Results 121 to 130 of about 10,498 (267)

Machine Learning‐Assisted Design and Performance Prediction of a Compact Dual‐Band Polarization‐Insensitive THz Metamaterial Absorber for Skin‐Cancer‐Related Refractive‐Index Sensing

Advanced Electronic Materials, EarlyView.
A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun, S. M. Rifatur Rana, Md. Golam Morshed, Imrose Jahan, F. A. Sabbir Ahamed, Md. Jahedul Islam   +5 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Computing and Communications for the Software-Defined Metamaterial Paradigm: A Context Analysis

IEEE Access, 2017
Metamaterials are artificial structures that have recently enabled the realization of novel electromagnetic components with engineered and even unnatural functionalities.
Sergi Abadal, Christos Liaskos, Ageliki Tsioliaridou, Sotiris Ioannidis, Andreas Pitsillides, Josep Sole-Pareta, Eduard Alarcon, Albert Cabellos-Aparicio   +7 more
doaj   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
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, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
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, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Design of Metamaterials for Absorbers Based on Variational Autoencoder

IEEE Access
Metamaterials have experienced rapid development in recent years. Absorbers made of metamaterials play a crucial role in electromagnetic applications and other fields.
Qi Li, Jianwei Wang, Tao Lei, Tianyu Xiang, Chanchan Qin, Maoze Yang   +5 more
doaj   +1 more source

Low-loss negative index metamaterials for X, Ku, and K microwave bands

AIP Advances, 2015
Low-loss, negative-index of refraction metamaterials were designed and tested for X, Ku, and K microwave frequency bands. An S-shaped, split-ring resonator was used as a unit cell to design homogeneous slabs of negative-index metamaterials.
David A. Lee, L. James Vedral, David A. Smith, Randall L. Musselman, Anatoliy O. Pinchuk   +4 more
doaj   +1 more source

1D chirality in all-photodesigned THz metamaterials

, 2017
We suggest that all-photodesigned metamaterials, sub-wavelength custom patterns of photoexcited carriers on a semiconductor, can display an exotic extrinsic electromagnetic chirality in terahertz (THz) frequency range.
Prati, F., Brambilla, M., C. Rizza, M. Brambilla, A. Ciattoni, Massimo Brambilla, Rizza, C., L. Columbo, F. Prati, Lorenzo Columbo, Columbo, L., Franco Prati, Ciattoni, A.   +12 more
core   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
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

Fano-resonant metamaterials and their applications

Nanophotonics, 2013
New developments in the field of Fano-resonant plasmonic metamaterials are reviewed. The emphasis is on the applications of such artificial electromagnetic materials to a variety of technologically important areas: solar energy harvesting and conversion,
Khanikaev Alexander B., Wu Chihhui, Shvets Gennady   +2 more
doaj   +1 more source