Mixed finite element numerical mode matching method for designing infrared broadband polarization-independent metamaterial absorbers.

Conventional numerical methods have found widespread applications in the design of metamaterial structures, but their computational costs can be high due to complex three-dimensional discretization needed for large complex problems. In this work, we apply a recently developed numerical mode matching (NMM) method to design a black phosphorus (BP) absorber. NMM transforms a complex three-dimensional (3D) problem into 2D numerical eigenvalue problems plus a 1-D analytical propagation solution, thus it can save a lot of computational costs. BP is treated as a 2D surface and represented by the anisotropic surface conductance. With a realistic simulation study, we show that our method is more accurate and efficient than the standard finite element method (FEM). Our designed absorber can achieve an average absorption of 97.4% in the wavelength range of 15 to 23 µm under normal incidence. Then, we investigate the physical mechanism of the absorber, tuning the geometric parameters and electron doping to optimize the performance. In addition, the absorption spectra under oblique incidence and arbitrary polarization are studied. The results confirm that our absorber is polarization-independent and has high absorption at large incident angles. Our work validates the superiority of NMM and provides a new simulation platform for emerging metamaterial device design.

A 3-D Full Convolution Electromagnetic Reconstruction Neural Network (3-D FCERNN) for Fast Super-Resolution Electromagnetic Inversion of Human Brain.

Three-dimensional (3-D) super-resolution microwave imaging of human brain is a typical electromagnetic (EM) inverse scattering problem with high contrast. It is a challenge for the traditional schemes based on deterministic or stochastic inversion methods to obtain high contrast and high resolution, and they require huge computational time. In this work, a dual-module 3-D EM inversion scheme based on deep neural network is proposed. The proposed scheme can solve the inverse scattering problems with high contrast and super-resolution in real time and reduce a huge computational cost. In the EM inversion module, a 3-D full convolution EM reconstruction neural network (3-D FCERNN) is proposed to nonlinearly map the measured scattered field to a preliminary image of 3-D electrical parameter distribution of the human brain. The proposed 3-D FCERNN is completely composed of convolution layers, which can greatly save training cost and improve model generalization compared with fully connected networks. Then, the image enhancement module employs a U-Net to further improve the imaging quality from the results of 3-D FCERNN. In addition, a dataset generation strategy based on the human brain features is proposed, which can solve the difficulty of human brain dataset collection and high training cost. The proposed scheme has been confirmed to be effective and accurate in reconstructing the distribution of 3-D super-resolution electrical parameters distribution of human brain through noise-free and noisy examples, while the traditional EM inversion method is difficult to converge in the case of high contrast and strong scatterers. Compared with our previous work, the training of FCERNN is faster and can significantly decrease computational resources.

Reconstruction of three-dimensional objects in layered composite structures from multimode orbital angular momentum.

Because of helical phase wavefront distribution, vortex electromagnetic waves are considered to carry more information and additional degrees of freedom than traditional spherical waves. Therefore, a vortex wave carrying orbital angular momentum (OAM) can improve inversion and imaging accuracy. In this work, we revisit the reconstruction of three-dimensional objects in layered composite structures extended with OAM. In forward modeling, the concentric uniform circle array is used to generate electromagnetic vortex beams. To analyze the difference of vortex beams, the electric field radiation pattern and phase pattern distribution of OAM waves with different modes are calculated. Then, the scattered field of layered media illuminated by different OAM beams is determined by the dyadic Green's function and the stabilized biconjugate gradient technique with a fast Fourier transform algorithm. In the inversion, the variational Born iterative method is used to reconstruct targets in layered composite structures, and multiple OAM modes are used to improve the reconstruction results. The numerical results prove that the permittivity of the target can be better reconstructed by using the multiple OAM modes rather than the traditional spherical wave. With the increase of OAM mode number, the reconstructed target parameters are closer to the true value. We expect that our results will provide a better understanding of the OAM and pave the way for the improvement of inversion and optical imaging technology using vortex waves.

Acoustic impact of the human skull on transcranial photoacoustic imaging.

With balanced spatial resolution, imaging depth, and functional sensitivity, photoacoustic tomography (PAT) hold great promise for human brain imaging. However, the strong acoustic attenuation and aberration of the human skull (∼8 mm thick) are longstanding technical challenges for PAT of the human brain. In this work, we numerically investigated the impacts of the stratified human skull on photoacoustic wave propagation (i.e., the forward model) and PAT image formation (i.e., the inverse model). We simulated two representative transcranial PAT implementations: photoacoustic computed tomography (PACT) and photoacoustic macroscopy (PAMac). In the forward model, we simulated the detailed photoacoustic wave propagation from a point or line source through a digital human skull. The wave attenuation, refraction, mode conversation, and reverberation were thoroughly investigated. In the inverse model, we reconstructed the transcranial PACT and PAMac images of a point or line target enclosed by the human skull. Our results demonstrate that transcranial PAMac suffers mainly from wave reverberation within the skull, leading to prolonged signal duration and reduced axial resolution. Transcranial PACT is more susceptible to the skull's acoustic distortion, mode conversion, and reverberation, which collectively lead to strong image artifacts and deteriorated spatial resolutions. We also found that PACT with a ring-shaped transducer array shows more tolerance of the skull's adverse impacts and can provide more accurate image reconstruction. Our results suggest that incorporating the skull's geometry and acoustic properties can improve transcranial PAT image reconstruction. We expect that our results have provided a more comprehensive understanding of the acoustic impact of the human skull on transcranial PAT.

All-dielectric orthogonal doublet cylindrical metalens in long-wave infrared regions.

Metalens have been recently introduced to overcome shortcomings of traditional lenses and optical systems, such as large volume and complicated assembly. As a proof-of-principle demonstration, we design an all-dielectric converging cylindrical metalens (CML) for working in long-wave infrared regions around 9 µm, which is made up of silicon-pillar on MgF2 dielectric layer. We further demonstrate the focusing effect of an orthogonal doublet cylindrical metalens (ODCM). Two CMLs are combined orthogonally and a circular focusing spot was demonstrated. This proves that within a certain size range, the focusing effect achieved by the ODCM is similar to that of a traditional circular metalens.

Doubly mirror-induced electric and magnetic anapole modes in metal-dielectric-metal nanoresonators.

Anapole mode is a nonradiative resonance originating from the destructive interference between co-excited Cartesian electric dipole and toroidal dipole moments. With at least two symmetric circulating currents, the anapole mode in all-dielectric nanoresonators provides the opportunity to operate the double perfect electric conductor (PEC) mirror effects. In this work, unlike the conventional metal-dielectric-metal (MDM) nanostructure generating a plasmonic magnetic resonance, two metal components are employed to produce the fictitious images of the middle dielectric, and the whole system can thus excite the doubly mirror-induced anapole mode. Electric anapole mode and its magnetic counterpart are, respectively, investigated in two types of MDM configurations according to their own symmetric characteristics. Benefiting from the double PEC mirror effects, the doubly mirror-induced electric and magnetic anapole modes possess the larger average electric-field enhancement factors (9 and 56.9 folds compared with those of the conventional ones, respectively), as well as the narrower line widths. This work will pave a new way for tailoring and boosting anapole modes in metal-dielectric hybrid nanoresonators and open up new opportunities for many significant applications in nonlinear and quantum nanophotonics.

The transport of a charged peptide through carbon nanotubes under an external electric field: a molecular dynamics simulation.

The study of interactions between biomolecules and carbon nanotubes (CNTs) is of great importance in CNT-based drug delivery systems and biomedical devices. In this work, the transport of polyarginine (R8) peptide through CNTs under an external electric field was investigated via all-atom molecular dynamics (AAMD) simulation. It was found that the electric field can assist the R8 peptide to overcome the resistance and make the transport smooth. Moreover, the efficiency of transport was improved with the increasing intensity of the electric field in a suitable range. In addition, we also investigated the effects of different types of CNTs on the transport of the R8 peptide and found that the single-walled carbon nanotube (SWCNT) was more suitable for transporting the R8 peptide than the double-walled carbon nanotube (DWCNT) due to its lower energy barrier to the R8 peptide. All these findings shed light on the role of the electric field on the transport of the R8 peptide through CNTs and also gave some valuable insights into the effects of CNT types on the transport process of the peptide.

Enhancing third-harmonic generation by mirror-induced electric quadrupole resonance in a metal-dielectric nanostructure.

Electric quadrupole resonance (EQR), a commonly available high-order Mie-type resonance in all-dielectric nanoparticles, suffers from weak field enhancement and thus inferior third-harmonic generation (THG). In this work, according to the intrinsic centrosymmetry of current distribution, mirror-induced EQR in a silicon disk is effectively generated by introducing a bottom metal film with the perfect electric conductor (PEC) mirror effect, manifesting preeminent capabilities of tailoring far-field scattering and enhancing near-field intensity. The beneficial THG by mirror-induced EQR is enhanced by more than 50-fold as compared to that of the typical EQR without the PEC mirror effect. Furthermore, the influence of the silicon Kerr effect on THG is investigated under increasing pump intensity, achieving maximal efficiency of 2.2×10-4 under pump intensity I0=3GW/cm2. This work opens possibilities of exploring new mirror-induced Mie-type resonances in hybrid nanostructures, finding important applications in frequency conversion, spectroscopy, and sensing at the nanoscale.

Mixed Finite Element Method for Full-Wave Simulation of Bioelectromagnetism From DC to Microwave Frequencies.

Bioelectromagnetism focuses on the study of electromagnetic fields in biological tissues from direct current (DC) to optical frequencies. It is challenging to develop an electromagnetics (EM) simulation method to cover this entire frequency band due to the electrically small/large scattering problem at extremely low/high frequencies. This paper focuses on the band from DC to microwave frequencies in bioelectromagnetism. Its main research objective is to develop a method that can overcome the low frequency breakdown problem at low frequencies (practically DC) and still stay stable at microwave frequencies. Based on the scattered field vector Helmholtz equation, the mixed finite element method (mixed FEM) is developed for the broadband electromagnetic field simulation in biological tissues. By imposing Gauss' law as the constraint condition, the mixed FEM overcomes the low frequency breakdown problem without resorting to the quasi-static approximation and remains effective and accurate at high frequencies. Extremely low frequency and high frequency numerical results are demonstrated to verify that the mixed FEM is a stable full-wave electromagnetic field simulation method for the full-bandwidth bioelectromagnetism.

Selective light trapping of plasmonic stack metamaterials by circuit design.

Plasmonic metamaterials have wide applications in light trapping and manipulation. However, most of their design typically rely on solving Maxwell's equations via computational electromagnetics, which is time-consuming and limits design flexibility. Here, we combined the transmission line circuit theory with full wave simulation to design plasmonic stack metamaterials in the near-infrared range. By virtue of the simplicity and high efficiency of circuit theory, we designed various light trapping functions by using plasmonic stack metamaterials, including comb filtering, short pass, long pass, band pass and band stop. Our study reveals the field-circuit relationship for the light-matter interaction of nanostructure stacks and provides a powerful method for the quick design of functional plasmonic metamaterials.

Reducing Acoustic Inhomogeneity Based on Speed of Sound Autofocus in Microwave Induced Thermoacoustic Tomography.

Microwave induced thermoacoustic tomography is a newly developing non-invasive and non-ionizing modality. In practical applications, such as breast tumor detection and brain imaging, the acoustic properties in the tissue to be detected are usually unknown and spatially non-uniform, which results in distortion and blurring of the buried targets. In this paper, a reconstruction method based on speed of sound (SoS) autofocus is proposed to reduce the effect of acoustic inhomogeneity in different soft tissues. According to this method, the number of tissue types, which are referred to as clusters in this work, can be automatically determined by a decision graph. To distinguish the boundaries of different tissues, a Gaussian Mixture Model (GMM) is fitted to the obtained image data for soft clustering instead of traditional hard clustering. Through fixing the tissue centers which are characterized by corresponding data density peaks as the means of Gaussian parameters rather than choosing them randomly, adaptive and robust reconstruction performance can be guaranteed. After performing an iterative GMM optimization, the SoS autofocus is achieved. Image reconstructed by using the updated SoS distribution is with higher accuracy than that with homogeneous assumption. Compared with the existing similar methods, the proposed method strategy obviates the need of extra experiment costs, and possesses good robustness with respect to hard assignment model errors when the medium is relatively complex. Realistic breast model and brain model simulations combined with experiments of agar phantom and pig's brain are provided to demonstrate the effectiveness of the proposed method.

Carbon Nanotubes Enabling Highly Efficient Cell Apoptosis by Low-Intensity Nanosecond Electric Pulses via Perturbing Calcium Handling.

Effective induction of targeted cancer cells apoptosis with minimum side effects has always been the primary objective for anti-tumor therapy. In this study, carbon nanotubes (CNTs) are employed for their unique ability to target tumors and amplify the localized electric field due to the high aspect ratio. Highly efficient and cancer cell specific apoptosis is finally achieved by combining carbon nanotubes with low intensity nanosecond electric pulses (nsEPs). The underlying mechanism may be as follows: the electric field produced by nsEPs is amplified by CNTs, causing an enhanced plasma membrane permeabilization and Ca2+ influx, simultaneously triggering Ca2+ release from intracellular storages to cytoplasm in a direct/indirect manner. All the changes above lead to excessive mitochondrial Ca2+ uptake. Substructural damage and obvious mitochondria membrane potential depolarization are caused subsequently with the combined action of numerously reactive oxygen species production, ultimately initiating the apoptotic process through the translocation of cytochrome c to the cytoplasm and activating apoptotic markers including caspase-9 and -3. Thus, the combination of nanosecond electric field with carbon nanotubes can actually promote HCT116 cell death via mitochondrial signaling pathway-mediated cell apoptosis. These results may provide a new and highly efficient strategy for cancer therapy.

High-efficient and low-coupling spoof surface plasmon polaritons enabled by V-shaped microstrips.

We propose a novel variety of V-shaped microstrips for highly efficient and strongly confined spoof surface plasmon polaritons (SSPPs) propagation. We analyze the dispersion characteristics of the V-shaped SSPPs microstrip units and find that the asymptotic frequency of the dispersion curve can be significantly reduced by adding the folded stub without increasing the lateral dimension of the structure. The V-shaped microstrip possesses the advantage of being compatible with a conventional microstrip without the need for complicated and bulky mode conversion structures in other typical grooved SSPP waveguides. Then, broadband transitions with a tapered microstrip and an array of graded height V-shaped units with good impedance matching and high mode conversion efficiency are designed. The simulated and measured results demonstrate that the proposed V-shaped microstrip has excellent broadband lowpass filter characteristics with the reflection coefficient (S11) less than -10 dB and the transmission coefficient (S21) higher than -3 dB in the frequency range from 0 to 10.3 GHz. Furthermore, the coupling characteristics of the parallel and symmetrically arranged V-shaped microstrips are investigated. Compared to conventional parallel microstrips with a separation of 2.8 mm, the proposed parallel V-shaped microstrips with 2 mm inner-overlapping have significantly lower coupling effects in the frequency ranging from 0 to 10 GHz. The low coupling, strong field confinement, and flexible dispersion manipulation of the proposed microstrip make it possible to achieve device miniaturization and noise interference suppression, which may have great potentials in the development of various highly integrated microwave plasmonic circuits, devices, and systems.

Broadband Waveguide Cloak for Water Waves.

Inspired by electromagnetic waveguide cloaks with gradient index metamaterials, we fabricated a broadband cloak with simply a gradient depth profile on the bottom and without any other structures on the top to confine water waves in a certain area for cloaking regions. The new physics of mode conversion for water waves is first found. The experimental and numerical simulation results are in good agreement and show that the presented device has a nice performance for various situations and is feasible over a broadband of working frequencies. Being easy to construct, this design is potentially of significance for port applications.

Smart inverse design of graphene-based photonic metamaterials by an adaptive artificial neural network.

The burgeoning research of graphene and other 2D materials enables many unprecedented metamaterials and metadevices for applications on nanophotonics. The design of on-demand graphene-based metamaterials often calls for the solution of a complex inverse problem within a small sampling space, which highly depends on the rich experiences from researchers of nanophotonics. Conventional optimization algorithms could be used for this inverse design, but they converge to local optimal solutions and take significant computational costs with increased nanostructure parameters. Here, we establish a deep learning method based on an adaptive batch-normalized neural network, aiming to implement smart and rapid inverse design for graphene-based metamaterials with on-demand optical responses. This method allows a quick converging speed with high precision and low computational consumption. As typical complex proof-of-concept examples, the optical metamaterials consisting of graphene/dielectric alternating multilayers are chosen to demonstrate the validity of our design paradigm. Our method demonstrates a high prediction accuracy of over 95% after very few training epochs. A universal programming package is developed to achieve the design goals of graphene-based metamaterials with low absorption and near unity absorption, respectively. Our work may find important design applications in the field of nanoscale photonics based on graphene and other 2D materials.

Green's function for anisotropic dispersive poroelastic media based on the Radon transform and eigenvector diagonalization.

A compact Green's function for general dispersive anisotropic poroelastic media in a full-frequency regime is presented for the first time. First, starting in a frequency domain, the anisotropic dispersion is exactly incorporated into the constitutive relationship, thus avoiding fractional derivatives in a time domain. Then, based on the Radon transform, the original three-dimensional differential equation is effectively reduced to a one-dimensional system in space. Furthermore, inspired by the strategy adopted in the characteristic analysis of hyperbolic equations, the eigenvector diagonalization method is applied to decouple the one-dimensional vector problem into several independent scalar equations. Consequently, the fundamental solutions are easily obtained. A further derivation shows that Green's function can be decomposed into circumferential and spherical integrals, corresponding to static and transient responses, respectively. The procedures shown in this study are also compatible with other pertinent multi-physics coupling problems, such as piezoelectric, magneto-electro-elastic and thermo-elastic materials. Finally, the verifications and validations with existing analytical solutions and numerical solvers corroborate the correctness of the proposed Green's function.

Enhanced Antitumor Efficacy Achieved Through Combination of nsPEFs and Low-Dosage Paclitaxel.

Looking for a safe and effective cancer therapy for patients is becoming an important and promising research direction. Nanosecond pulsed electric field (nsPEF) has been found to be a potential non-thermal therapeutic technique with few side effects in pre-clinical studies. On the other hand, paclitaxel (PTX), as a common chemotherapeutic agent, shows full anti-tumor activities and is used to treat a wide variety of cancers. However, the delivery of PTX is challenging due to its poor aqueous solubility. Hence, high dosages of PTX have been used to achieve effective treatment, which creates some side effects. In this study, nsPEF was combined with low-level PTX, in order to validate if this combined treatment could bring about enhanced efficacy and allow reduced doses of PTX in clinical application. Cell proliferation, apoptosis, and cell cycle distribution were examined using MTT and flow cytometry assay, respectively. Results showed that combination treatments of nsPEF and PTX exhibited significant synergistic effects in vitro. The underlying mechanism might be that these two agents acted at different targets and coordinately enhanced MDA-MB-231 cell death.

Broadband optical waveguide modulators based on strongly coupled hybrid graphene and metal nanoribbons for near-infrared applications.

In this paper, we numerically demonstrate a variety of broadband optical waveguide modulators based on the hybrid surface plasmon polariton (HSPP) concept for near-infrared applications. The modulator is composed of strongly coupled double-layer graphene and double rectangle cross-sectional metal nanoribbons separated by three Al2O3 spacers, which are interpolated in a SiO2 waveguide. Owing to the unique strong coupling of HSPPs between metal nanoribbons, the subwavelength confinement, the in-plane electric field component, the light-graphene interaction, and the modulation effect of the modulator are significantly enhanced. The results show the proposed modulator achieves an outstanding performance with a modulation depth (MD) over 2.3 dB µm-1 and a small normalized mode area of ∼10-5 in a wide range of wavelength from 1.3 to 1.8 µm. By optimizing the separation of the double rectangle metal nanoribbons at the telecommunication wavelength of 1.55 µm, the modulator exhibits a high MD of 3.12 dB µm-1, a small footprint of 1.8 µm2, an ultra-wide 3 dB modulation bandwidth of 380.23 GHz, and an ultra-low energy consumption of 29.39 fJ per bit. Furthermore, we also demonstrate a modulator based on two properly apart semicircular (rhombus) metal nanoribbons with a drastically enhanced MD of 11.3 (6.32) dB µm-1 at 1.55 µm. Benefitting from the strong subwavelength confinement and excellent broadband modulation performance, the proposed optical waveguide modulators offer a significant potential to realize various long-wave near-infrared integrated modulators, interconnects and optoelectronic devices.

A hybrid method to simulate elastic wave scattering of three-dimensional objects.

A hybrid method based on the finite-difference method and equivalence principle to simulate elastic wave scattering of three-dimensional objects is proposed. In this method, the near fields are first calculated in a rectangular volume containing the object by the finite-difference method. Then the displacements and tractions on a virtual surface are transformed to the far field by the application of the equivalence principle in elastodynamics. The feasibility is verified by comparing modeling results with the analytical solution for the canonical point force source radiation problem. Modeling for complex scatterer structures shows the advantage of this method in handling multi-scale scattering problems.

Frequency-Reconfigurable Wide-Angle Terahertz Absorbers Using Single- and Double-Layer Decussate Graphene Ribbon Arrays.

We propose and numerically demonstrate two novel terahertz absorbers made up of periodic single- and double-layer decussate graphene ribbon arrays. The simulated results show that the proposed absorbers have narrowband near-unity terahertz absorption with ultra-wide frequency reconfiguration and angular stability. By tuning the Fermi level of graphene ribbons, the over 90% absorbance peak frequency of the absorber with single-layer graphene structure can be flexibly adjusted from 6.85 to 9.85 THz for both the transverse magnetic (TM) and transverse electric (TE) polarizations. This absorber with single-layer graphene demonstrates excellent angular stability with the absorbance peaks of the reconfigurable absorption bands remaining over 99.8% in a wide angle of incidence ranging from 0 to 70°. The tuning frequency can be significantly enhanced by using the absorber with double-layer graphene structure from 5.50 to 11.28 THz and 5.62 to 10.65 THz, approaching two octaves under TM and TE polarizations, respectively. The absorbance peaks of the reconfigurable absorption band of this absorber for both polarizations maintain over 70%, even at a large angle of incidence up to 70°. Furthermore, an analytical fitting model is also proposed to accurately predict the absorbance peak frequencies for this variety of absorbers. Benefitting from these attractive properties, the proposed absorber may have great potential applications in tunable terahertz trapping, detecting, sensing, and various terahertz optoelectronic devices.