A machine learning-based method to design modular metamaterials

Wu, Lingling; Liu, Lei; Wang, Yong; Zhai, Zirui; Zhuang, Houlong; Krishnaraju, Deepakshyam; Wang, Qianxuan; Jiang, Hanqing

doi:10.1016/j.eml.2020.100657

Cited by 74 publications

(26 citation statements)

References 55 publications

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“…Likewise, a recent study by Wu et al. [ 469 ] put forward the design of a modular metamaterial shown in Figure 11e, which was made possible by combining neural networks for the band structure calculation and genetic algorithms for the optimization, as illustrated. This allows them to realize on‐demand wide and tunable BGs.…”

Section: Bg Engineering Through Inverse Designmentioning

confidence: 99%

“…This was made possible here by taking advantage of neural networks for both the eigenvalue problem (i.e., to calculate the dispersion behavior [443,468] ) as well as the optimization step. Likewise, a recent study by Wu et al [469] put forward the design of a modular metamaterial shown in Figure 11e, which was made possible by combining neural networks for the band structure calculation and genetic algorithms for the optimization, as illustrated. This allows them to realize on-demand wide and tunable BGs.…”

Section: Bg Engineering Through Inverse Designmentioning

confidence: 99%

mentioning

confidence: 99%

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Tailoring Structure‐Borne Sound through Bandgap Engineering in Phononic Crystals and Metamaterials: A Comprehensive Review

Oudich

Gerard

Deng

et al. 2022

Adv Funct Materials

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In solid state physics, a bandgap (BG) refers to a range of energies where no electronic states can exist. This concept was extended to classical waves, spawning the entire fields of photonic and phononic crystals where BGs are frequency (or wavelength) intervals where wave propagation is prohibited. For elastic waves, BGs are found in periodically alternating mechanical properties (i.e., stiffness and density). This gives birth to phononic crystals and later elastic metamaterials that have enabled unprecedented functionalities for a wide range of applications. Planar metamaterials are built for vibration shielding, while a myriad of works focus on integrating phononic crystals in microsystems for filtering, waveguiding, and dynamical strain energy confinement in optomechanical systems. Furthermore, the past decade has witnessed the rise of topological insulators, which leads to the creation of elastodynamic analogs of topological insulators for robust manipulation of mechanical waves. Meanwhile, additive manufacturing has enabled the realization of 3D architected elastic metamaterials, which extends their functionalities. This review aims to comprehensively delineate the rich physical background and the state-of-the art in elastic metamaterials and phononic crystals that possess engineered BGs for different functionalities and applications, and to provide a roadmap for future directions of these manmade materials.

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Section: Bg Engineering Through Inverse Designmentioning

confidence: 99%

Section: Bg Engineering Through Inverse Designmentioning

confidence: 99%

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Tailoring Structure‐Borne Sound through Bandgap Engineering in Phononic Crystals and Metamaterials: A Comprehensive Review

Oudich

Gerard

Deng

et al. 2022

Adv Funct Materials

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“…Recently, machine learning algorithms have shown exceptional performance in learning complicated relationships between high-dimensional inputs and outputs. Specifically, by leveraging the fast prediction of neural networks (NNs), previous works designing the optimized microstructure or shape for various engineering structures, such as composites, adhesive pillars, and metamaterials [23][24][25][26][27] need only consider a few initial designs out of an infinitely large design space.…”

Section: Introductionmentioning

confidence: 99%

Generative machine learning algorithm for lattice structures with superior mechanical properties

Lee

Zhang

2022

Mater. Horiz.

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“…For instance Lu et al 17 developed gradient based optimization technique to maximize the solid-to-void ratio of 3-D phononic structure in order to achieve ultrawide BGs. Recently, artificial intelligence based machine learning and deep learning data-driven methods have also caught enormous attention of phononic community for metamaterial physical structure and mechanical characteristics optimization 26 , 27 . For instance, Chan et al 26 developed a METASET to explore different two-dimensional and three-dimensional shape and property space to optimize the structure of mechanical metamaterials.…”

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confidence: 99%

Phononic metastructures with ultrawide low frequency three-dimensional bandgaps as broadband low frequency filter

Muhammad

Lim

2021

Sci Rep

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Vibration and noise control are among the classical engineering problems that still draw extensive research interest today. Multiple active and passive control techniques to resolve these problems have been reported, however, the challenges remain substantial. The recent surge of research activities on acoustic metamaterials for vibration and noise control are testimony to the fact that acoustic metamaterial is no longer limited to pure theoretical concepts. For vibration and noise control over an ultrawide frequency region, 3-D metastructures emerge as a novel solution tool to resolve this problem. In that context, the present study reports a novel proposal for 3-D monolithic phononic metastructures with the capability to induce low frequency ultrawide three-dimensional bandgaps with relative bandwidth enhancements of 157.6% and 160.1%. The proposed monolithic metastructure designs consist of elastic frame assembly that is connected with the rigid cylindrical masses. Such structural configuration mimics monoatomic mass-spring chain where an elastic spring is connected with a rigid mass. We develop an analytical model based on monoatomic mass-spring chain to determine the acoustic mode frequency responsible for opening the bandgap. The wave dispersion study reveals the presence of ultrawide bandgaps for both types of metastructures. The modal analysis shows distribution of vibration energy in the bandgap opening (global resonant mode) and closing (local resonant mode) bounding edges. We further analyze the band structures and discuss the physical concepts that govern such ultrawide bandgap. Vibration attenuation inside the bandgap frequency range is demonstrated by frequency response studies conducted by two different finite element models. Thanks to additive manufacturing technology, 3-D prototypes are prepared and low amplitude vibration test is performed to validate the numerical findings. Experimental results show the presence of an ultrawide vibration attenuation zone that spreads over a broadband frequency spectrum. The bandgaps reported by the proposed metastructures are scale and material independent. The research methodology, modelling and design strategy presented here may pave the way for the development of novel meta-devices to control vibration and noises over a broadband frequency range.

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A machine learning-based method to design modular metamaterials

Cited by 74 publications

References 55 publications

Tailoring Structure‐Borne Sound through Bandgap Engineering in Phononic Crystals and Metamaterials: A Comprehensive Review

Tailoring Structure‐Borne Sound through Bandgap Engineering in Phononic Crystals and Metamaterials: A Comprehensive Review

Generative machine learning algorithm for lattice structures with superior mechanical properties

Phononic metastructures with ultrawide low frequency three-dimensional bandgaps as broadband low frequency filter

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