Size ◽  
Critical Nucleus Size ◽  
Polyglutamine Aggregation

scholarly journals Critical nucleus size for disease-related polyglutamine aggregation is repeat-length dependent

2011 ◽  
Vol 18 (3) ◽  
pp. 328-336 ◽  
Author(s):  
Karunakar Kar ◽  
Murali Jayaraman ◽  
Bankanidhi Sahoo ◽  
Ravindra Kodali ◽  
Ronald Wetzel
Keyword(s):  
Critical Nucleus ◽  
Repeat Length ◽  
Nucleus Size ◽  
Critical Nucleus Size ◽  
Polyglutamine Aggregation

Homogeneous nucleation in a Poiseuille flow

2021 ◽  
Vol 23 (6) ◽  
pp. 3974-3982
Author(s):  
Fuqian Yang
Keyword(s):  
Poiseuille Flow ◽  
Homogeneous Nucleation ◽  
Critical Nucleus ◽  
Flow Speed ◽  
Nucleus Size ◽  
Average Flow ◽  
Critical Nucleus Size

Variation of the critical nucleus size and the corresponding work of formation with average flow speed at axisymmetric axis.

Trapping Effect on the Kinetic Critical Radius in Nucleation and Growth Processes

2014 ◽  
Vol 790-791 ◽  
pp. 97-102
Author(s):  
Zoltán Erdélyi ◽  
Zoltán Balogh ◽  
Gabor L. Katona ◽  
Dezső L. Beke
Keyword(s):  
Critical Nucleus ◽  
Solid Phase ◽  
Kinetic Monte Carlo ◽  
Mean Field ◽  
Transformation Process ◽  
Nucleus Size ◽  
Critical Nucleus Size ◽  
Acta Mater ◽  
Order Of Magnitude ◽  
The Difference

The critical nucleus size—above which nuclei grow, below dissolve—during diffusion controlled nucleation in binary solid-solid phase transformation process is calculated using kinetic Monte Carlo (KMC). If atomic jumps are slower in an A-rich nucleus than in the embedding B-rich matrix, the nucleus traps the A atoms approaching its surface. It doesn’t have enough time to eject A atoms before new ones arrive, even if it would be favourable thermodynamically. In this case the critical nucleus size can be even by an order of magnitude smaller than expected from equilibrium thermodynamics or without trapping. These results were published in [Z. Erdélyi et al., Acta Mater. 58 (2010) 5639]. In a recent paper M. Leitner [M. Leitner, Acta Mater. 60 (2012) 6709] has questioned our results based on the arguments that his simulations led to different results, but he could not point out the reason for the difference. In this paper we summarize our original results and on the basis of recent KMC and kinetic mean field (KMF) simulations we show that Leitner’s conclusions are not valid and we confirm again our original results.

scholarly journals Nucleation rate analysis of methane hydrate from molecular dynamics simulations

2015 ◽  
Vol 179 ◽  
pp. 463-474 ◽  
Author(s):  
Daisuke Yuhara ◽  
Brian C. Barnes ◽  
Donguk Suh ◽  
Brandon C. Knott ◽  
Gregg T. Beckham ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Nucleation Rate ◽  
Methane Hydrate ◽  
Critical Nucleus ◽  
Md Simulations ◽  
Clathrate Hydrate ◽  
Clathrate Hydrates ◽  
Growth Effect ◽  
Nucleus Size ◽  
Critical Nucleus Size

Clathrate hydrates are solid crystalline structures most commonly formed from solutions that have nucleated to form a mixed solid composed of water and gas. Understanding the mechanism of clathrate hydrate nucleation is essential to grasp the fundamental chemistry of these complex structures and their applications. Molecular dynamics (MD) simulation is an ideal method to study nucleation at the molecular level because the size of the critical nucleus and formation rate occur on the nano scale. Various analysis methods for nucleation have been developed through MD to analyze nucleation. In particular, the mean first-passage time (MFPT) and survival probability (SP) methods have proven to be effective in procuring the nucleation rate and critical nucleus size for monatomic systems. This study assesses the MFPT and SP methods, previously used for monatomic systems, when applied to analyzing clathrate hydrate nucleation. Because clathrate hydrate nucleation is relatively difficult to observe in MD simulations (due to its high free energy barrier), these methods have yet to be applied to clathrate hydrate systems. In this study, we have analyzed the nucleation rate and critical nucleus size of methane hydrate using MFPT and SP methods from data generated by MD simulations at 255 K and 50 MPa. MFPT was modified for clathrate hydrate from the original version by adding the maximum likelihood estimate and growth effect term. The nucleation rates calculated by MFPT and SP methods are within 5%, and the critical nucleus size estimated by the MFPT method was 50% higher, than values obtained through other more rigorous but computationally expensive estimates. These methods can also be extended to the analysis of other clathrate hydrates.

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