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Metamaterials are constructed such that, for a narrow range of frequencies, the momentum density depends on the local displacement gradient, and the stress depends on the local velocity. In these models the momentum density generally…

Mathematical Physics · Physics 2009-11-13 Graeme W. Milton

Mechanical metamaterials owe their extraordinary properties and functionalities to their micro-/nanoscale design of which shape, including both geometry and topology, is perhaps the most important aspect. 4D printing enables programmed,…

Soft Condensed Matter · Physics 2021-05-25 Amir A. Zadpoor

Mechanical metamaterials -- structures with unusual properties that emerge from their internal architecture -- that are designed to undergo large deformations typically exploit large internal rotations, and therefore, necessitate the…

Soft Condensed Matter · Physics 2024-08-30 A. S. Meeussen , G. Bordiga , A. X. Chang , B. Spoettling , K. P. Becker , L. Mahadevan , K. Bertoldi

High-throughput computational and experimental design of materials aided by machine learning have become an increasingly important field in material science. This area of research has emerged in leaps and bounds in the thermal sciences, in…

Materials Science · Physics 2019-06-17 Hang Zhang , Kedar Hippalgaonkar , Tonio Buonassisi , Ole M. Løvvik , Espen Sagvolden , Ding Ding

High-throughput data generation methods and machine learning (ML) algorithms have given rise to a new era of computational materials science by learning relationships among composition, structure, and properties and by exploiting such…

The design of intelligent materials often draws parallels with the complex adaptive behaviors of biological organisms, where robust functionality stems from sophisticated hierarchical organization and emergent long-distance coordination…

Soft Condensed Matter · Physics 2025-11-13 Vladimir A. Baulin , Rudolf M. Füchslin , Achille Giacometti , Helmut Hauser , Marco Werner

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

This article reviews recent inverse statistical-mechanical methodologies that we have devised to optimize interaction potentials in soft matter systems that correspond to stable "target" structures. We are interested in finding the…

Soft Condensed Matter · Physics 2008-11-05 Salvatore Torquato

This paper reviews recent advances in the field of metallic glasses, focusing on the development of novel experimental techniques and in silico models. We discuss progress in experimental characterization, additive manufacturing, multiscale…

Designing functional materials requires a deep search through multidimensional spaces for system parameters that yield desirable material properties. For cases where conventional parameter sweeps or trial-and-error sampling are impractical,…

Materials Science · Physics 2022-03-22 Sanket Kadulkar , Zachary M. Sherman , Venkat Ganesan , Thomas M. Truskett

Metamaterials are composed of periodic subwavelength metal/dielectric structures that resonantly couple to the electric and/or magnetic components of the incident electromagnetic fields, exhibiting properties that are not found in nature.…

Optics · Physics 2016-11-29 Hou-Tong Chen , Antoinette J Taylor , Nanfang Yu

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

Predicting the structural response of advanced multiphase alloys and understanding the underlying microscopic mechanisms that are responsible for it are two critically important roles modeling plays in alloy development. An alloys…

In simulations, particles are traditionally treated as rigid platforms with variable sizes, shapes and interaction parameters. While this representation is applicable for rigid core platforms, particles consisting of soft platforms (e.g.…

Soft Condensed Matter · Physics 2024-08-06 Massimiliano Paesani , Ioana M. Ilie

The complexity of condensed matter arises from emergent behaviors that cannot be understood by analyzing individual constituents in isolation. While traditional condensed-matter approaches-developed primarily for ideal crystalline…

Materials Science · Physics 2025-09-30 Elisabetta Nocerino

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution,…

Materials Science · Physics 2023-09-27 Sue Sin Chong , Yi Sheng Ng , Hui-Qiong Wang , Jin-Cheng Zheng

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-be-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has…

Machine Learning · Computer Science 2024-07-26 Mohammad Karimzadeh , Deekshith Basvoju , Aleksandar Vakanski , Indrajit Charit , Fei Xu , Xinchang Zhang

Architected materials can achieve enhanced properties compared to their plain counterparts. Specific architecting serves as a powerful design lever to achieve targeted behavior without changing the base material. Thus, the connection…

Materials Science · Physics 2023-02-14 Andrew J. Lew , Kai Jin , Markus J. Buehler

Metal additive manufacturing enables unprecedented design freedom and the production of customized, complex components. However, the rapid melting and solidification dynamics inherent to metal AM processes generate heterogeneous,…

Machine Learning · Computer Science 2025-05-05 D. Patel , R. Sharma , Y. B. Guo

Predicting mechanical properties in metal additive manufacturing (MAM) is essential for ensuring the performance and reliability of printed parts, as well as their suitability for specific applications. However, conducting experiments to…

Machine Learning · Computer Science 2024-11-01 Parand Akbari , Masoud Zamani , Amir Mostafaei