Results 81 to 90 of about 27,519 (287)

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, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

Discharge performance of Mg–Zn–Y alloys by regulating quasicrystal I phase as anodes for Mg-air battery

Journal of Materials Research and Technology
To investigate the influence of the morphology and amount of quasicrystal I phase on discharge performance, a comparative study is conducted on the discharge characteristics of Mg-2.4Zn-0.4Y (ZW-1), Mg-3.6Zn-0.6Y (ZW-2), and Mg-4.8Zn-0.8Y (ZW-3).
Wenhao Li, Kaibo Nie, Kunkun Deng, Quanxin Shi   +3 more
doaj   +1 more source

Identifying and Indexing Icosahedral Quasicrystals from Powder Diffraction Patterns

, 2001
We present a scheme to identify quasicrystals based on powder diffraction data and to provide a standardized indexing. We apply our scheme to a large catalog of powder diffraction patterns, including natural minerals, to look for new quasicrystals. Based
A. I. Goldman, A. P. Tsai, C. Janot, D. Levine, D. Levine, J. W. Cahn, Kenneth Deffeyes, Nan Yao, P. A. Bancel, Paul J. Steinhardt, Peter J. Lu, V. Elser   +11 more
core   +1 more source

Numerical Methods for Quasicrystals [PDF]

, 2013
Quasicrystals are one kind of space-filling structures. The traditional crystalline approximant method utilizes periodic structures to approximate quasicrystals.
Jiang, Kai, Zhang, Pingwen
core   +1 more source

Applied Artificial Intelligence in Materials Science and Material Design

Advanced Intelligent Systems, EarlyView.
AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material ...
Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza   +7 more
wiley   +1 more source

Methods for Calculating Empires in Quasicrystals

Crystals, 2017
This paper reviews the empire problem for quasiperiodic tilings and the existing methods for generating the empires of the vertex configurations in quasicrystals, while introducing a new and more efficient method based on the cut-and-project technique ...
Fang Fang, Dugan Hammock, Klee Irwin
doaj   +1 more source

Effect of milling time on XRD phases and microstructure of a novel Al67Cu20Fe10B3 quasicrystalline alloy

Materials Research Express, 2020
The quasicrystalline materials represent a new materials group with definite crystallite structural characteristics, in which the AlCuFe(B) quasicrystalline alloys have been widely studied owing to its various technological advantages such as easily ...
Meysam Amini, Mohammad Reza Rahimipour, Seyed Ali Tayebifard, Yahya Palizdar   +3 more
doaj   +1 more source

Neutron scattering study on spin correlations and fluctuations in the transition-metal-based magnetic quasicrystal Zn-Fe-Sc

, 2007
Spin correlations and fluctuations in the 3d-transition-metal-based icosahedral quasicrystal Zn-Fe-Sc have been investigated by neutron scattering using polycrystalline samples.
A. Abragam, Chihiro Masuda, Isao Nakanowatari, Kazuki Iida, Rei Morinaga, S. W. Lovesey, Shiro Kashimoto, T. Ishimasa, T. J. Sato, Takahiro Onimaru, Taku J. Sato, Tsutomu Ishimasa   +11 more
core   +1 more source

Predicting Lattice Thermal Conductivity in 2D Materials: Integrating Experiments, Theory, and Machine Learning

FlexTech, EarlyView.
This review summarizes the latest research progress on the thermal conductivity of two‐dimensional materials in experiments, traditional theoretical methods, and machine learning approaches, highlighting their integration and future development directions. ABSTRACT Lattice thermal conductivity is a critical parameter for assessing the thermal transport
Jie Zhu, Yajing Sun
wiley   +1 more source

ON SELF-SIMILARITIES OF CUT-AND-PROJECT SETS

Acta Polytechnica, 2017
Among the commonly used mathematical models of quasicrystals are Delone sets constructed using a cut-and-project scheme, the so-called cut-and-project sets.
Zuzana Masáková, Jan Mazáč
doaj   +1 more source