Results 51 to 60 of about 21,421 (221)
Automatic Determination of Quasicrystalline Patterns from Microscopy Images
Advanced Intelligent Discovery, EarlyView.This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender +2 more
wiley +1 more source
Quasicrystals - Discovery, Structure and Properties [PDF]
Kemija u Industriji, 2012 Quasicrystals are solid materials the structures of which can have crystallographically forbidden symmetries, e.g. of the fifth order, and do not have the translational invariance charactistic for classical crystals.
Stilinović, V., Brückler, F. M.
doaj
Crystals, 2016 A rigorous method for obtaining the diffraction patterns of quasicrystals is presented. Diffraction patterns are an essential analytical tool in the study of quasicrystals, since they can be used to determine their photonic resonances.
Farhad A. Namin, Douglas H. Werner
doaj +1 more source
The eight-fold way for optical quasicrystals
, 2013 In a recent Letter we proposed a means to realize a quasicrystal with eight-fold symmetry by trapping particles in an optical potential created by four lasers.
Duneau, Michel, Jagannathan, Anuradha
core +4 more sources
Quasicrystals, model sets, and automatic sequences [PDF]
, 2014 We survey mathematical properties of quasicrystals, first from the point of view of harmonic analysis, then from the point of view of morphic and automatic sequences. Nous proposons un tour d'horizon de propri\'et\'es math\'ematiques des quasicristaux,
Allouche, Jean-Paul, Meyer, Yves
core +3 more sources
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
, 2019 This article is made available for reference. It was written following the March 2006 workshop "The World a Jigsaw: Tessellations in the Sciences" at the Lorentz Center, and due to be published in a book entitled "Tessellations in the Sciences: Virtues, Techniques and Applications of Geometric Tilings" (eds R van de Weijgaert, G Vegter, J Ritzerveld ...
Grimm, Uwe, Kramer, Peter
openaire +2 more sources
Landau levels in quasicrystals
, 2018 Two-dimensional tight-binding models for quasicrystals made of plaquettes with commensurate areas are considered. Their energy spectrum is computed as a function of an applied perpendicular magnetic field.
Fuchs, Jean-Noël +2 more
core +1 more source
Macromolecular Materials and Engineering, EarlyView.Due to the different conformation structures of the grafting chains on the surface of silica, the nanoparticles contact each other by brush chains and bridge into a polymer‐mediated nanoparticle network in HDPE14K/HDPE1K‐g‐SiO2 PNCs, resulting in a more significant modulus reinforcement than that of PP370K/PP90K‐g‐SiO2 PNCs with a soft interfacial ...
Ye Yao +4 more
wiley +1 more source
Acta Crystallographica Section B, EarlyView.A structural solution is presented of a primitive icosahedral ZnMgEr quasicrystal representing the Bergman‐type family. The structure model is based on atomic decoration of the Ammann–Kramer–Neri tiling.This study presents the atomic structure solution of a primitive icosahedral Zn70.83Mg20.31Er8.86 quasicrystal using in‐house X‐ray diffraction and the
Ireneusz Buganski +7 more
wiley +1 more source