Starting from the seminal works of Toupin, Mindlin and Germain, a wide class of generalized
elastic models have been proposed via the principle of virtual work, by postulating …

Abstract Machine learning (ML) has recently enabled many modeling tasks in design,
manufacturing, and condition monitoring due to its unparalleled learning ability using …

This paper introduces a novel machine learning-based optimization strategy for multi-
functional acoustic black hole (ABH) metaplates. The primary objective is to achieve a multi …

Metamaterials are widely studied for their ability to carry human designs and realize exotic,
specific physical properties. However, the existing metamaterial design methods are highly …

Multifunctional metamaterials (MMM) bear promise as next‐generation material platforms
supporting miniaturization and customization. Despite many proof‐of‐concept …

In a deep-learning-based algorithm, generative adversarial networks can generate images
similar to an input. Using this algorithm, an artificial three-dimensional (3D) microstructure …

Abstract Machine intelligence continues to rise in popularity as an aid to the design and
discovery of novel metamaterials. The properties of metamaterials are essentially …

Dynamic control of terahertz metamaterials using thin organic perovskite active layers has
been extensively researched. However, the preparation of organic perovskite devices …

The use of metamaterials in various devices has revolutionized applications in optics,
healthcare, acoustics, and power systems. Advancements in these fields demand novel or …

Generative machine learning models have shown notable success in identifying
architectures for metamaterials—materials whose behavior is determined primarily by their …