Nonreciprocal thermal metamaterials:Methods and applications

Nonreciprocity of thermal metamaterials has significant application prospects in isolation protection,unidirectional transmission,and energy harvesting.However,due to the inherent isotropic diffusion law of heat flow,it is extremely difficult to achieve nonreciprocity of heat transfer.This review presents the recent developments in thermal nonreciprocity and explores the fundamental theories,which underpin the design of nonreciprocal thermal metamaterials,i.e.,the Onsager reciprocity theorem.Next,three methods for achieving nonreciprocal metamaterials in the thermal field are elucidated,namely,nonlinearity,spatiotemporal modulation,and angular momentum bias,and the applications of nonreciprocal thermal metamaterials are outlined.We also discuss nonreciprocal thermal radiation.Moreover,the potential applications of nonreciprocity to other Laplacian physical fields are discussed.Finally,the prospects for advancing nonreciprocal thermal metamaterials are highlighted,including developments in device design and manufacturing techniques and machine learning-assisted material design.

General three-dimensional thermal illusion metamaterials

Thermal illusion aims to create fake thermal signals or hide the thermal target from the background thermal field to mislead infrared observers,and illusion thermotics was proposed to regulate heat flux with artificially structured metamaterials for thermal illusion.Most theoretical and experimental works on illusion thermotics focus on two-dimensional materials,while heat transfer in real three-dimensional(3D)objects remains elusive,so the general 3D illusion thermotics is urgently demanded.In this study,we propose a general method to design 3D thermal illusion metamaterials with varying illusions at different sizes and positions.To validate the generality of the 3D method for thermal illusion metamaterials,we realize thermal functionalities of thermal shifting,splitting,trapping,amplifying and compressing.In addition,we propose a special way to simplify the design method under the condition that the size of illusion target is equal to the size of original heat source.The 3D thermal illusion metamaterial paves a general way for illusion thermotics and triggers the exploration of illusion metamaterials for more functionalities and applications.

Suppression of low-frequency ultrasound broadband vibration using star-shaped single-phase metamaterials

In order to suppress the low-frequency ultrasound vibration in the broadband range of 20 k Hz—100 k Hz,this paper proposes and discusses an acoustic metamaterial with low-frequency ultrasound vibration attenuation properties,which is configured by hybrid arc and sharp-angle convergent star-shaped lattices.The effect of the dispersion relation and the bandgap characteristic for the scatterers in star-shaped are simulated and analyzed.The target bandgap width is extended by optimizing the geometry parameters of arc and sharp-angle convergent lattices.The proposed metamaterial configured by optimized hybrid lattices exhibits remarkable broad bandgap characteristics by bandgap complementarity,and the simulation results verify a 99%vibration attenuation amplitude can be obtained in the frequency of20 k Hz—100 k Hz.After the fabrication of the proposed hybrid configurational star-shaped metamaterial by 3D printing technique,the transmission loss experiments are performed,and the experimental results indicate that the fabricated metamaterial has the characteristics of broadband vibration attenuation and an amplitude greater than 85%attenuation for the target frequency.These results demonstrate that the hybrid configurational star-shaped metamaterials can effectively widen the bandgap and realize high efficiency attenuation,which has capability for the vibration attenuation in the application of highprecise equipment.

Auxetic mechanical metamaterials: from soft to stiff

Auxetic mechanical metamaterials are artificially architected materials that possess negative Poisson’s ratio,demonstrating transversal contracting deformation under external vertical compression loading.Their physical properties are mainly determined by spatial topological configurations.Traditionally,classical auxetic mechanical metamaterials exhibit relatively lower mechanical stiffness,compared to classic stretching dominated architectures.Nevertheless,in recent years,several novel auxetic mechanical metamaterials with high stiffness have been designed and proposed for energy absorption,load-bearing,and thermal-mechanical coupling applications.In this paper,mechanical design methods for designing auxetic structures with soft and stiff mechanical behavior are summarized and classified.For soft auxetic mechanical metamaterials,classic methods,such as using soft basic material,hierarchical design,tensile braided design,and curved ribs,are proposed.In comparison,for stiff auxetic mechanical metamaterials,design schemes,such as hard base material,hierarchical design,composite design,and adding additional load-bearing ribs,are proposed.Multi-functional applications of soft and stiff auxetic mechanical metamaterials are then reviewed.We hope this study could provide some guidelines for designing programmed auxetics with specified mechanical stiffness and deformation abilities according to demand.

Design,fabrication and optimization of electromagnetic absorption metamaterials

For decades,the rapid development of wireless communication has provided people a smarter way of living.However,a significant increase in electromagnetic pollution is an unavoidable consequence.Evading radar detection in modern warfare has also become an important prerequisite for survival on the battlefield.This review provides a comprehensive overview of the current status and types of electromagnetic absorption metamaterials,especially their design and preparation methods.Moreover,this review focuses on the strategies used to optimize the absorber absorption performance.Finally,this review presents a viewpoint on future research on electromagnetic absorption metamaterials,the main challenges that need to be addressed and the possible solutions.

Active Truss Metamaterials: Modelling and Tuning of Band Gaps

Periodic composite structures, like acoustic metamaterials (AMMs) and phononic crystals (PCs), are able to prevent the propagation of sound and elastic waves for some specific frequency ranges, leading to the emergence of so-called band gaps. So far, the optimization of the metamaterial properties and therefore of the band gaps has been typically performed on passive PCs and AMMs. Hence, the band gap properties cannot be tuned anymore after the production process of the metamaterials;this problem can be overcome thanks to the use of active materials. In this work, material and geometric nonlinearities are exploited to actively tune the frequency ranges of the band gaps of an architected AMM characterized by a three-dimensional periodicity. Specifically, a hyperelastic piezoelectric composite, that can be obtained by embedding piezo nanoparticles in a soft polymeric matrix, is considered to assess the effects of the nonlinearities on the behavior of sculptured microstructures, taking advantage of instability-induced pattern transformation and piezoelectricity to actively tune the band gaps. .

Designing radiative cooling metamaterials for passive thermal management by particle swarm optimization

The passive radiative cooling technology shows a great potential application on reducing the enormous global energy consumption.The multilayer metamaterials could enhance the radiative cooling performance.However,it is a challenge to design the radiative cooler.In this work,based on the particle swarm optimization(PSO)evolutionary algorithm,we develop an intelligent workflow in designing photonic radiative cooling metamaterials.Specifically,we design two 10-layer SiO_(2) radiative coolers doped by cylindrical MgF_(2) or air impurities,possessing high emissivity within the selective(8–13μm)and broadband(8–25μm)atmospheric transparency windows,respectively.Our two kinds of coolers demonstrate power density as high as 119 W/m^(2) and 132 W/m^(2) at the room temperature(300 K).Our scheme does not rely on the usage of special materials,forming high-performing metamaterials with conventional poor-performing components.This significant improvement of the emission spectra proves the effectiveness of our inverse design algorithm in boosting the discovery of high-performing functional metamaterials.

Nonlinear wave propagation in acoustic metamaterials with bilinear nonlinearity

Nonlinear phononic crystals have attracted great interest because of their unique properties absent in linear phononic crystals.However,few researches have considered the bilinear nonlinearity as well as its consequences in acoustic metamaterials.Hence,we introduce bilinear nonlinearity into acoustic metamaterials,and investigate the propagation behaviors of the fundamental and the second harmonic waves in the nonlinear acoustic metamaterials by discretization method,revealing the influence of the system parameters.Furthermore,we investigate the influence of partially periodic nonlinear acoustic metamaterials on the second harmonic wave propagation,and the results suggest that pass-band and band-gap can be transformed into each other under certain conditions.Our findings could be beneficial to the band gap control in nonlinear acoustic metamaterials.

The design, manufacture and application of multistable mechanical metamaterials-a state-of-the-art review

Multistable mechanical metamaterials are a type of mechanical metamaterials with special features,such as reusability,energy storage and absorption capabilities,rapid deformation,and amplified output forces.These metamaterials are usually realized by series and/or parallel of bistable units.They can exhibit multiple stable configurations under external loads and can be switched reversely among each other,thereby realizing the reusability of mechanical metamaterials and offering broad engineering applications.This paper reviews the latest research progress in the design strategy,manufacture and application of multistable mechanical metamaterials.We divide bistable structures into three categories based on their basic element types and provide the criterion of their bistability.Various manufacturing techniques to fabricate these multistable mechanical metamaterials are introduced,including mold casting,cutting,folding and three-dimensional/4D printing.Furthermore,the prospects of multistable mechanical metamaterials for applications in soft driving,mechanical computing,energy absorption and wave controlling are discussed.Finally,this paper highlights possible challenges and opportunities for future investigations.The review aims to provide insights into the research and development of multistable mechanical metamaterials.

Machine learning-based stiffness optimization of digital composite metamaterials with desired positive or negative Poisson's ratio

Mechanical metamaterials such as auxetic materials have attracted great interest due to their unusual properties that are dictated by their architectures.However,these architected materials usually have low stiffness because of the bending or rotation deformation mechanisms in the microstructures.In this work,a convolutional neural network(CNN)based self-learning multi-objective optimization is performed to design digital composite materials.The CNN models have undergone rigorous training using randomly generated two-phase digital composite materials,along with their corresponding Poisson's ratios and stiffness values.Then the CNN models are used for designing composite material structures with the minimum Poisson's ratio at a given volume fraction constraint.Furthermore,we have designed composite materials with optimized stiffness while exhibiting a desired Poisson's ratio(negative,zero,or positive).The optimized designs have been successfully and efficiently obtained,and their validity has been confirmed through finite element analysis results.This self-learning multi-objective optimization model offers a promising approach for achieving comprehensive multi-objective optimization.

Theory of complex-coordinate transformation acoustics for non-Hermitian metamaterials

Transformation acoustics(TA)has emerged as a powerful tool for designing several intriguing conceptual devices,which can manipulate acoustic waves in a flexible manner,yet their applications are limited in Hermitian materials.In this work,we propose the theory of complex-coordinate transformation acoustics(CCTA)and verify the effectiveness in realizing acoustic non-Hermitian metamaterials.Especially,we apply this theory for the first time to the design of acoustic parity-time(PT)and antisymmetric parity-time(APT)metamaterials and demonstrate two distinctive examples.First,we use this method to obtain the exceptional points(EPs)of the PT/APT system and observe the spontaneous phase transition of the scattering matrix in the transformation parameter space.Second,by selecting the Jacobian matrix's constitutive parameters,the PT/APT-symmetric system can also be configured to approach the zero and pole of the scattering matrix,behaving as an acoustic coherent perfect absorber and equivalent laser.We envision our proposed CCTAbased paradigm to open the way for exploring the non-Hermitian physics and finding application in the design of acoustic functional devices such as absorbers and amplifiers whose material parameters are hard to realize by using the conventional transformation method.

Active Truss Metamaterials: Modelling and Tuning of Band Gaps

Periodic composite structures, like acoustic metamaterials (AMMs) and phononic crystals (PCs), are able to prevent the propagation of sound and elastic waves for some specific frequency ranges, leading to the emergence of so-called band gaps. So far, the optimization of the metamaterial properties and therefore of the band gaps has been typically performed on passive PCs and AMMs. Hence, the band gap properties cannot be tuned anymore after the production process of the metamaterials;this problem can be overcome thanks to the use of active materials. In this work, material and geometric nonlinearities are exploited to actively tune the frequency ranges of the band gaps of an architected AMM characterized by a three-dimensional periodicity. Specifically, a hyperelastic piezoelectric composite, that can be obtained by embedding piezo nanoparticles in a soft polymeric matrix, is considered to assess the effects of the nonlinearities on the behavior of sculptured microstructures, taking advantage of instability-induced pattern transformation and piezoelectricity to actively tune the band gaps. .

Wireless Power Supply Based on MNG-MNZ Metamaterial for Cardiac Pacemakers

To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-negative(MNG) and mu-nearzero(MNZ) metamaterials. First, a hybrid metamaterial consisted of central MNG unit for magnetic field concentration and surrounding MNZ units for magnetic leakage shielding was established by theoretical calculation. Afterwards, the magnetic field distribution of wireless power supply system with MNG-MNZ metamaterial slab was acquired via finite element simulation and verified to be better than the distribution with conventional MNG slab deployed. Finally, an experimental platform of wireless power supply system was established with which power transfer experiment and system temperature rise experiment were conducted.Simulation and experimental results showed that the power transfer efficiency was improved from 44.44%,19.42%, 8.63% and 6.19% to 55.77%, 62.39%, 20.81%and 14.52% at 9.6 mm, 20 mm, 30 mm and 50 mm,respectively. The maximum SAR acquired by SAR simulation under human body environment was-7.14 dbm and maximum reduction of the magnetic field strength around the receiving coil was 2.82 A/m. The maximum temperature rise during 30min charging test was 3.85℃,and the safety requirements of human bodies were met.

Prediction of Bandwidth of Metamaterial Antenna Using Pearson Kernel-Based Techniques

The use of metamaterial enhances the performance of a specific class of antennas known as metamaterial antennas.The radiation cost and quality factor of the antenna are influenced by the size of the antenna.Metamaterial antennas allow for the circumvention of the bandwidth restriction for small antennas.Antenna parameters have recently been predicted using machine learning algorithms in existing literature.Machine learning can take the place of the manual process of experimenting to find the ideal simulated antenna parameters.The accuracy of the prediction will be primarily dependent on the model that is used.In this paper,a novel method for forecasting the bandwidth of the metamaterial antenna is proposed,based on using the Pearson Kernel as a standard kernel.Along with these new approaches,this paper suggests a unique hypersphere-based normalization to normalize the values of the dataset attributes and a dimensionality reduction method based on the Pearson kernel to reduce the dimension.A novel algorithm for optimizing the parameters of Convolutional Neural Network(CNN)based on improved Bat Algorithm-based Optimization with Pearson Mutation(BAO-PM)is also presented in this work.The prediction results of the proposed work are better when compared to the existing models in the literature.

Terahertz toroidal dipole metamaterial sensors for detection of aflatoxin B1

Terahertz metamaterial biosensors have attracted significant attention in the biological field due to their advantages of label-free,real-time and in situ detection.In this paper,a highly sensitive metamaterial sensor with semi-ring mirror symmetry based on toroidal dipole resonance is designed for a new metamaterial biosensor.It is shown that a refractive index sensitivity of 337.5 GHz per refractive index unit can be achieved under an analyte of saturated thickness near a 1.33 THz transmission dip.For biosensor samples where aflatoxin B1 is dropped on the metamaterial surface in our experiment,dip amplitudes of transmission varying from 0.1904 to 0.203 and 0.2093 are observed as aflatoxin B1 concentrations are altered from 0 to 0.001μg·ml-1 and to 0.01μg·ml-1,respectively.Furthermore,when aflatoxin B1 concentrations are 0.1μg·ml-1,1μg·ml-1,10μg·ml-1 and 100μg·ml-1,dip amplitudes of 0.2179,0.226,0.2384 and 0.2527 and dip redshifts of 10.1 GHz,20.1 GHz,27.7 GHz and 37.6 GHz are respectively observed.These results illustrate high-sensitivity,label-free detection of aflatoxin B1,enriching the applications of sensors in the terahertz domain.

Gelatin-Based Metamaterial Hydrogel Films with High Conformality for Ultra-Soft Tissue Monitoring

Implantable hydrogel-based bioelectronics(IHB)can precisely monitor human health and diagnose diseases.However,achieving biodegradability,biocompatibility,and high conformality with soft tissues poses significant challenges for IHB.Gelatin is the most suitable candidate for IHB since it is a collagen hydrolysate and a substantial part of the extracellular matrix found naturally in most tissues.This study used 3D printing ultrafine fiber networks with metamaterial design to embed into ultra-low elastic modulus hydrogel to create a novel gelatin-based conductive film(GCF)with mechanical programmability.The regulation of GCF nearly covers soft tissue mechanics,an elastic modulus from 20 to 420 kPa,and a Poisson’s ratio from-0.25 to 0.52.The negative Poisson’s ratio promotes conformality with soft tissues to improve the efficiency of biological interfaces.The GCF can monitor heartbeat signals and respiratory rate by determining cardiac deformation due to its high conformability.Notably,the gelatin characteristics of the biodegradable GCF enable the sensor to monitor and support tissue restoration.The GCF metamaterial design offers a unique idea for bioelectronics to develop implantable sensors that integrate monitoring and tissue repair and a customized method for endowing implanted sensors to be highly conformal with soft tissues.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Numerical Simulation of Slurry Diffusion in Fractured Rocks Considering a Time-Varying Viscosity

To analyze the effects of a time-varying viscosity on the penetration length of grouting,in this study cement slur-ries with varying water-cement ratios have been investigated using the Bingham’sfluidflow equation and a dis-crete element method.Afluid-solid coupling numerical model has been introduced accordingly,and its accuracy has been validated through comparison of theoretical and numerical solutions.For different fracture forms(a single fracture,a branch fracture,and a fracture network),the influence of the time-varying viscosity on the slurry length range has been investigated,considering the change in the fracture aperture.The results show that under different fracture forms and the same grouting process conditions,the influence of the time-varying viscosity on the seepage length is 0.350 m.

Adaptive Event-Triggered Time-Varying Output Group Formation Containment Control of Heterogeneous Multiagent Systems

In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.