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Metadamping is the phenomenon of either enhanced or diminished intrinsic dissipation in a material stemming from the material's internal structural dynamics. It has been previously shown that a locally resonant elastic metamaterial may be…

Applied Physics · Physics 2023-12-19 Mahmoud I. Hussein , Ibrahim Patrick , Arnab Banerjee , Sondipon Adhikari

Metasurfaces are ultrathin, engineered materials composed of nanostructures that manipulate light in ways unattainable by natural materials. Recent advances have leveraged computational optimization, machine learning, and deep learning to…

Optics · Physics 2025-08-08 Hao Li , Andrey Bogdanov

Metamaterials can enable peculiar static and dynamic behavior (such as negative effective mass density, dynamical stiffness, and Poisson's ratio) due to their geometry rather than their chemical composition. The geometry of these…

Soft Condensed Matter · Physics 2022-01-03 Audrey A. Watkins , Austin Eichelberg , Osama R. Bilal

The elastic wave propagation is investigated in the beam lattice material characterized by a square periodic cell with anti-tetrachiral microstructure. With reference to the Floquet-Bloch spectrum, focus is made on the band structure…

Materials Science · Physics 2016-08-04 Andrea Bacigalupo , Giorgio Gnecco , Marco Lepidi , Luigi Gambarotta

Digital stiffness programmability is fulfilled with a heterogeneous mechanical metamaterial. The prototype consists of an elastomer matrix containing tessellations of diamond shaped cavities selectively confined with semi-rigid plastic beam…

Soft Condensed Matter · Physics 2021-08-13 H. Tao , F. Danzi , C. E. Silva , J. M. Gibert

Slowing down, stopping, and reversing a signal is a core functionality for information processing. Here, we show that this functionality can be realized by tuning the dispersion of a periodic system through a dispersionless, or flat, band.…

Soft Condensed Matter · Physics 2021-04-08 Pragalv Karki , Jayson Paulose

We propose a unified deep meta-learning framework for accelerated magnetic resonance imaging (MRI) that jointly addresses multi-coil reconstruction and cross-modality synthesis. Motivated by the limitations of conventional methods in…

Optimization and Control · Mathematics 2026-03-10 Merham Fouladvand , Peuroly Batra

Material responses to static and dynamic stimuli, represented as nonlinear curves, are design targets for engineering functionalities like structural support, impact protection, and acoustic and photonic bandgaps. Three-dimensional…

Mechanical metamaterials composed of bistable elements have recently emerged as promising platforms for mechanical memory. Traditional approaches to writing information in these systems typically rely on localized actuation or predefined…

Applied Physics · Physics 2025-08-29 Audrey A. Watkins , Giovanni Bordiga , Mingxing Mu , Vincent Tournat , Katia Bertoldi

In this paper, we present the design and experimental validation of a labyrinthine metamaterial for vibro-acoustic applications. Based on a 2D unit cell, different designs of finite-size metamaterial specimens in a sandwich configuration…

Shape-morphing metamaterials enable adaptive structures capable of complex functional deformations, with applications ranging from reconfigurable structures and soft robotics to medical devices. However, their design remains challenging due…

Computational Engineering, Finance, and Science · Computer Science 2026-05-11 Jipeng Cui , Wei "Wayne" Chen

The inverse design of microstructures plays a pivotal role in optimizing metamaterials with specific, targeted physical properties. While traditional forward design methods are constrained by their inability to explore the vast…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Tianyang Xue , Haochen Li , Longdu Liu , Paul Henderson , Pengbin Tang , Lin Lu , Jikai Liu , Haisen Zhao , Hao Peng , Bernd Bickel

Conventional meta-atom designs rely heavily on researchers' prior knowledge and trial-and-error searches using full-wave simulations, resulting in time-consuming and inefficient processes. Inverse design methods based on optimization…

Machine Learning · Computer Science 2023-12-11 Zezhou Zhang , Chuanchuan Yang , Yifeng Qin , Hao Feng , Jiqiang Feng , Hongbin Li

The dispersive wave propagation in a periodic metamaterial with tetrachiral topology and inertial local resonators is investigated. The Floquet-Bloch spectrum of the metamaterial is compared with that of the tetrachiral beam lattice…

Materials Science · Physics 2016-05-24 Andrea Bacigalupo , Giorgio Gnecco , Marco Lepidi , Luigi Gambarotta

This work introduces a surrogate-based model for efficiently estimating the frequency response of dynamic mechanical metamaterials, particularly when dealing with large parametric perturbations and aperiodic substructures. The research…

Computational Engineering, Finance, and Science · Computer Science 2025-11-06 J. Pereira , R. O. Ruiz

In this work, perfectly-matched metamaterials (PMMs) are described and combined with inverse design to realize broadband devices. PMMs are discretized metamaterials with anisotropic unit cells selected from a constrained design space,…

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

By designing tailor-made resonance modes with structured atoms, metamaterials allow us to obtain constitutive parameters outside their limited range from natural or composite materials. Nonetheless, tuning the constitutive parameters relies…

Applied Physics · Physics 2021-06-29 Choonlae Cho , Xinhua Wen , Namkyoo Park , Jensen Li

We present an analytical scheme for the design of realistic metagratings for wide-angle engineered reflection. These recently proposed planar structures can reflect an incident plane wave into a prescribed (generally non-specular) angle…

Applied Physics · Physics 2018-06-18 Oshri Rabinovich , Ariel Epstein

Machine learning (ML) is emerging as a transformative tool for the design of architected materials, offering properties that far surpass those achievable through lab-based trial-and-error methods. However, a major challenge in current…