Machine learning (ML), as an advanced data analysis tool, simulates the learning process of
the human brain, enabling the extraction of features, discovery of patterns, and making …

This paper introduces a novel locally resonant hierarchical hexachiral acoustic metamaterial
(HAM) with double-negative characteristics, aimed at achieving broad low-frequency bands …

Acoustic metamaterials exhibit significant potential in mitigating low-frequency vibration.
However, current efficient and customized design strategies remain inadequate. To address …

Acoustic black hole configuration (ABH) design is a type of technique for passive structural
vibration control, by utilizing local inhomogeneities, such as gradual variations of cross …

A deep-learning-based generative design method is proposed to improve the frequency-
dependent characteristics of a reactive silencer, and it has been validated both numerically …

Engineering applications concurrently face challenges related to vibration, impact, load-
bearing and energy absorption. Here, an arch-honeycomb metamaterial with split-ring …

This study innovatively integrates machine learning with intelligent tunable materials to
propose an inverse design strategy for customized bandgap design to regulate vibration …

Elastic metastructures have attracted extensive research interest for their unique properties
of generating bandgaps to mitigate vibration. However, it is difficult for conventional …

Multifunctional materials attract extensive attention for simultaneously satisfying diverse
engineering applications, such as protection against mechanical and vibratory intrusions …