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Related papers: Mechanical Metamaterials Fabricated from Self-asse…

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Mechanical metamaterials present a promising platform for seemingly impossible mechanics. They often require incompatibility of their elementary building blocks, yet a comprehensive understanding of its role remains elusive. Relying on an…

Soft Condensed Matter · Physics 2021-06-16 Ben Pisanty , Erdal C. Oguz , Cristiano Nisoli , Yair Shokef

Recent advances in hyperbolic metamaterials have spurred many breakthroughs in the field of manipulating light propagation. However, the unusual electromagnetic properties also put extremely high demands on its compositional materials.…

Applied Physics · Physics 2021-03-16 Li-Zheng Yin , Feng-Yuan Han , Jin Zhao , Di Wang , Tie-Jun Huang , Pu-Kun Liu

Metamaterials are nano-engineered media with designed properties beyond those available in nature with applications in all aspects of materials science. In particular, metamaterials have shown promise for next generation of optical…

Mesoscale and Nanoscale Physics · Physics 2014-08-19 Prashant Shekhar , Jonathan Atkinson , Zubin Jacob

Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has emerged as a powerful tool for advancing this understanding and…

Metamaterials are composite structures whose properties arise from a mesoscale organization of their constituents. Provided this organization occurs on scales smaller than the characteristic lengths associated with their response, it is…

Soft Condensed Matter · Physics 2022-06-03 Prateek Sehgal , Meera Ramaswamy , Edward Y. X. Ong , Christopher Ness , Itai Cohen , Brian J. Kirby

We describe some of the important physical characteristics of the `pathways', i.e. dynamical processes, by which molecular, nanoscale and micron-scale self-assembly occurs. We highlight the fact that there exist features of self-assembly…

Statistical Mechanics · Physics 2016-03-22 Stephen Whitelam , Robert L. Jack

The self-assembly of metallic colloidal clusters (so called plasmonic metamolecules) has been viewed as a versatile, but highly effective approach for the materialization of the metamaterials exhibiting artificial magnetism at optical…

Optics · Physics 2018-11-21 Kwangjin Kim , Ji-Hyeok Huh , Doyoung Yu , Seungwoo Lee

Machine learning techniques have been widely employed as effective tools in addressing various engineering challenges in recent years, particularly for the challenging task of microstructure-informed materials modeling. This work provides a…

Materials Science · Physics 2024-05-29 Xiang-Long Peng , Mozhdeh Fathidoost , Binbin Lin , Yangyiwei Yang , Bai-Xiang Xu

A concept of a planar modular mechanical metamaterial inspired by the nature's principle of local adaptivity is proposed. The metamaterial consists of identical pieces similar to jigsaw puzzle tiles. Their rotation within assembly provides…

Materials Science · Physics 2018-09-12 V. Nežerka , M. Somr , T. Janda , J. Vorel , M. Doškář , J. Antoš , J. Zeman , J. Novák

Defects, and in particular topological defects, are architectural motifs that play a crucial role in natural materials. Here we provide a systematic strategy to introduce such defects in mechanical metamaterials. We first present…

Soft Condensed Matter · Physics 2020-03-18 Anne S. Meeussen , Erdal C. Oguz , Yair Shokef , Martin van Hecke

By coupling controllable quantum systems into larger structures we introduce the concept of a quantum metamaterial. Conventional meta-materials represent one of the most important frontiers in optical design, with applications in diverse…

Multi-step pathways, constituted of a sequence of reconfigurations, are central to a wide variety of natural and man-made systems. Such pathways autonomously execute in self-guided processes such as protein folding and self-assembly, but…

Soft Condensed Matter · Physics 2018-10-18 Corentin Coulais , Alberico Sabbadini , Fré Vink , Martin van Hecke

Understanding how living organisms spontaneously develop complex functional structures inspires innovative approaches in engineering design. Here, we introduce a decentralized generative model based on morphogenesis to autonomously grow…

Applied Physics · Physics 2025-09-15 Thomas Fromentèze , Philippe Michaud , Ali Hassny , Vincent Pateloup

Machine-learning (ML) techniques have revolutionized a host of research fields of chemical and materials science with accelerated, high-efficiency discoveries in design, synthesis, manufacturing, characterization and application of novel…

Materials Science · Physics 2021-08-31 Zhexu Xi

Artificial intelligence is gaining strength and materials science can both contribute to and profit from it. In a simultaneous progress race, new materials, systems and processes can be devised and optimized thanks to machine learning…

Materials Science · Physics 2022-09-29 Cefe López

Materials informatics offers a promising pathway towards rational materials design, replacing the current trial-and-error approach and accelerating the development of new functional materials. Through the use of sophisticated data analysis…

Materials Science · Physics 2018-05-17 Cormac Toher , Corey Oses , Stefano Curtarolo

Metamaterials exhibit materials response deviation from conventional elasticity. This phenomenon is captured by the generalized elasticity as a result of extending the theory at the expense of introducing additional parameters. These…

Computational Engineering, Finance, and Science · Computer Science 2021-06-10 Bilen Emek Abali , Emilio Barchiesi

There is a growing mechanics literature concerning the macroscopic properties of mechanism-based mechanical metamaterials. This amounts mathematically to a homogenization problem involving nonlinear elasticity. A key goal is to identify the…

Analysis of PDEs · Mathematics 2025-11-10 Xuenan Li , Robert V. Kohn

Fully harnessing the vast design space enabled by metamaterials to control electromagnetic (EM) fields remains an open problem for researchers. Inverse-design techniques have shown to best exploit the degrees of freedom available in design,…

Optics · Physics 2025-11-27 Jorge Ruiz-Garcia , Anthony Grbic

Over the past decade inter-atomic potentials based on machine-learning (ML) techniques have become an indispensable tool in the atomic-scale modeling of materials. Trained on energies and forces obtained from electronic-structure…

Materials Science · Physics 2022-08-15 Michele Ceriotti