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Related papers: Data-Driven Design for Metamaterials and Multiscal…

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Metamaterials are engineered materials composed of specially designed unit cells that exhibit extraordinary properties beyond those of natural materials. Complex engineering tasks often require heterogeneous unit cells to accommodate…

Machine Learning · Computer Science 2025-11-06 Hongrui Chen , Liwei Wang , Levent Burak Kara

Data-driven design of mechanical metamaterials is an increasingly popular method to combat costly physical simulations and immense, often intractable, geometrical design spaces. Using a precomputed dataset of unit cells, a multiscale…

Computational Engineering, Finance, and Science · Computer Science 2021-12-08 Yu-Chin Chan , Faez Ahmed , Liwei Wang , Wei Chen

Mechanical metamaterials leverage geometric design to achieve unconventional properties, such as high strength at low density, efficient wave guiding, and complex shape morphing. The ability to control shape changes builds on the complex…

Applied Physics · Physics 2025-01-28 Krzysztof K. Dudek , Muamer Kadic , Corentin Coulais , Katia Bertoldi

Mechanism - collections of rigid elements coupled by perfect hinges which exhibit a zero-energy motion -- motivate the design of a variety of mechanical metamaterials. We significantly enlarge this design space by considering…

Soft Condensed Matter · Physics 2021-06-23 Nitin Singh , Martin van Hecke

Metamaterials are artificially engineered devices that go beyond the properties of conventional materials in nature. Metamaterials allow the creation of negative refractive indexes, light trapping with epsilon-near-zero compounds, bandgap…

Optics · Physics 2022-02-01 Antonio Alex-Amor , Angel Palomares-Caballero , Carlos Molero

The recent decades have seen various attempts at accelerating the process of developing materials targeted towards specific applications. The performance required for a particular application leads to the choice of a particular material…

Machine learning models can assist with metamaterials design by approximating computationally expensive simulators or solving inverse design problems. However, past work has usually relied on black box deep neural networks, whose reasoning…

Machine Learning · Computer Science 2022-10-04 Zhi Chen , Alexander Ogren , Chiara Daraio , L. Catherine Brinson , Cynthia Rudin

Mechanical cloaks are materials engineered to manipulate the elastic response around objects to make them indistinguishable from their homogeneous surroundings. Typically, methods based on material-parameter transformations are used to…

Applied Physics · Physics 2022-04-27 Liwei Wang , Jagannadh Boddapati , Ke Liu , Ping Zhu , Chiara Daraio , Wei Chen

Within a decade of fruitful developments, metamaterials became a prominent area of research, bridging theoretical and applied electrodynamics, electrical engineering and material science. Being man-made structures, metamaterials offer a…

The increasing demands of sustainable energy, electronics, and biomedical applications call for next-generation functional materials with unprecedented properties. Of particular interest are emerging materials that display exceptional…

Metamaterials are a new generation of advanced materials, exhibiting engineered microstructures that enable customized material properties not found in nature. The dynamics of metamaterials are particularly fascinating, promising the…

Applied Physics · Physics 2025-07-03 Charles Dorn , Vignesh Kannan , Ute Drechsler , Dennis M. Kochmann

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

Dielectric structures composed of many inclusions that manipulate light in ways the bulk materials cannot are commonly seen in the field of metamaterials. In these structures, each inclusion depends on a set of parameters such as location…

Computational Physics · Physics 2019-03-05 Boaz Blankrot , Clemens Heitzinger

From self-assembly and protein folding to combinatorial metamaterials, a key challenge in material design is finding the right combination of interacting building blocks that yield targeted properties. Such structures are fiendishly…

Soft Condensed Matter · Physics 2025-06-26 Ryan van Mastrigt , Marjolein Dijkstra , Martin van Hecke , Corentin Coulais

Mechanical metamaterials utilize intricate architectural designs to achieve advanced properties beyond those of their bulk counterparts. Existing metamaterial designs often rely on design inspirations and extensive experimental and…

In this paper, we present a unit cell showing a band-gap in the lower acoustic domain. The corresponding metamaterial is made up of a periodic arrangement of this unit cell. We rigorously show that the relaxed micromorphic model can be used…

Applied Physics · Physics 2022-09-07 F. Demore , G. Rizzi , M. Collet , P. Neff , A. Madeo

Metamaterials are artificial composite structures designed for controlling waves or fields, and exhibit interaction phenomena that are unexpected on the basis of their chemical constituents. These phenomena are encoded in effective material…

Materials Science · Physics 2015-12-21 Mihai Caleap , Bruce W Drinkwater

Metamaterials are artificial structures which have recently enabled the realization of novel electromagnetic components with engineered and even unnatural functionalities. Existing metamaterials are specifically designed for a single…

Emerging Technologies · Computer Science 2018-06-19 S. Abadal , C. Liaskos , A. Tsioliaridou , S. Ioannidis , A. Pitsillides , J. Solé-Pareta , E. Alarcón , A. Cabellos-Aparicio

Metamaterials are artificially engineered structures that manipulate electromagnetic waves, having optical properties absent in natural materials. Recently, machine learning for the inverse design of metamaterials has drawn attention.…

The optimization of composition and processing to obtain materials that exhibit desirable characteristics has historically relied on a combination of scientist intuition, trial and error, and luck. We propose a methodology that can…

Machine Learning · Statistics 2017-07-20 Julia Ling , Max Hutchinson , Erin Antono , Sean Paradiso , Bryce Meredig
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