Data‐Driven Design for Metamaterials and Multiscale Systems: A Review
Abstract: Metamaterials are artificial materials designed to exhibit effective material parameters that go beyond those found in nature. Composed of unit cells with rich designability that are assembled into multiscale systems, they hold great promise for realizing next‐generation devices with exceptional, often exotic, functionalities. However, the vast design space and intricate structure–property relationships pose significant challenges in their design. A compelling paradigm that could bring the full potential of metamaterials to fruition is emerging: data‐driven design. This review provides a holistic overview of this rapidly evolving field, emphasizing the general methodology instead of specific domains and deployment contexts. Existing research is organized into data‐driven modules, encompassing data acquisition, machine learning‐based unit cell design, and data‐driven multiscale optimization. The approaches are further categorized within each module based on shared principles, analyze and compare strengths and applicability, explore connections between different modules, and identify open research questions and opportunities.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Data‐Driven Design for Metamaterials and Multiscale Systems: A Review ; day:05 ; month:12 ; year:2023 ; extent:45
Advanced materials ; (05.12.2023) (gesamt 45)
- Urheber
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Lee, Doksoo
Chen, Wei (Wayne)
Wang, Liwei
Chan, Yu‐Chin
Chen, Wei
- DOI
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10.1002/adma.202305254
- URN
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urn:nbn:de:101:1-2023120614224184643421
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:37 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Lee, Doksoo
- Chen, Wei (Wayne)
- Wang, Liwei
- Chan, Yu‐Chin
- Chen, Wei
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