Inverse design of phononic meta-structured materials

Hao Wen Dong*, Chen Shen, Ze Liu, Sheng Dong Zhao, Zhiwen Ren, Chen Xu Liu, Xudong He, Steven A. Cummer, Yue Sheng Wang, Daining Fang, Li Cheng

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

4 Citations (Scopus)

Abstract

Flexible manipulation of elastic and acoustic waves through phononic meta-structured materials (PMSMs) has attracted a lot of attention in the last three decades and shows a bright future for potential applications in many fields. Conventional engineering design methods for PMSMs rely on changing the material composition and empirical structural configurations, which often result in limited performance due to the limited design space. Recent advances in the fields of additive manufacturing, optimization, and artificial intelligence have given rise to a plethora of creative meta-structured materials that offer superior functionality on demand. In this Review, we provide an overview of inverse design of phononic crystals, phononic-crystal devices, phononic metamaterials, phononic-metamaterial devices, phononic metasurfaces, and phononic topological insulators. We first introduce fundamental wave quantities including dispersion relations, scattering characterizations, and dynamic effective parameters, and then discuss how these wave quantities can be leveraged for systematic inverse design of PMSMs to achieve a variety of customized phononic functionalities with highly customizable full-wave responses, intrinsic physical parameters, and hybrid local–global responses. Furthermore, we show representative applications of some inverse-designed PMSMs and look at future directions. We outline the concept of phononic structures genome engineering (PSGE) through key developments in PMSM inverse design. Finally, we discuss the new possibilities that PSGE brings to wave engineering.

Original languageEnglish
Pages (from-to)824-855
Number of pages32
JournalMaterials Today
Volume80
DOIs
Publication statusPublished - Nov 2024

Keywords

  • Elastic/Acoustic waves
  • Machine learning
  • Meta-structured materials
  • Phononic structures genome engineering
  • Topology optimization

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