Enhanced sampling of cylindrical microphase separation via a shell-averaged bond-orientational order parameter

Soft Matter ◽  
2020 ◽  
Vol 16 (3) ◽  
pp. 659-667
Author(s):  
Bumjoon Seo ◽  
Min Young Ha ◽  
Ji Woong Yu ◽  
Won Bo Lee

The underlying free energy surfaces for the order–disorder transition of hexagonal mesophase were identified along with the metstable state.

Polymers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1262
Author(s):  
Mikhail A. Osipov ◽  
Maxim V. Gorkunov ◽  
Alexander A. Antonov

Density functional theory of rod-coil diblock copolymers, developed recently by the authors, has been generalised and used to study the liquid crystal ordering and microphase separation effects in the hexagonal, lamellar and nematic phases. The translational order parameters of rod and coil monomers and the orientational order parameters of rod-like fragments of the copolymer chains have been determined numerically by direct minimization of the free energy. The phase diagram has been derived containing the isotropic, the lamellar and the hexagonal phases which is consistent with typical experimental data. The order parameter profiles as functions of temperature and the copolymer composition have also been determined in different anisotropic phases. Finally, the spatial distributions of the density of rigid rod fragments and of the corresponding orientational order parameter in the hexagonal phase have been calculated.


2020 ◽  
Vol 22 (40) ◽  
pp. 23064-23072
Author(s):  
Andraž Rešetič ◽  
Jerneja Milavec ◽  
Valentina Domenici ◽  
Blaž Zupančič ◽  
Alexej Bubnov ◽  
...  

Orientational order parameter of magnetically aligned liquid crystal elastomer particles suspended in a cured silicone matrix is assessed using 2H-NMR spectroscopy. Obtained results correspond well with the composite's thermomechanical response.


2019 ◽  
Vol 116 (36) ◽  
pp. 17641-17647 ◽  
Author(s):  
Luigi Bonati ◽  
Yue-Yu Zhang ◽  
Michele Parrinello

Sampling complex free-energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a direct approach useless. A popular strategy is to identify a small number of key collective variables and to introduce a bias potential that is able to favor their fluctuations in order to accelerate sampling. Here, we propose to use machine-learning techniques in conjunction with the recent variationally enhanced sampling method [O. Valsson, M. Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to determine such potential. This is achieved by expressing the bias as a neural network. The parameters are determined in a variational learning scheme aimed at minimizing an appropriate functional. This required the development of a more efficient minimization technique. The expressivity of neural networks allows representing rapidly varying free-energy surfaces, removes boundary effects artifacts, and allows several collective variables to be handled.


2014 ◽  
Vol 22 (3) ◽  
Author(s):  
J. Kędzierski ◽  
K. Garbat ◽  
Z. Raszewski ◽  
M. Kojdecki ◽  
K. Kowiorski ◽  
...  

AbstractOptical properties of a nematic liquid crystal with small refractive index and small birefringence were studied. The ordinary and extraordinary refractive indices and birefringence were measured as functions of temperature by using an Abbe refractometer and wedge nematic cells. From values of these indices the nematic orientational order parameter was calculated by using several methods and corresponding mathematical models. Kuczyński et al. method was found to be suitable for determining the order parameter also for materials featuring small ordinary refractive index, with unknown density.


2010 ◽  
Vol 528 (1) ◽  
pp. 49-63 ◽  
Author(s):  
M. Ramakrishna ◽  
Nanchara Rao ◽  
P. V. Datta Prasad ◽  
V. G. K. M. Pisipati

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