Defect Interactions in Anisotropic Two-Dimensional Fluids

Stannarius, Ralf; Harth, Kirsten

doi:10.1103/physrevlett.117.157801

Cited by 26 publications

(35 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Even small differences K B − K S suffice to fix the phase. This was demonstrated in previous experiments [28] which revealed some limitations of the classical models in SmC films.…”

supporting

confidence: 57%

Annihilation of point defect pairs in freely suspended liquid-crystal films

Missaoui

Harth

Szűcs

et al. 2020

Phys. Rev. Research

View full text Add to dashboard Cite

We study the annihilation of topological defect pairs in the quasi-twodimensional (2D) geometry of freely suspended smectic films. This elementary process is at the basis of all models describing the statistics of complex defect patterns. We prepare pairs with opposite topological charges and retrieve the interaction mechanisms from their trajectories. The square-root dependence of the defect separation on the time until annihilation and the asymmetry in propagation velocities of the opponents predicted by theory are confirmed. The importance of defect orientations is demonstrated. Trajectories are in general curved, depending on the mutual orientations (phase mismatch) of the defects and on the orientation of the pair respective to the far, undisturbed director. The experiments provide the basis for an adaption of the theoretical models to the real complexity of the annihilation.

show abstract

“…Even small differences K B − K S suffice to fix the phase. This was demonstrated in previous experiments [28] which revealed some limitations of the classical models in SmC films.…”

supporting

confidence: 57%

Annihilation of point defect pairs in freely suspended liquid-crystal films

Missaoui

Harth

Szűcs

et al. 2020

Phys. Rev. Research

View full text Add to dashboard Cite

show abstract

“…1(b)]. This decomposition reduces the elastic energy, which scales as s 2 away from the defect core [7,[36][37][38]. The decomposed daughter [39] defects repel each other such that, at the master surface, their separation distance is a competition between the anchoring strength imposed by the master substrate and the repulsion between same-strength defects (see Supplemental Material movie 1 in Ref.…”

Section: Numerical Simulationsmentioning

confidence: 99%

Electric field driven reconfigurable multistable topological defect patterns

Harkai

Murray

Rosenblatt

et al. 2020

Phys. Rev. Research

View full text Add to dashboard Cite

Topological defects appear in symmetry breaking phase transitions and are ubiquitous throughout Nature. As an ideal testbed for their study, defect configurations in nematic liquid crystals (NLCs) could be exploited in a rich variety of technological applications. Here we report on robust theoretical and experimental investigations in which an external electric field is used to switch between predetermined stable chargeless disclination patterns in a nematic cell, where the cell is sufficiently thick that the disclinations start and terminate at the same surface. The different defect configurations are stabilized by a master substrate that enforces a lattice of surface defects exhibiting zero total topological charge value. Theoretically, we model disclination configurations using a Landau-de Gennes phenomenological model. Experimentally, we enable diverse defect patterns by implementing an in-house-developed atomic force measurement scribing method, where NLC configurations are monitored via polarized optical microscopy. We show numerically and experimentally that an "alphabet" of up to 18 unique line defect configurations can be stabilized in a 4 × 4 lattice of alternating s = ±1 surface defects, which can be "rewired" multistably using appropriate field manipulation. Our proof-of-concept mechanism may lead to a variety of applications, such as multistable optical displays and rewirable nanowires. Our studies also are of interest from a fundamental perspective. We demonstrate that a chargeless line could simultaneously exhibit defect-antidefect properties. Consequently, a pair of such antiparallel disclinations exhibits an attractive interaction. For a sufficiently closely spaced pair of substrate-pinned defects, this interaction could trigger rewiring, or annihilation if defects are depinned.

show abstract

“…To first order, the Frank free energy that describes a single smectic-c layer is well approximated by the continuous XY model, which supports as ground-state solutions stable topological defects. The theoretical [23][24][25][26][27]and experimental [28][29][30][31] dynamics of defects in liquid crystal systems has been studied since the early 90's. However, it is an open question how well the non-hydrodynamic XY model describes the interaction of these topological defects in fluidic systems of liquid crystal materials.…”

Section: Introductionmentioning

confidence: 99%

End-to-end machine learning for experimental physics: using simulated data to train a neural network for object detection in video microscopy

et al. 2020

View full text Add to dashboard Cite

We demonstrate a method for training a convolutional neural network with simulated images for usage on real-world experimental data. Modern machine learning methods require large, robust training data sets to generate accurate predictions. Generating these large training sets requires a significant up-front time investment that is often impractical for small-scale applications. Here we demonstrate a 'full-stack' computational solution, where the training data set is generated on-the-fly using a noise injection process to produce simulated data characteristic of the experimental system.We demonstrate the power of this full-stack approach by applying it to the study of topological defect annihilation in systems of liquid crystal freely-suspended films. This specific experimental system requires accurate observations of both the spatial distribution of the defects and the total number of defects, making it an ideal system for testing the robustness of the trained network. The fully trained network was found to be comparable in accuracy to human hand-annotation, with four-orders of magnitude improvement in time efficiency. arXiv:1908.05271v1 [cond-mat.soft]

show abstract

Defect Interactions in Anisotropic Two-Dimensional Fluids

Cited by 26 publications

References 67 publications

Annihilation of point defect pairs in freely suspended liquid-crystal films

Annihilation of point defect pairs in freely suspended liquid-crystal films

Electric field driven reconfigurable multistable topological defect patterns

End-to-end machine learning for experimental physics: using simulated data to train a neural network for object detection in video microscopy

Contact Info

Product

Resources

About