Design Of Metamaterials Research Articles

Low-frequency bandgap and anomalous refraction of elastic waves in tetra-chiral metamaterial

In this paper, the tetra-chiral metamaterial is proposed. Compared with general materials, tetra-chiral metamaterials exhibit excellent mechanical properties because of their compression-torsion coupling. Based on the finite element method, the mechanism of bandgap generation in tetra-chiral metamaterials is investigated. The effect of the geometrical parameters of the tetra-chiral metamaterial on the bandgaps is discussed. By further design of tetra-chiral structures, the bandgap of hybrid-tetra-chiral metamaterial can realize the wide relative bandwidth, and the frequency of bandgaps can also be reduced significantly. More than that, the anomalous refraction of elastic waves in tetra-chiral metamaterials is also examined by analyzing the iso-frequency curves. The propagation of elastic waves in tetra-chiral metamaterials exhibits self-collimation, birefraction, and negative refraction. This study provides new ideas for the design of low-frequency broadband metamaterials.

Structurally Transformable and Reconfigurable Hydrogel-Based Mechanical Metamaterials and Their Application in Biomedical Stents.

Mechanical metamaterials exhibit several unusual mechanical properties, such as a negative Poisson's ratio, which impart additional capabilities to materials. Recently, hydrogels have emerged as exceptional candidates for fabricating mechanical metamaterials that offer enhanced functionality and expanded applications due to their unique responsive characteristics. However, the adaptability of these metamaterials remains constrained and underutilized, as they lack integration of the hydrogels' soft and responsive characteristics with the metamaterial design. Here, we propose structurally transformable and reconfigurable hydrogel-based mechanical metamaterials through three-dimensional (3D) printing of lattice structures composed of multishape-memory poly(acrylic acid)-chitosan hydrogels. By incorporating reversible shape-memory mechanisms that control the structural arrangements of the lattice, these metamaterials can exhibit transformable and reconfigurable mechanical characteristics under various environmental conditions, including auxetic behavior, with Poisson's ratios switchable from negative to zero or positive. These adaptable mechanical responses across different states arise from structural changes in lattice, surpassing the gradual changes observed in conventional stimuli-responsive materials. The application of these metamaterials in multimode biomedical stents demonstrates their adaptability in practical settings, allowing them to transition between expandable, nonexpandable, and shrinkable states, with corresponding Poisson's ratios. By integrating multishape-memory soft materials with metamaterial design, we can significantly enhance their functionality, advancing the development of smart biomaterials.

A review on mechanical metamaterials and additive manufacturing techniques for biomedical applications

This review presents the design and experimental analysis of metamaterials with tunable properties for biomedical applications.

Optimal design of acoustic metamaterials for noise suppression by the frequency division in military equipment

This paper presents a multi-Helmholtz unit series–parallel acoustic metamaterial with a segmented noise control effect designed by taking advantage of the adjustable frequency band of an acoustic metamaterial, aiming to change the main noise spectrum characteristics under different driving conditions of military equipment such as tanks. Based on the transfer matrix method, a theoretical model that can predict the acoustic characteristics of a hybrid structure with multiple Helmholtz resonator (HR) units is established, and its feasibility is verified through finite element simulations and experiments. By combining particle swarm optimization with finite element simulation, the suboptimal average sound absorption coefficient (αavg) of ten populations was 0.52, 0.54, 0.54, and 0.44, respectively, after iterating for 50 generations. The results demonstrate that the αavg of the four groups of HRs in series with three layers reaches 0.79, 0.62, and 0.66, respectively, at the frequency bands of 205–285, 540–720, and 940–1130 Hz, and the overall thickness of the longest part is 88 mm. Low-frequency noise at approximately λ/18 can be controlled. The HR obtained by means of the first series and then parallel can achieve accurate sound absorption for specific frequency bands and can reduce its volume by removing redundant absorption bands. The findings of this study provide an effective noise-control scheme for changing the noise environment in military equipment.

Electromagnetic metamaterial agent

Metamaterials have revolutionized wave control; in the last two decades, they evolved from passive devices via programmable devices to sensor-endowed self-adaptive devices realizing a user-specified functionality. Although deep-learning techniques play an increasingly important role in metamaterial inverse design, measurement post-processing and end-to-end optimization, their role is ultimately still limited to approximating specific mathematical relations; the metamaterial is still limited to serving as proxy of a human operator, realizing a predefined functionality. Here, we propose and experimentally prototype a paradigm shift toward a metamaterial agent (coined metaAgent) endowed with reasoning and cognitive capabilities enabling the autonomous planning and successful execution of diverse long-horizon tasks, including electromagnetic (EM) field manipulations and interactions with robots and humans. Leveraging recently released foundation models, metaAgent reasons in high-level natural language, acting upon diverse prompts from an evolving complex environment. Specifically, metaAgent’s cerebrum performs high-level task planning in natural language via a multi-agent discussion mechanism, where agents are domain experts in sensing, planning, grounding, and coding. In response to live environmental feedback within a real-world setting emulating an ambient-assisted living context (including human requests in natural language), our metaAgent prototype self-organizes a hierarchy of EM manipulation tasks in conjunction with commanding a robot. metaAgent masters foundational EM manipulation skills related to wireless communications and sensing, and it memorizes and learns from past experience based on human feedback.

Bandgap characteristics analysis and graded design of a novel metamaterial for flexural wave suppression

A novel elastic metamaterial is proposed with the aim of achieving low-frequency broad bandgaps and bandgap regulation. The band structure of the proposed metamaterial is calculated based on the Floquet-Bloch theorem, and the boundary modes of each bandgap are analyzed to understand the effects of each component of the unit cell on the bandgap formation. It is found that the metamaterials with a low elastic modulus of ligaments can generate flexural wave bandgaps below 300 Hz. Multi-frequency vibrations can be suppressed through the selective manipulation of bandgaps. The dual-graded design of metamaterials that can significantly improve the bandgap width is proposed based on parametric studies. A new way that can regulate the bandgap is revealed by studying the graded elastic modulus in the substrate. The results demonstrate that the nonlinear gradient of the elastic modulus in the substrate offers better bandgap performance. Based on these analyses, the proposed elastic metamaterials can pave the way for multi-frequency vibration control, low-frequency bandgap broadening, and bandgap tuning.

Dual metal synergistic modulation of boron nitride for high-temperature wave-transparent metamaterials.

Electromagnetic metamaterials have demonstrated immense potential in the development of novel high-temperature wave-transparent materials, yet the requirements of their intricate structural design and strict stability pose dual challenges, particularly in high-speed radome applications. A strategy involving the synergistic modulation of boron nitride (BN) by dual metallic elements of Ca and Al (0.5Ca-0.5Al-BN) was proposed in this study, which elegantly integrates the advantages of metamaterial-like split ring resonator (SRR) features and h-BN's oxidation resistance enhancement. The highest wave transmittance at room temperature reaches 0.96 at 2-18 GHz. Notably, Al elements play a pivotal dual role in: (1) facilitating the solid solution of Ca to optimize the formation of metamaterial-like structures and (2) generating an amorphous Al2O3 protective layer to preferentially defend against surface oxidation. This further prevents the breakdown of metamaterial characteristics at high temperatures, thereby striking a dual balance between the preservation of metamaterial-like structures and the high temperature stability of BN. Notably, 0.5Ca-0.5Al-BN retains its metamaterial-like characteristics, with a low permittivity not exceeding 2 even after exposure to 1500 °C oxidation. The corresponding wave transmission rate remains above 0.7 in most frequency bands at incidence angles of 0°, 10°, and 30°, ensuring superior wave-transparent properties. Furthermore, 0.5Ca-0.5Al-BN exhibits great hydrophobicity, benefiting resistance to rain and snow erosion. By integrating the merits between fundamental materials and metamaterials, this work transcends the limitations of conventional metamaterial design and offers fresh insights and empirical support for developing high-speed aircraft radome materials.

Terahertz Metamaterials Inspired by Quantum Phenomena.

The study of many phenomena in the terahertz (THz) frequency spectral range has emerged as a promising playground in modern science and technology, with extensive applications in high-speed communication, imaging, sensing, and biosensing. Many THz metamaterial designs explore quantum physics phenomena embedded into a classical framework and exhibiting various unexpected behaviors. For spatial THz waves, the effects inspired by quantum phenomena include electromagnetically induced transparency (EIT), Fano resonance, bound states in the continuum (BICs), and exceptional points (EPs) in non-Hermitian systems. They facilitate the realization of extensive functional metadevices and applications. For on-chip THz waves, quantum physics-inspired topological metamaterials, as photonic analogs of topological insulators, can ensure robust, low-loss propagation with suppressed backscattering. These trends open new pathways for high-speed on-chip data transmission and THz photonic integrated circuits, being crucial for the upcoming 6G and 7G wireless communication technologies. Here, we summarize the underlying principles of quantum physics-inspired metamaterials and highlight the latest advances in their application in the THz frequency band, encompassing both spatial and on-chip metadevice realizations.

3D arc-shaped structure design of compression-twist coupling metamaterial

Abstract Compression-twist coupling (CTC) metamaterials are special mechanical metamaterials that convert axial force into circumferential force. Based on the dislocated re-entrant structure, a novel structure with line-shaped polyline rods is proposed to achieve the CTC effect. To reduce the stress concentration, a corresponding arc-shaped CTC structure is further designed, which is the focus structure of our study. The influence of the geometrical parameters of the arc-shaped structures on the CTC effect is explored through energy-based theoretical analysis, finite element simulation, and validation experiments. Finally, the CTC effects of extended single-side arc-shaped and multi-arc design structures are discussed. Compared with previous designs, the novel structure proposed in this work enhances the design flexibility and achieves a significant CTC effect, which can serve as a reference for the design of new CTC metamaterials.

Design and manufacture of low-frequency acoustic absorption metamaterials with enhanced coupling characteristic

ABSTRACT The current designs of low-frequency acoustic absorption metamaterials suffer from inadequate prediction accuracy and low efficiency. Herein, by integrating impedance theory with artificial neural networks, we propose an optimisation method of unit impedance correction (UIC). Meanwhile, a mutated honeycomb structure with teardrop-shaped apertures (MHSTA) fabricated by stereolithography is proposed, which can enhance the low-frequency coupling performance through rationally arranging the relative positions of the apertures. To verify prediction ability of the UIC method, the 50 mm-thickness typical structures of MHSTA are designed for two low-frequency ranges (220–500 Hz and 230–550 Hz). Compared with the simulation, the UIC result can reach the maximum relative error of 3.9% and the maximum absolute error of 0.033, which ensures the accurate prediction commendably. The experiment also demonstrates that the acoustic absorption coefficients are highly consist with the UIC result. This work provides a novel strategy of precise design for low-frequency acoustic absorption metamaterials.

Mathematical modelling and virtual design of metamaterials for reducing noise and vibration in built-up structures

Noise and vibration pose significant challenges in built-up structures, affecting structural integrity and occupant comfort. Traditional materials often fail to address these issues effectively across all relevant frequencies, particularly in urban and industrial environments. This paper presents a mathematical modeling approach and virtual design framework for developing metamaterials specifically tailored to mitigate noise and vibration in built-up structures. By leveraging finite element analysis, dynamic energy analysis, and optimization algorithms, the study demonstrates how metamaterials can create frequency-specific barriers. Comparative analyses with previous studies, performance metrics, and sensitivity evaluations reveal the robustness and unique contributions of this approach. Validation through simulations and benchmarking confirms the model’s effectiveness, enhancing structural resilience and human comfort in complex environments. Additionally, this study surveys natural metamaterials and the urban environment. The major findings highlight the effectiveness of natural metamaterials (NMs) in ground vibration attenuation, offering diverse applications and proposing a roadmap for developing natural materials for clean and quiet environments

High‐dimensional Bayesian optimization for metamaterial design

AbstractMetamaterial design, encompassing both microstructure topology selection and geometric parameter optimization, constitutes a high‐dimensional optimization problem, with computationally expensive and time‐consuming design evaluations. Bayesian optimization (BO) offers a promising approach for black‐box optimization involved in various material designs, and this work presents several advanced techniques to adapt BO to address the challenges associated with metamaterial design. First, variational autoencoders (VAEs) are employed for efficient dimensionality reduction, mapping complex, high‐dimensional metamaterial microstructures into a compact latent space. Second, mutual information maximization is incorporated into the VAE to enhance the quality of the learned latent space, ensuring that the most relevant features for optimization are retained. Third, trust region‐based Bayesian optimization (TuRBO) dynamically adjusts local search regions, ensuring stability and convergence in high‐dimensional spaces. The proposed techniques are well incorporated with conventional Gaussian processes (GP)‐based BO framework. We applied the proposed method for the design of electromagnetic metamaterial microstructures. Experimental results show that we achieve a significantly high probability of finding the ground‐truth topology types and their geometric parameters, leading to high accuracy in matching the design target. Moreover, our approach demonstrates significant time efficiency compared with traditional design methods.

Building epsilon near zero materials from layered uniaxial metamaterials.

Recently, there has been an explosion of activity in the fields of optics and photonics with the advent of fabrication techniques which enable the design of metamaterials which possess properties not encountered in the natural world. In this work, we are concerned with zero permittivity materials and a new scheme to design metamaterials for which all components of the dielectric tensor are approximately zero. Our approach involves the alternate layering of many, very thin, slices of two constituent metamaterials, a uniaxial layered medium and a uniaxial nanowire array. With a simple optimization strategy we demonstrate a candidate configuration which very nearly satisfies our design goal of zero permittivity.

Analysis of hyperbolic crystals with non-square lattice for improving acoustic energy harvesting

Abstract With the increase in the production of small and low-power electrical devices, there has been an increased focus on creating a useful power source to replace the battery. The energy contained in acoustic waves is one of the attractive energy sources for powering low-power devices. The design and fabrication of metamaterials is one of the effective methods of harvesting acoustic energy that has recently attracted the attention of many researchers. As is presented in this article, the aim is to design and fabricate a novel metamaterial structure with optimal dimensions to improve acoustic energy harvesting in a specific frequency range using a piezoelectric patch. In this metamaterial, hyperbolic crystals with non-square lattice have been used for the first time. This analysis is simulated using the 3D version of Comsol software 6.0. In addition, artificial neural networks and genetic algorithms were used to select the optimal parameters. The results showed that using the non-square lattice of the hyperbolic crystal, more average energy can be harvested in the frequency range of 3310-4325 Hz than in the metamaterial with the cylindrical crystal. Furthermore, the maximum amount of voltage and power extraction with an optimal electrical resistance of 10 kΩ in the metamaterial with the hyperbolic crystals at a frequency of 3374.71 Hz is equal to 27.26 mV and 74.33 nW, respectively, which is much larger compared to the metamaterial with the cylindrical crystals under the same mass and conditions. The simulation results are compared and validated with the experimental results by fabricating the present metamaterial and conducting laboratory tests.

Modeling and design of architected structures and metamaterials assisted with artificial intelligence

Abstract Architected structures and metamaterials have attracted the attention of scientists and engineers due to the contrast in behavior compared to the base material they are made from. This interest within the scientific and engineering community has lead to the use of computational tools to accelerate the design, optimization, and discovery of architected structures and metamaterials. A computational tool that has gained popularity in recent years is artificial intelligence (AI). There are several AI algorithms and as many have been used in the field of architected structures and metamaterials. AI has been used for different objectives and with different degrees of success. Then, in this review we identify the different AI used to study architected structures and metamaterials, identify the purpose of using the AI, and discuss their advantages and disadvantages. Additionally, trends in the usage of AI and particular architected structures and metamaterials are identified. Finally, perspectives regarding new directions and areas of opportunity for the use of AI in the study of architected structures and metamaterials are presented.

Shape Optimization of Tunable Poisson's Ratio Metamaterials With Disk B‐Splines

ABSTRACTWe propose an explicit representation method using disk B‐splines for Poisson's ratio metamaterial design. Disk B‐spline representation generalizes the concept of the B‐spline control point into a control disk, enhancing the ability to manipulate both the shape and thickness of the region. Therefore, this representation is frequently employed for shape optimization. The optimized metamaterials described by disk B‐spline are decomposed into a sequence of circles constructing one implicit function. A novel optimization model based on disk B‐spline representation is proposed, and the homogenization theory is used for calculating effective Poisson's ratio (PR). The numerical examples contained missing rib metamaterials, petal‐like metamaterials, and extreme PR metamaterials, which are studies to illustrate the advantages and effectiveness. By explicitly manipulating the parameters of the disk's B‐spline, a broad spectrum of unexpectedly negative Poisson's ratio from ‐0.1 to ‐0.9 sequences can be achieved, and arbitrary Poisson's ratios structures can be obtained through interpolating continuous parameters. It's also extended to encompass 3D structures. We validate the accuracy of our results by comparing them with simulations performed using commercial software.

Inverse design of multishape metamaterials

Inverse design of multishape metamaterials

Advances in artificial intelligence for artificial metamaterials

The 2024 Nobel Prizes in Physics and Chemistry were awarded for foundational discoveries and inventions enabling machine learning through artificial neural networks. Artificial intelligence (AI) and artificial metamaterials are two cutting-edge technologies that have shown significant advancements and applications in various fields. AI, with its roots tracing back to Alan Turing’s seminal work, has undergone remarkable evolution over decades, with key advancements including the Turing Test, expert systems, deep learning, and the emergence of multimodal AI models. Electromagnetic wave control, critical for scientific research and industrial applications, has been significantly broadened by artificial metamaterials. This review explores the synergistic integration of AI and artificial metamaterials, emphasizing how AI accelerates the design and functionality of artificial materials, while novel physical neural networks constructed from artificial metamaterials significantly enhance AI’s computational speed and its ability to solve complex physical problems. This paper provides a detailed discussion of AI-based forward prediction and inverse design principles and applications in metamaterial design. It also examines the potential of big-data-driven AI methods in addressing challenges in metamaterial design. In addition, this review delves into the role of artificial metamaterials in advancing AI, focusing on the progress of electromagnetic physical neural networks in optics, terahertz, and microwaves. Emphasizing the transformative impact of the intersection between AI and artificial metamaterials, this review underscores significant improvements in efficiency, accuracy, and applicability. The collaborative development of AI and artificial metamaterials accelerates the metamaterial design process and opens new possibilities for innovations in photonics, communications, radars, and sensing.

Advancing microwave absorption: Innovative strategies spanning nano-micro engineering to metamaterial design

Advancing microwave absorption: Innovative strategies spanning nano-micro engineering to metamaterial design

One-Click to 3D: Helical Carbon Nanotube-Mediated MXene Hierarchical Aerogel with Layer Spacing Engineering for Broadband Electromagnetic Wave Absorption.

MXenes are 2D materials known for their unique electromagnetic wave absorption (EMWA) properties arising from their varied composition and structure. In this study, a one-step ice-assisted process is utilized to directly transform 2D MXene into 3D single-layer MXene aerogels (SMAs). Furthermore, the interlayer spacing of the SMAs is optimized by incorporating helical carbon nanotubes (HCNTs). Because of the van der Waals interaction between the MXene nanosheets and HCNTs, the assembled HCNT@MXene aerogels (HMAs) exhibited a regular porous structure and moderate conductivity, leading to significantly enhanced electromagnetic responses, as demonstrated by finite element simulation. The HMAs showed an exceptional EMWA, with a minimum reflection loss of -51.45 dB and an effective absorption bandwidth of 6.48 GHz at 3.0 wt.% filler ratio. Additionally, visualization of surface charge distribution and power loss density characteristics clarified the underlying EMWA mechanisms. By employing a hollow structure gradient metamaterial design, the effective EMWA bandwidth is further expanded to 13.98 GHz. Additionally, HMAs exhibited the maximum radar cross-section reduction values with 27.08 dBm2. Moreover, the HMAs exhibited excellent thermal insulation capability. This paper presents a straightforward yet effective method for fabricating MXene aerogels and offers valuable insights for the development and application of MXene-aerogel-based EMW absorbers.