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Metamaterials, synthetic materials with customized properties, have emerged as a promising field due to advancements in additive manufacturing. These materials derive unique mechanical properties from their internal lattice structures,…

Artificial Intelligence · Computer Science 2024-10-01 Jaewan Park , Shashank Kushwaha , Junyan He , Seid Koric , Qibang Liu , Iwona Jasiuk , Diab Abueidda

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.…

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

In this paper, we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually…

Machine Learning · Computer Science 2023-06-14 Nikolaos N. Vlassis , WaiChing Sun

The design of metamaterials which support unique optical responses is the basis for most thin-film nanophotonics applications. In practice this inverse design problem can be difficult to solve systematically due to the large design…

Computational Physics · Physics 2026-05-25 Andrew Lininger , Michael Hinczewski , Giuseppe Strangi

Harnessing the rich nonlinear dynamics of highly-deformable materials has the potential to unlock the next generation of functional smart materials and devices. However, unlocking such potential requires effective strategies to spatially…

Disordered metamaterials are promising for programming physical properties across diverse applications, yet their inverse design remains challenging due to the non-intuitive structure-property relationships and large design spaces. Recent…

Computational Engineering, Finance, and Science · Computer Science 2026-03-18 Ziyuan Xie , Weipeng Xu , Dazhi Zhao , Wenchang Zhang , Daoyang Dong , Bingbing Xu , Ning Liu , Sheng Mao , Tianju Xue

Deep generative models, particularly denoising diffusion models, have achieved remarkable success in high-fidelity generation of architected microstructures with desired properties and styles. Nevertheless, these recent methods typically…

Computational Engineering, Finance, and Science · Computer Science 2026-01-13 Weipeng Xu , Ziyuan Xie , Haoju Lin , Xinyu Wang , Guangjin Mou , Tianju Xue

Disordered (amorphous) materials, such as glasses, are emerging as promising candidates for applications within energy storage, nonlinear optics, and catalysis. Their lack of long-range order and complex short- and medium-range orderings,…

Materials Science · Physics 2025-09-18 Jonas A. Finkler , Yan Lin , Tao Du , Jilin Hu , Morten M. Smedskjaer

Programmable structures are systems whose undeformed geometries and material property distributions are deliberately designed to achieve prescribed deformed configurations under specific loading conditions. Inflatable structures are a…

Computational Engineering, Finance, and Science · Computer Science 2025-08-19 Sara Karimi , Nikolaos N. Vlassis

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…

Multishape metamaterials exhibit more than one target shape change, e.g. the same metamaterial can have either a positive or negative Poisson's ratio. So far, multishape metamaterials have mostly been obtained by trial-and-error. The…

Soft Condensed Matter · Physics 2023-04-25 David M. J. Dykstra , Corentin Coulais

Practical applications of mechanical metamaterials often involve solving inverse problems where the objective is to find the (multiple) microarchitectures that give rise to a given set of properties. The limited resolution of additive…

Metasurfaces are ultra-thin optical elements composed of engineered sub-wavelength structures that enable precise control of light. Their inverse design - determining a geometry that yields a desired optical response - is challenging due to…

Optics · Physics 2025-06-30 Liav Hen , Erez Yosef , Dan Raviv , Raja Giryes , Jacob Scheuer

The inverse design of metamaterial architectures presents a significant challenge, particularly for nonlinear mechanical properties involving large deformations, buckling, contact, and plasticity. Traditional methods, such as gradient-based…

Computational Physics · Physics 2025-05-29 Qibang Liu , Seid Koric , Diab Abueidda , Hadi Meidani , Philippe Geubelle

Spinodal metamaterials, with architectures inspired by natural phase-separation processes, have presented a significant alternative to periodic and symmetric morphologies when designing mechanical metamaterials with extreme performance.…

Computational Engineering, Finance, and Science · Computer Science 2025-01-10 Prakash Thakolkaran , Michael A. Espinal , Somayajulu Dhulipala , Siddhant Kumar , Carlos M. Portela

Composite materials often exhibit mechanical anisotropy owing to the material properties or geometrical configurations of the microstructure. This makes their inverse design a two-fold problem. First, we must learn the type and orientation…

Computational Engineering, Finance, and Science · Computer Science 2024-12-19 Asghar A. Jadoon , Karl A. Kalina , Manuel K. Rausch , Reese Jones , Jan N. Fuhg

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

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…

Diffusion models promise to accelerate material design by directly generating novel structures with desired properties, but existing approaches typically require expensive and substantial labeled data ($>$10,000) and lack adaptability. Here…

Chemical Physics · Physics 2025-11-06 Junwu Chen , Jeff Guo , Edvin Fako , Philippe Schwaller
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