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Mechanical meta-materials are solids whose geometric structure results in exotic nonlinear behaviors that are not typically achievable via homogeneous materials. We show how to drastically expand the design space of a class of mechanical…

Computational Engineering, Finance, and Science · Computer Science 2024-10-04 Mehran Mirramezani , Anne S. Meeussen , Katia Bertoldi , Peter Orbanz , Ryan P. Adams

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

With the achievement on the additive manufacturing, the mechanical properties of architectured materials can be precisely designed by tailoring microstructures. As one of the primary design objectives, the elastic isotropy is of great…

Applied Physics · Physics 2021-04-15 Anran Wei , Jie Xiong , Weidong Yang , Fenglin Guo

Molecules composed of atoms exhibit properties not inherent to their constituent atoms. Similarly, meta-molecules consisting of multiple meta-atoms possess emerging features that the meta-atoms themselves do not possess. Metasurfaces…

Optics · Physics 2019-07-09 Zhaocheng Liu , Dayu Zhu , Kyu-Tae Lee , Andrew S. Kim , Lakshmi Raju , Wenshan Cai

Crystal structure generation is fundamental to materials science, enabling the discovery of novel materials with desired properties. While existing approaches leverage Large Language Models (LLMs) through extensive fine-tuning on materials…

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

Multiscale techniques have been widely shown to potentially overcome the limitation of homogenization schemes in representing the microscopic failure mechanisms in heterogeneous media as well as their influence on their structural response…

Numerical Analysis · Mathematics 2021-08-10 Fabrizio Greco , Lorenzo Leonetti , Paolo Lonetti , Raimondo Luciano , Andrea Pranno

In nature, most materials are composed of atoms with periodic structures. Hence, it's impossible to introduce topological structures into their lattice compose, because the atoms as basic blocks cannot be modulated. However, the lattice…

Mesoscale and Nanoscale Physics · Physics 2020-10-06 Wenjin Zhang , Ziyuan Meng , Zidong Zhang , Ke Bi , Runhua Fan , Yi Du , Weichang Hao

The mechanical properties of a material are intimately related to its microstructure. This is particularly important for predicting mechanical behavior of polycrystalline metals, where microstructural variations dictate the expected…

Materials Science · Physics 2024-01-23 Yejun Gu , Christopher D. Stiles , Jaafar A. El-Awady

Kernel classifiers and regressors designed for structured data, such as sequences, trees and graphs, have significantly advanced a number of interdisciplinary areas such as computational biology and drug design. Typically, kernels are…

Machine Learning · Computer Science 2020-01-14 Hanjun Dai , Bo Dai , Le Song

Body-Centred Cubic (BCC) lattices with twinned meta-crystal architecture inspired by the strengthening of bulk metals have significantly improved mechanical performance; however, their deformation behaviour and underlying strengthening…

Materials Science · Physics 2025-03-06 David McArthur , PJ Tan , Chu Lun Alex Leung

Building on discoveries in graphene and two-dimensional (2D) transition metal dichalcogenides, van der Waals (VdW) layered heterostructures - stacks of such 2D materials - are being extensively explored with resulting new discoveries of…

Materials Science · Physics 2022-10-20 Nicholas Ng , Tyrel M. McQueen

Leveraging on the underlying low-dimensional structure of data, low-rank and sparse modeling approaches have achieved great success in a wide range of applications. However, in many applications the data can display structures beyond simply…

Machine Learning · Computer Science 2019-12-04 Zhao Kang , Xiao Lu , Yiwei Lu , Chong Peng , Zenglin Xu

We introduce a new measure of the structure of a liquid which is the softness of the mean-field potential developed by us earlier. We find that this softness is sensitive to small changes in the structure. We then study its correlation with…

Soft Condensed Matter · Physics 2021-05-26 Manoj Kumar Nandi , Sarika Maitra Bhattacharyya

Computational methods that automatically extract knowledge from data are critical for enabling data-driven materials science. A reliable identification of lattice symmetry is a crucial first step for materials characterization and…

Materials Science · Physics 2018-07-19 A. Ziletti , D. Kumar , M. Scheffler , L. M. Ghiringhelli

Data-driven methodologies for designing new materials are developing apace, yet advances for organic crystals have been infrequent. For organic crystals, the need to predict solid-state electronic properties from molecular structure alone…

Materials Science · Physics 2022-04-22 Daniel M. Packwood , Yu Kaneko , Daiji Ikeda , Mitsuru Ohno

A numerical study on the elastic response of single- and multi-layer systems formed by alternating pentamode lattices and stiffening plates is presented. Finite element simulations are conducted to analyze the dependence of the effective…

Applied Physics · Physics 2020-01-08 A. Amendola , G. Carpentieri , L. Feo , F. Fraternali

The connection between the properties of cell tissue and those of the single constituent cells remains to be elucidated. At the purely mechanical level, the degree of rigidity of different cellular components, such as the nucleus and the…

Soft Condensed Matter · Physics 2022-03-15 Stefano Villa , Andrea Palamidessi , Emanuela Frittoli , Giorgio Scita , Roberto Cerbino , Fabio Giavazzi

Understanding structure-property relationships in complex materials requires integrating complementary measurements across multiple length scales. Here we propose an interpretable "multimodal" machine learning framework that unifies…

Materials Science · Physics 2026-02-03 Shun Muroga , Hideaki Nakajima , Taiyo Shimizu , Kazufumi Kobashi , Kenji Hata

Metamaterials are arrangement of basic building blocks that repeat in space, time, or both. These material systems serve as an excellent platform for controlling waves, such as engineering wavenumber band gaps, flat bands, and…

Applied Physics · Physics 2026-01-13 Mohamed A. Elgamal , Osama R. Bilal
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