Results 81 to 90 of about 13,645 (194)
Nuclear mechanical properties are inherently scale‐dependent, arising from a hierarchical architecture that spans DNA, chromatin, the nuclear envelope, and condensates. Experimental techniques and theoretical models are integrated into a cohesive multiscale framework linking nanoscale structural features to organelle‐level mechanical behavior.
Xinran Liu +15 more
wiley +1 more source
Highly-anisotropic elements for acoustic pentamode applications
Pentamode metamaterials are a class of acoustic metafluids that are characterized by a divergence free modified stress tensor. Such materials have an unconventional anisotropic stiffness and isotropic mass density, which allow themselves to mimic other ...
Calvo, David C. +4 more
core +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Double-negative acoustic metamaterials [PDF]
The aim of this paper is to provide a mathematical theory for understanding the mechanism behind the double-negative refractive index phenomenon in bubbly fluids. The design of double-negative metamaterials generally requires the use of two different kinds of subwavelength resonators, which may limits the applicability of double-negative metamaterials.
Ammari, Habib +4 more
openaire +3 more sources
Low-frequency attenuation signal absorption performance of thin-film acoustic metamaterials
Considering that thin film acoustic metamaterials have many special properties that natural materials and traditional materials do not possess, the low-frequency attenuation signal absorption performance of thin film acoustic metamaterials is studied ...
Xu Jingcheng, Chen Changzheng
doaj +1 more source
Evolution of Physical Intelligence Across Scales
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley +1 more source
Much effort has been made to experimentally fabricate acoustic metamaterials that display novel properties, such as single or double negativity, negative refractive index.
Lirong LU +5 more
doaj +1 more source
Theoretical Optimization of Trapped-Bubble-Based Acoustic Metamaterial Performance
Acoustic metamaterials have proven to be a versatile tool for the precise control and manipulation of sound waves. One of the promising designs of acoustic metamaterials employ the arrays of bubbles and find applications for soundproofing, blast ...
Dmitry Gritsenko, Roberto Paoli
doaj +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source

