Characterization Of Metamaterials Research Articles

Characterisation of metamaterials for underwater acoustics using the 5-point method

The characterization of metamaterials by measurement is essential to reveal the true efficiency of a material's reflection and transmission in water. The current 3-point method developed by L. Roux et al, J. Acoust. Soc. Am. 147, 2 (2020) 1104-1112 provides important advantages, such as consideration of the pressure field diffracted by the edges of the panel and late reflections, due respectively to the finite size of the panel and the water tank. However, this method only considers specularly reflected and transmitted waves. For metamaterial panels based on periodic arrays of macro-inclusions there exists a diffraction cut-off frequency, above which several propagating waves are generated in water, with frequency-dependent propagation directions, in both the reflected and transmitted fields. Due to this multiplication of waves, the 3-point method is no longer adequate. The 5-point method consider these components, in addition to those considered by the 3-point method allowing measurement beyond the material's first cut-off frequency by using 5 hydrophone position instead of three. Tests were carried out on a panel with an adaptable grating periodicity to test the robustness of the 5 points method. Results are compared with the 3-point method when both are valid and numerical results obtained by FEM.

Machine-Learning-Based Characterization and Inverse Design of Metamaterials.

Metamaterials, characterized by unique structures, exhibit exceptional properties applicable across various domains. Traditional methods like experiments and finite-element methods (FEM) have been extensively utilized to characterize these properties. However, exploring an extensive range of structures using these methods for designing desired structures with excellent properties can be time-intensive. This paper formulates a machine-learning-based approach to expedite predicting effective metamaterial properties, leading to the discovery of microstructures with diverse and outstanding characteristics. The process involves constructing 2D and 3D microstructures, encompassing porous materials, solid-solid-based materials, and fluid-solid-based materials. Finite-element methods are then employed to determine the effective properties of metamaterials. Subsequently, the Random Forest (RF) algorithm is applied for training and predicting effective properties. Additionally, the Aquila Optimizer (AO) method is employed for a multiple optimization task in inverse design. The regression model generates accurate estimation with a coefficient of determination higher than 0.98, a mean absolute percentage error lower than 0.088, and a root mean square error lower than 0.03, indicating that the machine-learning-based method can accurately characterize the metamaterial properties. An optimized structure with a high Young's modulus and low thermal conductivity is designed by AO within the first 30 iterations. This approach accelerates simulating the effective properties of metamaterials and can design microstructures with multiple excellent performances. The work offers guidance to design microstructures in various practical applications such as vibration energy absorbers.

Roll‐to‐Roll Compatible Topochemical Wetting Control for Metamaterial Printing

AbstractThe widespread utilization of metamaterials, despite their immense transformative potential, faces challenges regarding scalability in mass production. To address these limitations, an additive method that leverages liquid inks and selective wetting to produce scalable and cost‐effective metamaterials is presented. UV‐based imprinting lithography is utilized to fabricate surface energy‐modulated patterns, enabling precise solution patterning. This approach, unlike conventional UV‐based imprinting lithography, not only accurately produces the negative replica of the stamp topography during UV‐induced crosslinking but also transfers a hydrophobic layer onto the raised surfaces of the imprinted hydrophilic layer, resulting in 3D shapes with spatially modulated surface energy. In the second process step, a functional ink is dragged over the patterned substrate where it dewets to fill the hydrophilic recesses. This innovative process enables high‐speed metamaterial production, with ink deposition speeds up to 12 m min−1. The method accommodates a wide range of inks, including metals, dielectrics, and semiconductors, providing meticulous control over vertical structures such as pattern thickness and hetero‐multilayer formation. Additionally, it offers flexibility in creating metamaterials on free‐standing ultra‐thin sheets, introducing desirable attributes like foldability and disposability. The effectiveness of this approach is validated through the fabrication and characterization of metallic metamaterials.

Characterization of interaction phenomena of electromagnetic waves with metamaterials via microwave near-field visualization technique

A new practical imaging technique was presented for metamaterial characterization and investigation by visualizations of the magnetic microwave near-field (H-MWNF) distributions on a metamaterial's surface using the method of thermo-elastic optical indicator microscopy (TEOIM). ITO-based transparent and ceramic-based opaque metamaterial structures were designed for magnetic near-field visualization. Depending on the incident microwave field polarization, the TEOIM system allows the characterization of the metamaterial properties and microwave interaction behavior. The working principle of the periodic structures was investigated through numerical simulations, and the obtained results exhibited strong agreement when compared with experimental observations. Moreover, the visualization of the H-MWNF revealed the potential to characterize and evaluate the absorption and transmission properties effectively.

Physics of Complex Photonic Media and Metamaterials: feature issue introduction

We introduce the Optical Materials Express feature issue on the Physics of Complex Photonic Media and Metamaterials. This issue comprises a collection of nine manuscripts on the development, characterization, control, and applications of complex photonic media and metamaterials, including but not limited to metagratings, chiral metamirrors, diamond nanopillars, rotating metamaterials, and networks of random lasers.

Strongly suppressed diffuse scattering in periodic graphene metamaterials.

As an emerging two-dimensional material, graphene offers an alternative material platform for exploring new metamaterial phenomena and device functionalities. In this work, we examine diffuse scattering properties in graphene metamaterials. We take periodic graphene nanoribbons as a representative example and show that diffuse reflection in graphene metamaterials as dominated by diffraction orders is restricted to wavelengths less than that of first-order Rayleigh anomaly, and is enhanced by plasmonic resonances in graphene nanoribbons, as similar to metamaterials made of noble metals. However, the overall magnitude of diffuse reflection in graphene metamaterial is less than 10-2 due to the large period to nanoribbon size ratio and ultra-thin thickness of the graphene sheet, which suppress the grating effect from the structural periodicity. Our numerical results indicate that, in contrast to the cases of metallic metamaterials, diffuse scattering plays a negligible role in spectral characterization of graphene metamaterials in cases with large resonance wavelength to graphene feature size ratio, which corresponds to typical chemical vapor deposition (CVD)-grown graphene with relatively small Fermi energy. These results shed light on fundamental properties of graphene nanostructures and are helpful in designing graphene metamaterials for applications in infrared sensing, camouflaging, and photodetection, etc.

Metamaterial characterization from far-field acoustic wave measurements using convolutional neural network

Identifying the material properties of unknown media is an important scientific/engineering challenge in areas as varied as in-vivo tissue health diagnostics and metamaterial characterization. Currently, techniques exist to retrieve the material parameters of large unknown media from elastic wave scattering in free-space using analytical or numerical methods. However, applying these methods to small samples on the order of few wavelengths in diameter is challenging, as the fields scattered by these samples become significantly contaminated by diffraction from the sample edges. Here, we propose a method to extract the material parameters of small samples using convolutional neural networks trained to learn the mapping between far-field echoes and the material parameters. Networks were trained with synthetic time domain echo data obtained by simulating the free-space scattering of sound from unknown media underwater. Results show that neural networks can accurately predict effective material parameters such as mass density, bulk modulus, and shear modulus even when small training sets are used. Furthermore, we demonstrate in experiments executed in a water tank that the networks trained with synthetic data can accurately estimate the material properties of fabricated metamaterial samples from single-point echo measurements performed in the far-field. This work highlights the effectiveness of our approach to identify unknown media using far-field acoustic reflection dominated by diffraction fields and will open a new avenue toward acoustic sensing techniques.

Extraction of the Electromagnetic Parameters of a Metamaterial Using the Nicolson–Ross–Weir Method: An Analysis Based on Global Analytic Functions and Riemann Surfaces

The characterization of electromagnetic metamaterials (MMs) plays a fundamental role in their engineering processes. To this end, the Nicolson–Ross–Weir (NRW) method is intensively used to recover the effective parameters of MMs, even though this is affected by the branch ambiguity problem. In this paper, we face this issue in the context of global analytic functions and Riemann surfaces. This point of view allows us to rigorously demonstrate the mathematical foundations of an algorithmic approach for avoiding the branch ambiguity problem, in which the phase unwrapping method is merged with K-K relations for recovering the effective parameters of an MM. In addition, exploiting the intimate relationship between the K-K relations and the Hilbert transform, a simple variant of the above algorithm is presented.

Learning the dynamics of metamaterials from diffracted waves with convolutional neural networks

Conventional methods used to identify the dynamical properties of unknown media from scattered mechanical waves rely on analytical or numerical manipulations of the wave equation. These methods show their limitations in scenarios where the analyzed medium is moderately sized and the diffraction from the material edges influences the scattered fields significantly, such as non-destructive diagnostics and metamaterial characterization. Here, we show that convolutional neural networks can interpret the diffracted fields and learn the mapping between the scattered fields and all the effective material parameters including mass density and stiffness tensors from a small set of numerical simulations. Furthermore, networks trained with synthetic data can process physical measurements and are very robust to measurement errors. More importantly, the trained network provides insight into the dynamic behavior of matter including quantitative measures of the scattered field sensitivity to each material property and how the sensitivity changes depending on the material under test.

Design and characterization of novel bi-directional auxetic cubic and cylindrical metamaterials

Traditional auxetic structures only exhibit lateral contraction when axially compressed. In this paper, a strategy of bi-directional auxetic metamaterials with tunable effective Poisson's ratio is proposed. The bi-directional auxetic metamaterials based on two-dimensional double arrow structures are designed and then fabricated through additive manufacturing. The deformation mechanisms of the proposed structures are investigated through numerical simulations combined with experiments in the present study. The results show that the relative specific stiffness and the effective Poisson’s ratios of the proposed structures depend on geometrical parameters and geometrical configuration. The relative specific stiffness of the three-dimensional cubic structure (TCU) is between the internal and external stiffness of the structure, as is the case of the effective Poisson’s ratio. The axisymmetric deformation mechanism of the three-dimensional cylindrical structure (TCY) generates transversely isotropic Poisson’s ratio and enhances stiffness compared to the TCU with the same geometric parameters. This work systematically characterizes the deformation mechanism of innovatively designed structures and widens the potential applications of metamaterials in the fields of machinery, encompassing biomedicine, and electronic devices.

Characterization and development of periodic acoustic metamaterials using a transfer matrix approach

A transfer matrix approach that combines with finite element calculations is proposed tocharacterizehomogeneous and non-homogeneous acoustic absorbing materialswith in-plane periodicity. The characterized acoustic materials are mainly metamaterials made of multiple layers, where at least one layer consists of a non-homogeneous material (NHM). The NHM is a porous or solid matrix with embedded periodic simple or complex inclusions and Helmholtz resonators. The equivalent transfer matrix of the NHM is determined by the proposed approach which is similar to the three-microphone two-load method. By using the equivalent transfer matrix of the NHM coupled analytically in series with other transfer matrices, complex multilayer systems can be modeled easily and quickly in configurations wherein the use of finite element calculation alone will be more expensive and time consuming. The results of the normal incidence sound transmission loss predicted by the present method are compared with finite element results for different configurations of metamaterials and good agreements are obtained. The proposed method offers an efficient way to characterize and design at normal incidence complex multilayer acoustic metamaterials with periodic inclusions. It can be used to optimize multilayer system containing non-homogeneous materials.

Design and Wave Propagation Characterization of Starchiral Metamaterials

Design and Wave Propagation Characterization of Starchiral Metamaterials

Validation of FEM models based on Carrera Unified Formulation for the parametric characterization of composite metamaterials

This work focuses on the study of composite metamaterials to be employed as possible lightweight insulation systems for noise and vibrations. In particular, the dispersion relations are derived by applying the Bloch-Floquet theory to the unit cell of the periodic microstructure. Advanced beam finite elements based on Carrera Unified Formulation are here extended, for the first time, to the dynamic characterization of these materials. Moreover, transmission curves are computed to validate the band gaps encountered in the analysis of dispersion behavior. The finite element model is first assessed by evaluating the dispersion behavior of some metamaterial configurations proposed in the literature. Finally, the model is applied to the parametric characterization of a composite metamaterial made of a melamine foam matrix and periodic distribution of cylindrical aluminium inclusions. The results show that it is possible to tune the band gaps of the metamaterial to lower frequencies by simply varying the dimensions of the unit cell and keeping constant its equivalent density.

Empirical Study of Solar Absorber Metamaterial Characterization in GHz and THz Regime

Advanced material such as composite material, metamaterial, nanomaterials and smart materials plays a significant role in degree of performance of any system as compared to conventional material and hence, they are commonly used in diverse applications such as aerospace, medical devices, sensor detection, smart solar application etc. Metamaterial is one of such artificial sub-wavelength materials to exhibit electromagnetic and optical properties that surpass or complement those accessible in nature. In this research paper, three structure of metamaterials are simulated for the solar application as an absorber to increase solar efficiency as well as to increase negative refractive index to represent wave propagation in different directions. From this study it can be concluded that all the three materials have reached maximum point of absorption in a narrow bandwidth and it is possible to obtain transverse magnetic wave if the materials are stacked. These materials can be used as frequency detector for THz applications.

Retrieving effective surface susceptibilities of high-index metasurfaces based on dipole approximation

Electromagnetic (EM) characterization of metamaterials and metasurfaces is crucial for theoretical modeling and also efficient design of state-of-the-art applications. Thus far, the widely used parameter retrieval methods have been provided unphysical artifacts in modeling of metasurfaces. In this work, we develop a new parameter retrieval method which is based on dipole approximation and Ewald lattice summation. This technique can be used to efficiently characterize metasurfaces that support simultaneous electric and magnetic dipole resonances, when illuminated by a plane-wave at an arbitrary angle of incidence. We retrieve the effective parameters of a high-index metasurface composed of silicon nanospheres and demonstrate that in contrast to the conventional methods, the proposed model successfully describes its optical responses. Based on our results, it is demonstrated that even in metasurfaces composed of isotropic structures, bianisotropic terms can be excited at oblique angles of incidence. The developed parameter retrieval method is much more efficient compared to conventional methods, and it is certainly useful in precise modeling and proper designing of even more complex optical metasurfaces.

Anomalous blueshift of aperture resonance enabled by the loss of a thin film

The substrate effects on aperture resonance have been widely studied because the resonance peak position is key for sensing, communications, and field enhancement applications. So far, the theoretical works have focused on the lossless infinite substrate case, which only explains the resonance peak redshift by the substrate index. The loss effect has not been investigated yet because lossy infinite substrate significantly reduces the aperture transmission. Therefore, this work studied the loss effect on aperture resonance via an analytic model of the transmission though slot antennas on a finite substrate. When the substrate thickness was very thin compared to the wavelength, the transmittance remained high even for a large imaginary part of the refractive index; furthermore, the developed model predicted a strong blueshift when this imaginary part exceeds the real part. Besides, the zero of the imaginary part of the coupling strength was crucial in determining the resonance frequency for both infinite and finite substrates. Thus, this study can contribute to the material characterization, label-free detection, and efficient design of active metamaterials.

Design and characterization of tunable three-dimensional acoustic composite metamaterials

Purpose The purpose of this paper is to developing a kind of acoustic metamaterial with wide frequency band especially in low frequency region. At the same time, its the tunability of sound insulation frequency is achieved. Design/methodology/approach A three-dimensional (3D) acoustic metamaterial consisting of rigid frame, spherical attachment and thin film is proposed. The material parameters and the effect of the attachment hole on the forbidden band are investigated by finite element simulation. The sound insulation effect of the structure is validated by the combination of simulation and experiment. Findings The results show that the elastic modulus of the structural material determines the initial frequency of the forbidden band of the proposed 3D acoustic metamaterials. The lower the elastic modulus of the structural material, the lower the initial frequency of the forbidden band. The material parameters of the frame mainly affect the initial frequency of the first forbidden band, and the material parameters of the attachment will affect both the initial and termination frequency of the first forbidden band. Holes in the attachments reduce the band gap width. The characteristic curve moves down with the increase of subtracted mass. Research limitations/implications The findings may greatly benefit the application of the acoustic metamaterials in the fields of sound insulation and noise reduction. Originality/value This acoustic metamaterial structure has excellent sound insulation performance. At the same time, the single cell structure can be assembled into any shape. The structure can achieve sound selective filtering and combination control.

Nanocone-based plasmonic metamaterials

Metamaterials and metasurfaces provide unprecedented opportunities for designing light–matter interactions. Optical properties of hyperbolic metamaterials with meta-atoms based on plasmonic nanorods, important in nonlinear optics, sensing and spontaneous emission control, can be tuned by varying geometrical sizes and arrangement of the meta-atoms. At the same time the role of the shape of the meta-atoms forming the array has not been studied. We present the fabrication and optical characterization of metamaterials based on arrays of plasmonic nanocones closely packed at the subwavelength scale. The plasmonic mode structure of the individual nanocones and pronounced coupling effects between them provide multiple degrees of freedom to engineer both the field enhancement and the optical properties of the resulting metamaterials. The metamaterials are fabricated using a scalable manufacturing procedure, allowing mass-production at the centimeter scale. The ultra-sharp cone apex (2 nm) and the associated field enhancement provide an extremely high density of electromagnetic hot-spots (∼1010 cm−2). These properties of nanocone-based metamaterials are important for the development of gradient-index metamaterials and in numerous applications in fluorescence enhancement, surface enhanced Raman spectroscopy as well as hot-carrier plasmonics and photocatalysis.

The use of acoustic resonators for characterization of underwater acoustic metamaterials

The characterization of acoustic metamaterials used in underwater applications at low frequencies (below a few kilohertz) is complicated by the associated long wavelengths (1 m and greater), which render free field methods impractical for a range of frequencies of significant interest. One approach used to address this issue is the water-filled acoustic resonator. The key benefit is that a resonator tube with a length of as little as one half wavelength can be used for material characterization, compared to free-field techniques, which require a spatial extent of several wavelengths in two or more dimensions. Another benefit is that sample size can be orders of magnitude smaller when using a resonator. These benefits are enabling, but come at the expense of designing a system to overcome the fact that practical tube materials such as steel or glass cannot be considered rigid when water-filled. Another caveat is that an appropriate model is required to relate the observed resonance frequencies to the acous...

Adaptive manifold interpolation techniques for acoustic metamaterial characterization in HPC environments

Functionally graded acoustic metamaterials (FGAMs) can be designed to have specific waveguide properties dictated by a theory relevant to the application. Frequently, these material properties do not exist naturally, and must be fabricated by gradually layering manufactured unit cell microstructures, resulting in a (usually smooth) variation of properties. Tailoring these microstructures to the demands of the relevant theory requires assembling microstructures with very specific material properties—a process that often requires haphazardly searching a large domain space of unit cells for desirable parameter combinations. Moreover, the process of determining the material tensor of interest for a specific set of metamaterial cell design parameters typically involves solving a costly high dimensional finite element problem for each new microstructure cell of interest. This work presents a gradient-based, manifold interpolation technique to characterize acoustic metamaterial homogenized elastic tensors. An adaptive refinement method is used to seed the interpolation data allowing the method to reliably recover unit cell stiffness tensors within predefined error bounds—allowing for interpolation of a cell with desired properties within specified error tolerances while minimizing the number of unit cells that require high-fidelity, computationally-expensive simulation. Finally, an implementation of the process is presented in a massively parallel computing environment.