Effect of dislocations on the structural order parameter in a crystal upon torsional strain

2017 ◽  
Vol 59 (11) ◽  
pp. 2290-2295 ◽  
Author(s):  
Yu. D. Zavorotnev ◽  
A. Yu. Zakharov ◽  
L. S. Metlov
Keyword(s):  
Order Parameter ◽  
Torsional Strain ◽  
Structural Order

scholarly journals Autonomously revealing hidden local structures in supercooled liquids

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Emanuele Boattini ◽  
Susana Marín-Aguilar ◽  
Saheli Mitra ◽  
Giuseppe Foffi ◽  
Frank Smallenburg ◽  
...  
Keyword(s):  
Machine Learning ◽  
Disordered Systems ◽  
Order Parameter ◽  
Learning Algorithm ◽  
Structural Characteristics ◽  
Supercooled Liquids ◽  
Machine Learning Techniques ◽  
Unsupervised Machine Learning ◽  
Local Structures ◽  
Structural Order

Abstract Few questions in condensed matter science have proven as difficult to unravel as the interplay between structure and dynamics in supercooled liquids. To explore this link, much research has been devoted to pinpointing local structures and order parameters that correlate strongly with dynamics. Here we use an unsupervised machine learning algorithm to identify structural heterogeneities in three archetypical glass formers—without using any dynamical information. In each system, the unsupervised machine learning approach autonomously designs a purely structural order parameter within a single snapshot. Comparing the structural order parameter with the dynamics, we find strong correlations with the dynamical heterogeneities. Moreover, the structural characteristics linked to slow particles disappear further away from the glass transition. Our results demonstrate the power of machine learning techniques to detect structural patterns even in disordered systems, and provide a new way forward for unraveling the structural origins of the slow dynamics of glassy materials.

scholarly journals Structural order as a genuine control parameter of dynamics in simple glass formers

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Hua Tong ◽  
Hajime Tanaka
Keyword(s):  
Glass Transition ◽  
Order Parameter ◽  
Liquid Structure ◽  
Coarse Grained ◽  
Glassy Dynamics ◽  
Slowing Down ◽  
Structural Order ◽  
Particle Level ◽  
Complex Structural ◽  
Unified Description

AbstractGlass transition is characterised by drastic dynamical slowing down upon cooling, accompanied by growing spatial heterogeneity. Its rationalisation by subtle changes in the liquid structure has been long debated but remains elusive, due to intrinsic difficulty in detecting the underlying complex structural ordering. Here we report that structural order parameter characterising local packing capability can well describe the glassy dynamics not only macroscopically but also microscopically, no matter whether it is driven by temperature or density. A Vogel-Fulcher-Tammann (VFT)-like relation is universally identified between the structural relaxation time and the order parameter for supercooled liquids with isotropic interactions. More importantly, we find such an intriguing VFT-like relation to be statistically valid even at a particle level, between spatially coarse-grained structural order and microscopic particle-level dynamics. Such a unified description of glassy dynamics based solely on structural order is expected to contribute to the ultimate understanding of the long-standing glass-transition problem.

scholarly journals Feature of the behavior of structural order parameter in course of plastic deformation by twisting

2020 ◽  
Vol 1658 ◽  
pp. 012080
Author(s):  
Yu D Zavorotnev ◽  
L S Metlov ◽  
A M Glezer ◽  
A Yu Zakharov ◽  
E Yu Tomashevskaya
Keyword(s):  
Plastic Deformation ◽  
Order Parameter ◽  
Structural Order

Aging-dependent modification of lipid composition and lipid structural order parameter of hepatic mitochondria

1982 ◽  
Vol 217 (1) ◽  
pp. 351-361 ◽  
Author(s):  
Marie L. Vorbeck ◽  
Arlene P. Martin ◽  
James W. Long ◽  
Jennie M. Smith ◽  
Richard R. Orr
Keyword(s):  
Lipid Composition ◽  
Order Parameter ◽  
Structural Order ◽  
Dependent Modification

An increase of structural order parameter in Fe–Co–V soft magnetic alloy after thermal aging

1996 ◽  
Vol 69 (25) ◽  
pp. 3917-3919 ◽  
Author(s):  
Q. Zhu ◽  
L. Li ◽  
M. S. Masteller ◽  
G. J. Del Corso
Keyword(s):  
Thermal Aging ◽  
Order Parameter ◽  
Magnetic Alloy ◽  
Soft Magnetic ◽  
Soft Magnetic Alloy ◽  
Structural Order
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