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Mechanical and phononic metamaterials exhibiting negative elastic moduli, gapped vibrational spectra, or topologically protected modes enable precise control of structural and acoustic functionalities. While much progress has been made in…

Materials Science · Physics 2019-09-25 Henrik Ronellenfitsch , Norbert Stoop , Josephine Yu , Aden Forrow , Jörn Dunkel

Models for image representation learning are typically designed for either recognition or generation. Various forms of contrastive learning help models learn to convert images to embeddings that are useful for classification, detection, and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Matthew Gwilliam , Xiao Wang , Xuefeng Hu , Zhenheng Yang

A key challenge in metasurface design is the development of algorithms that can effectively and efficiently produce high performance devices. Design methods based on iterative optimization can push the performance limits of metasurfaces,…

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

Discrete models provide concise descriptions of complex physical phenomena, such as negative refraction, topological insulators, and Anderson localization. While there are multiple tools to obtain discrete models that demonstrate particular…

Materials Science · Physics 2018-07-03 Kathryn H. Matlack , Marc Serra-Garcia , Antonio Palermo , Sebastian D. Huber , Chiara Daraio

Efficient and fast reconstruction of anatomical structures plays a crucial role in clinical practice. Minimizing retrieval and processing times not only potentially enhances swift response and decision-making in critical scenarios but also…

Relying on either deep models or physical models are two mainstream approaches for solving inverse sample reconstruction problems in programmable illumination computational microscopy. Solutions based on physical models possess strong…

Image and Video Processing · Electrical Eng. & Systems 2024-03-21 Ruiqing Sun , Delong Yang , Shaohui Zhang , Qun Hao

Multi-functional materials are increasingly essential in many applications due to their ability to serve multiple purposes, simultaneously. Metamaterials can offer tailored functionality based on carefully designed tessellating basic…

Applied Physics · Physics 2025-06-12 Evan Kluge , Osama R. Bilal

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…

Mechanical metamaterials capable of large deformations are an emerging platform for functional devices and structures across scales. Bistable designs are particularly attractive since they endow a single object with two configurations that…

Soft Condensed Matter · Physics 2024-08-09 Yingchao Peng , Imtiar Niloy , Megan Kam , Paolo Celli , Paul Plucinsky

Photonic metamaterials are man-made structures composed of tailored micro- or nanostructured metallo-dielectric sub-wavelength building blocks that are densely packed into an effective material. This deceptively simple, yet powerful, truly…

Optics · Physics 2015-05-30 Costas M. Soukoulis , Martin Wegener

The behavior of materials is influenced by a wide range of phenomena occurring across various time and length scales. To better understand the impact of microstructure on macroscopic response, multiscale modeling strategies are essential.…

A recently proposed class of materials, called software-defined metamaterials, can change their electromagnetic behavior on demand, utilizing a nanonetwork embedded in their structure. The present work focuses on 2D metamaterials, known as…

Emerging Technologies · Computer Science 2018-01-18 Angeliki Tsioliaridou , Christos Liaskos , Andreas Pitsillides , Sotiris Ioannidis

Model merging has attracted significant attention as a powerful paradigm for model reuse, facilitating the integration of task-specific models into a singular, versatile framework endowed with multifarious capabilities. Previous studies,…

Machine Learning · Computer Science 2025-01-03 Zhengqi Xu , Han Zheng , Jie Song , Li Sun , Mingli Song

This paper investigates the influence of interfaces on the performance of finite-sized mechanical metamaterial structures for vibration damping applications. The metamaterial structures are designed in a sandwich configuration in which two…

Applied Physics · Physics 2026-04-30 Svenja Hermann , Kévin Billon , Manuel Collet , Angela Madeo

Mechanical metamaterial is a synthetic material that can possess extraordinary physical characteristics, such as abnormal elasticity, stiffness, and stability, by carefully designing its internal structure. To make metamaterials contain…

Computational Engineering, Finance, and Science · Computer Science 2024-06-11 Yanyan Yang , Lili Wang , Xiaoya Zhai , Kai Chen , Wenming Wu , Yunkai Zhao , Ligang Liu , Xiao-Ming Fu

Deployable structures, essential across various engineering applications ranging from umbrellas to satellites, are evolving to include soft, morphable designs where geometry drives transformation. However, a major challenge for soft…

Recently, metamaterials-inspired diffraction gratings (or metagratings) have demonstrated unprecedented efficiency in wavefront manipulation by means of relatively simple structures. Conventional one-dimensional (1D) gratings have a profile…

Mechanical metamaterials feature engineered microstructures designed to exhibit exotic, and often counter-intuitive, effective behaviour. Such a behaviour is often achieved through instability-induced transformations of the underlying…

Computational Engineering, Finance, and Science · Computer Science 2020-09-04 S. E. H. M. van Bree , O. Rokoš , R. H. J. Peerlings , M. Doškář , M. G. D. Geers

Many real-world data can be represented as heterogeneous graphs with different types of nodes and connections. Heterogeneous graph neural network model aims to embed nodes or subgraphs into low-dimensional vector space for various…

Artificial Intelligence · Computer Science 2024-12-24 Xinjun Cai , Jiaxing Shang , Fei Hao , Dajiang Liu , Linjiang Zheng
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