Department of Chemical Engineering, Biotechnology and Materials, Engineering Sciences Faculty, Ariel University, Ariel 407000, Israel.
Published: April 2019
AI Article Synopsis
Article Abstract
The Voronoi entropy for random patterns and patterns demonstrating various elements of symmetry was calculated. The symmetric patterns were characterized by the values of the Voronoi entropy being very close to those inherent to random ones. This contradicts the idea that the Voronoi entropy quantifies the ordering of the seed points constituting the pattern. Extension of the Shannon-like formula embracing symmetric patterns is suggested. Analysis of Voronoi diagrams enables the elements of symmetry of the patterns to be revealed.
We carry out experiments in diffusion-precipitation systems in a framework with multiple diffusion sources. The advancing precipitation fronts reach a point where they stop, leaving a rift or gap between the precipitate zones. In a similar setting, fractal metal deposits emerging from various reduction centers were synthesized.
In this study, we simulate breath figures that are evolving two-dimensional assemblies of droplets on a substrate. We focus on the Voronoi/Shannon entropy of these figures, which quantifies the order related to the coordination number of droplets. We show that the Voronoi entropy of the complete breath figure pattern converges to a value that is the one of a randomly distributed point system.
The most trivial example of self-assembly is the entropy-driven crystallization of hard spheres. Past works have established the similarities and differences in the phase behavior of monomers and chains made of hard spheres. Inspired by the difference in the melting points of the pure components, we study, through Monte Carlo simulations, the phase behavior of athermal mixtures composed of fully flexible polymers and individual monomers of uniform size.
Self-assembled microdroplet clusters can levitate above a locally heated water surface. Normally, the temperature of droplets is in the range of 50-95 °C. However, it is possible to generate clusters at lower temperatures.
State Key Laboratory of Advanced Special Steel & Shanghai Key Laboratory of Advanced Ferrometallurgy & School of Materials Science and Engineering, Shanghai University,99 Shangda Road, Baoshan District, Shanghai 200444, China.
The short-range order (SRO) structure in high-entropy alloys (HEAs) is closely associated with many properties, which can be studied through density functional theory (DFT) calculations. Atomic-scale modeling and calculations require substantial computational resources, and machine learning can provide rapid estimations of DFT results. To describe SRO information in HEAs, a new descriptor based on Voronoi Analysis and Shannon Entropy (VASE) is proposed.
