3D Unit Research Articles

Exploring the Relationship Between 2D/3D Convolution for Hyperspectral Image Super-Resolution

Hyperspectral image super-resolution (SR) methods based on deep learning have achieved significant progress recently. However, previous methods lack the joint analysis between spectrum and horizontal or vertical direction. Besides, when both 2D and 3D convolution are in the network, the existing models cannot effectively combine the two. To address these issues, in this article, we propose a novel hyperspectral image SR method by exploring the relationship between 2D/3D convolution (ERCSR). Our method alternately employs 2D and 3D units to solve the problem of structural redundancy by sharing spatial information during reconstruction for existing model, which can enhance the learning ability of 2D spatial domain. Importantly, compared with the network using 3D units, i.e., 2D units are replaced by 3D units, it can not only reduce the size of the model but also improve the performance of the model. Furthermore, to exploit the spectrum fully, the split adjacent spatial and spectral convolution (SAEC) is designed to parallelly explore information between spectrum and horizontal or vertical direction in space. Experiments on widely used benchmark datasets demonstrate that the proposed approach outperforms state-of-the-art SR algorithms across different scales in terms of quantitative and qualitative analysis.

Enhanced Invariance Class Partitioning using Discrete Curvatures and Conformal Geometry

Mesh models have been widely employed in current CAD/CAM systems, where the workpiece is considered as made up of a number of features limited by natural boundaries. The natural boundaries among features are in most cases edges where an abrupt change of point differential geometry properties occurs. However, such features and underlying surface portions could also be connected smoothly without an abrupt change at the natural boundaries. In the context of ISO GPS (Geometrical Product Specifications and Verification) Standards, partitioning is a fundamental operation that decomposes a mechanical part into independent surface portions for a functional specification purpose. In this paper, an enhanced mesh partitioning method is proposed to enable a feature-based decomposition considering kinematic invariance classes. The proposed two-step method includes an initial partitioning based on sharp edge detection and an enhanced partitioning process based on non-sharp edge rectification. The partitioning criteria rely on two surface descriptors derived from shapes’ principal curvatures: Curvedness and Shape Index. To refine the boundary points on non-sharp edges, conformal geometry is exploited during the enhanced partitioning process by mapping the 3D surface onto a 2D unit disk. Connecting regions without abrupt changes at their natural boundaries are well partitioned after the boundary rectification process. A statistical evaluation process is used to address invariance class identification for each partitioned surface portion on the part. Experiments and results on different mesh models are presented to demonstrate the effectiveness of invariance class partitioning for ISO GPS.

Experimental and numerical upscaling of foam flow in highly permeable porous media

Foam in porous media has been studied as a tool for various applications. Recently, the technology has become relevant for contaminated-aquifer remediation, where porous media are highly permeable. Therefore, the behavior of foam flow in high permeability porous media still raises numerous questions. In particular, upscaling of the foam flow from pore to Darcy scale is still under debate. Since the behavior of bulk foam has been studied principally in the food and cosmetics industries, and foam flow in porous media has mainly been investigated in the oil industry, the link between bulk-foam behavior and foam flow in porous media is still missing. The upscaling of foam flow from the pore scale to the laboratory scale could give valuable insight for understanding foam flow in aquifers.We studied the behavior of pre-generated foam with different foam qualities through the rheological characterization of bulk foam using a rheometer and also when flowing in a porous medium composed of 1 mm glass beads. Foam was formed by co-injecting surfactant solution and nitrogen gas through a porous column filled by fine sand. The homogenization method is used to study macroscopic foam flow properties in porous media by solving the non-linear boundary value problem. The rheology of bulk foam is then used as an input in the upscaling procedure for foam flow in different periodic model 2D and 3D unit cells.From our experiments, we found that the bulk foam is a yield-stress fluid and that the yield-stress values increase with foam quality. Moreover, the rheology of bulk foam corresponds well to the yield stress (Herschel-Bulkley-Papanastasiou) model. We found that foam behaves as a continuous yield-stress fluid in highly permeable porous media. It was also shown that the apparent foam viscosity in porous media increases with the foam quality at the same total flow rate. The results obtained from the rheometer successfully match the outcomes of apparent foam viscosity obtained by flow in porous media by a shifting parameter for the same foam quality. The apparent foam viscosity found in 1 mm glass-bead packing was much higher than bulk foam viscosity.Experimental results were compared to numerical results on simple unit cells. Although we observed considerable differences between the experimental and numerical results of upscaling, the general trend was identical. The differences can be explained by the complexity of the foam flow in porous media, especially foam compressibility. We found that foam flow at low capillary numbers is influenced by the trapping effect and at high pressure gradients by the compressibility. Compressibility was estimated for foam flow in 1 mm glass-bead packing. When foam compressibility is insignificant, the upscaling model can predict foam-flow behavior well at the Darcy scale.

2D-Planar decorated 3D-network enables strong synergistic mechanics and programmable shape transformations for alginate-based hydrogels

Simultaneously enhancing the strength and toughness of physically crosslinked hydrogels is imperative as structural materials, especially for those from natural sources. Herein, inspired by the principle of synergistic effect, a facile yet effective strategy is developed to construct the two-dimensional planar decorated 3D network (2D-3D) in ionic-crosslinked alginate-based hydrogels, generating the strong synergistic mechanics. The strategy is based on a novel hybrid crosslinker (trivalent/divalent cations, e.g. Fe3+/Ca2+) with very low percentage of Fe3+ (1%), which surprisingly imparts multivalent cations with a balanced complexation competition in the hydrogels and thus co-joints loose 2D and rigid 3D structure units in a tightest matching manner. Using the approach in popular Ca-alginate/polyacrylamide system, the complementary architecture induces a 6-fold increase in yield strength accompanied with improved toughness, breaking its mechanical limitations. By varying the molar percentage of each cation in the primary crosslinker, their association abilities with the hydrogels are precisely tuned, giving architectures and mechanics over a wide range. Additionally, the diverse categories of hybrid crosslinkers become the ideal candidates for the development of programmable stimuli-responsive hydrogels, e.g., interesting reverse and unidirectional shape transformations. The method offers a new path in designing metal–ligand coordinated materials, which will certainly become popular in fabricating new generation of alginate-based hydrogels.

Surface-Induced 2D/1D Heterostructured Growth of ReS2/CoS2 for High-Performance Electrocatalysts.

Two-dimensional/one-dimensional (2D/1D) heterostructures have received much attention from researchers for their abundant catalytically active sites and low contact resistance due to formation of chemical bonds at the interface. The investigation of such heterostructures, however, is confined to lattice-matched materials, which severely limits the material candidates. Herein, we demonstrate a lattice-mismatched 2D/1D heterostructured electrocatalyst consisting of 2D ReS2 nanosheets and 1D CoS2 nanowires. We propose that the higher surface energy of the CoS2 nanowire and the lattice mismatch between 1D and 2D units are crucial for the growth process of ReS2 nanosheets. More importantly, the terminal S2- exposed on the surface of CoS2 nanowires serves not only as the nucleus of ReS2 nanosheets but also as a bridge to enhance electron transport efficiency. Thus, the ReS2/CoS2 heterostructures show outstanding hydrogen evolution reaction performance. This work is of general interest for the design of complex multidimensional nano-heterostructures with outstanding functionalities.

Mixed 2D/3D Convolutional Network for Hyperspectral Image Super-Resolution

Deep learning-based hyperspectral image super-resolution (SR) methods have achieved great success recently. However, there are two main problems in the previous works. One is to use the typical three-dimensional convolution analysis, resulting in more parameters of the network. The other is not to pay more attention to the mining of hyperspectral image spatial information, when the spectral information can be extracted. To address these issues, in this paper, we propose a mixed convolutional network (MCNet) for hyperspectral image super-resolution. We design a novel mixed convolutional module (MCM) to extract the potential features by 2D/3D convolution instead of one convolution, which enables the network to more mine spatial features of hyperspectral image. To explore the effective features from 2D unit, we design the local feature fusion to adaptively analyze from all the hierarchical features in 2D units. In 3D unit, we employ spatial and spectral separable 3D convolution to extract spatial and spectral information, which reduces unaffordable memory usage and training time. Extensive evaluations and comparisons on three benchmark datasets demonstrate that the proposed approach achieves superior performance in comparison to existing state-of-the-art methods.

Comparative study on electrochemical charge storage behavior of FeCo2S4 electrodes with different dimensional nanostructures

The deep understanding of the electrochemical behavior of active materials is essential for the design of high-performance electrochemical energy storage devices. Herein, nanostructured FeCo2S4 electrodes with different dimensional morphologies [i.e., one dimensional nanoneedles (1D FeCo2S4), two dimensional nanosheets (2D FeCo2S4), and three dimensional structures consisting of nanosheets grafting on nanoneedles (3D FeCo2S4)] were in situ grown on carbon cloth via a robust hydrothermal strategy. Subsequently, the electrochemical charge storage behavior of such three FeCo2S4 electrodes was carefully investigated and analyzed through several electrochemical methods. It was revealed that the 3D FeCo2S4 electrode exhibited a considerable higher specific capacity (92.88 mAh g−1) as compared with 1D (58.42 mAh g−1) and 2D (26.00 mAh g−1) electrodes at a current density of 1 A g−1, which was mainly due to the superior charge transport characteristic from the rational combination between 1D and 2D units. Additionally, the 3D FeCo2S4 electrode indicated great stability in the cycling tests (∼82% capacity retention after 11200 cycles at 5 A g−1). Moreover, the quantitative calculation of the capacitive and diffusion-controlled contribution of three electrodes was performed to deep distinguish their electrochemical behavior based on different architectures. Thus, the design of 3D nanostructured electrodes will be an effective strategy to exploit high-performance electrochemical energy storage devices.

Self-Assembly Properties of Solution Processable, Electroactive Alkoxy, and Alkylthienylene Derivatives of Fused Benzoacridines: A Scanning Tunneling Microscopy Study.

Self-organization in mono- and bilayers on HOPG of two groups of benz[5,6]acridino[2,1,9,8-klmna]acridine derivatives, namely, 8,16-dialkoxybenzo[h]benz[5,6]acridino[2,1,9,8-klmna]acridines with an increasing alkoxy substituent length and 8,16-bis(3- or 4- or 5-octylthiophen-2-yl)benzo[h]benz[5,6]acridino[2,1,9,8-klmna]acridines, i.e., three positional isomers of the same benzoacridine, is investigated by scanning tunneling microscopy. The layers were deposited from a solution of the adsorbate (in hexane or dichloromethane) and imaged ex situ at molecular resolution. In all cases, the resulting two-dimensional (2D) supramolecular organization is governed by the interactions between large, fused heteroaromatic cores that form densely packed rows separated by areas covered by substituents. In 8,16-dialkoxybenzo[h]benz[5,6]acridino[2,1,9,8-klmna]acridines, the alkoxy substituents, separating the rows of densely packed cores, are interdigitated. An increasing substituent length leads to an intuitively expected increase in this 2D unit cell parameter that corresponds to the orientation of the substituent in the monolayer. In the case of 8,16-bis(3- or 4- or 5-octylthiophen-2-yl)benzo[h]benz[5,6]acridino[2,1,9,8-klmna]acridine positional isomers, the self-assembly processes are more complex. Although the determined 2D unit cell is in all cases essentially the same, the role of alkylthienylene substituents in layer formation is distinctly different. Thus, the formation of monolayers and bilayers is very sensitive to isomerism. 8,16-Bis(5-octylthiophen-2-yl)benzo[h]benz[5,6]acridino[2,1,9,8-klmna]acridine is capable of forming the most stable monolayer and the most labile bilayer. In the case of 8,16-bis(3-octylthiophen-2-yl)benzo[h]benz[5,6]acridino[2,1,9,8-klmna]acridine, an inverse phenomenon is observed leading to the most labile monolayer and the most stable bilayer. These differences are rationalized in terms of dissimilar molecular geometries of the studied isomers and different interdigitation patterns in their 2D supramolecular structures.

An Acoustic Metamaterial-Based Sensor Capable of Multiband Filtering and Amplification

Dispersive acoustic metamaterials (AMMs) with graded refractive index is promising in acoustic sensing enhancement by providing acoustic rainbow trapping (ART) effect. However, previous solutions to this type of AMMs are based on 2D unit cells that require infinite or very large size in the third dimension; they cannot integrate with conventional acoustic sensors without deteriorating the ability of acoustic wave manipulation. In order to advance their practical applications, this paper proposes an axisymmetric, microphone embedded AMM device with gradient profile as well as gradient plate thickness and gradient gap width along the axis. Both numerical simulations and experiments are performed to examine the ART effect of the proposed AMM device and demonstrate its excellent capacity of acoustic pressure amplification and multi-band acoustic filtering. Deploying a microphone in the gap does not disturb the acoustic field, so the proposed AMM sensor experimentally achieves remarkable acoustic gains over one order of magnitude. Sound waves of different frequencies are picked up by microphones at different gaps, realizing the real-time spatially splitting of the sound spectrum. The proposed AMM provides excellent immunity to broadband noise and a little weak suppression of the single tone noise while significantly amplifying acoustic signals of a given frequency.

Image Thresholding Using the Complement Feature

A new feature (the complement feature) is proposed in an Eigen formulations for performing global image thresholding. The goal is to find an intensity or gray-level value below which is the background while above it is the foreground (object). Each pixel in the image is represented by a (2D) unit vector where the x-component is the normalized (to [0,1] or [-1,1]) intensity of the pixel, while the y-component is its complement (e.g., Euclidian L2-Norm). The correlation matrix can then constructed to find the cross-correlation, Eigen vectors (axes of inertia) and Eigen values (description of respective sizes). Several implementations for each of the three previously mentioned categories are proposed to perform image thresholding. Interestingly, some of the proposed implementations do not require exhaustive search and a direct solution can be obtained. The results are promising on a wide range of images as demonstrated by comparison with the well-known Otsu method.

Supramolecular Organization of Model Polycyclic Aromatic Molecules: Comparison of 2D and 3D Assemblies

AbstractThe spatial organization of polycyclic aromatic molecules during adhesion on a solid/liquid interface is the key event of a plethora of natural and industrial processes. Herein, we report the supramolecular assembly of violanthrone‐79—a model of asphaltenes, an intractable mixture of polycyclic aromatics from crude oil—at the solid‐liquid interface between highly oriented pyrolytic graphite (HOPG) and a hydrophobic medium (1‐phenyloctane). High‐resolution scanning tunneling microscopy revealed that molecules of violanthrone‐79 readily self‐assemble on the surface in supramolecular “nanoring” structures. The lattice parameters of the 2D unit cell are on the same order as those determined from a bulk single crystal. Transmission electron microscopy showed long‐range ordered patterns, and the spacing between the fringes is in agreement with the inter‐planar distances between aromatic cores of molecules that are helically arranged around the [001] axis in the 3D crystal. The results confirm that upon adsorption on solid/liquid interfaces, polycyclic aromatic molecules such as violanthrone‐79 form supramolecular assemblies by interaction with the substrate and self‐association, and this process could be the initial step of deposition of asphaltenes on carbonaceous oil reservoir walls and production tubing.

Characterizing Durability of PFSA Membranes of PEM Fuel Cell Based on Numerical Fatigue Crack Propagation

Fatigue crack growth in the Perfluorosulfonic-acid (PFSA) ionomer membranes with mechanical reinforcement and chemical stabilizer represents a key barrier in improving the durability of the polymer electrolyte membrane (PEM) fuel cell. Both ex-situ and in-situ Paris regime fatigue crack behaviors can be evaluated numerically based on the critical plastically dissipated energy (CPDE) ahead of the crack tip. Some fairly good agreement between the finite element (FE) computational crack predictions and the ex-situ experimental crack propagation rates have been found for different polymers in previous work1. In a similar fashion, the fatigue crack growth criteria (e.g., CPDE) of Nafion®-based ionomer membranes can be determined numerically at various environmental conditions (RH and T). The determined fatigue crack criteria, then, will be implemented in a 2D unit fuel cell FE model following the reference work2 with extensions. Thus, in-situ fatigue crack behaviors of the ionomer membranes can be evaluated in response to different operating circumstances. This numerical scheme can be used to evaluate the mechanical integrity of different ionomer membranes in the screening process by the manufacturer/buyer. Moreover, in further implementations, the results from this modeling can be used in exploring the synergy between chemical (e.g., gas-crossovers) and mechanical failures (e.g., fatigue cracks) in PEM fuel cell membranes. REFERENCES G. Ding, A. M. Karlsson, and M. H. Santare, Int. J. Fatigue, 94, 89–96 (2017) http://dx.doi.org/10.1016/j.ijfatigue.2016.09.012.G. Ding, M. H. Santare, A. M. Karlsson, and A. Kusoglu, J. Power Sources, 316, 114–123 (2016) http://dx.doi.org/10.1016/j.jpowsour.2016.03.031.

Molecular-Based Design of Microporous Carbon Nanosheets.

Microporous carbons afford high surface areas, large pore volumes, and good conductivity, and are fascinating over a wide range of applications. Traditionally synthesized microporous carbon materials usually suffer from some limitations, such as poor accessibility and slow mass transport of molecules due to the micrometer-scale diffusion pathways and space confinement imposed by small pore sizes. Two-dimensional microporous carbon materials, denoted as microporous carbon nanosheets (MCNs), possess nanoscale thickness, which allows fast mass and heat transport along the z axis; thus overcoming the drawbacks of their bulk counterparts. Herein, recent breakthroughs in the synthetic strategies for MCNs are summarized. Three typical methods are discussed in detail with several examples: pyrolysis of organic precursors with 2D units, a templating method that uses wet chemistry, and the molten salt method. Among them, molecular-based assembly of MCNs in the liquid phase shows more controllable morphology, thickness, and pore size distribution. Finally, challenges in this research area are discussed to inspire future explorations.

Time-dependent neutron diffusion coefficient for the effective diffusion equation

The time-dependency of neutron diffusion coefficient as well as neutronic interfacial coefficients in nuclear reactors at short time-scale is investigated via the volume averaging method. The boundary-value problems of governing differential equation for spatial deviations around averages of local variables are developed in this work. The general solution of spatial deviations-boundary-value problem allows closing the up-scaled neutron diffusion equation, which incorporates new terms with respect to classic equation. Meanwhile, the particular solutions of spatial deviations enable the numerical estimation of effective diffusion and neutronic interfacial coefficients. The geometrical domains where effective coefficients were numerically computed include 2D and 3D unit cells, which are representative geometries for two types of nuclear reactors: conventional arrangements with fuel rods and pebble bed. The numerical estimations were fitted to an analytical expression as function of time. The numerical solution of up-scaled model and comparison with results of direct numerical simulations are presented and discussed in this work.

Validation method for the systematization of results based on a similarity concept

The development of a functional methodological approach is presented here, to clarify a globally valid way of evaluating the precision of mathematical modeling of physical and/or chemical processes. Starting from the description of the system, a phenomenon accompanied by a disclaiming hypothesis is investigated, against which the knowledge is accumulated with time. Moreover, the possibility of the evolution of any phenomenon being interrupted when a parameter overpasses a critical threshold, after which the hypothesis is not any more valid, is introduced. This possibility should be obtained through the dependence of a selected macroscopic quantity (marker) on a specific parameter. To apply this methodology, the problem of Stokes flow through a granular medium of spheroidal grains has been selected as an indicative case study. The prolate spheroidal configuration is considered, since the results for the oblate spheroid can be recovered via a simple transformation. Therein, the three‐dimensional flow fields are initially constructed analytically via the Papkovich‐Neuber differential representation, which provides the velocity and pressure fields in terms of harmonic spheroidal eigenfunctions. Next, under the Kuwabara‐type spheroidal 2D unit cell concept, the above expressions degenerate to the axisymmetric case, and the full solution is then obtained, keeping the leading terms of the series, which are adequate for most engineering applications for specific aspect ratio of the spheroids. In the sequel, the aforementioned problem is solved numerically for a 3D extension of the same model, where this numerical solution has been achieved by using the finite volumes method, while the resulting linear systems were approximated by applying the well‐known successful over‐relaxation concept. Finally, outcomes by both models have been compared via the above methodology, resulting to objective and reliable accuracy criteria.

Study of effect of soft inclusion on the mechanical behavior of soilcrete mixtures: experimental and modeling approaches

The influence of the volume fraction and size of soft soil inclusions on the mechanical behavior of soilcretes was experimentally and numerically investigated. Spherical kaolinite chunks with a specific water content and volume were added to the soilcrete samples during the filling phase of the molds. Different mechanical properties such as the effective static elastic modulus (E) and the unconfined compressive strength (UCS) of soilcrete specimens with different volume fraction of inclusions were determined. E and UCS of soilcrete specimens with different volume fraction of inclusions were also determined using 2D (unit cell) and 3D (digital specimens) finite element models. UCS and E decrease considerably as the volume fraction of soft inclusions increases. Experimental results show that these UCS and E drops are, respectively, about 47% and 20% for a volume fraction of inclusions fv = 9%. A good agreement between the experimental and simulated data was observed, especially for elastic modulus.

Gold-potassium sheets intercalated into graphite: Chemistry and structure of a first stage ternary compound

A ternary graphite-potassium-gold compound K1.3Au1.5C4 was synthesized by immersing a pyrographite platelet in various potassium metal-based molten alloys. Numerous reaction parameters were investigated (duration, temperature, composition of the alloy) in order to determine the stability conditions of the ternary compound. Using complementary X-ray diffraction and ion beam analysis experiments, the optimal conditions of preparation of this compound have been pointed out. The composition and homogeneity were evidenced by ion beam analysis and X-ray diffraction allowed to determine its repeat distance (1311 pm) and its c-axis stacking sequence (K-Au-Au-Au-K). The 2D unit cell observed thanks to Transmission Electron Microscopy (TEM) is square with a = 1192 pm, no-commensurate with that of graphite.

On manufacturing constraints for tow-steered composite design optimization

Automatic fiber placement machines have made it viable to manufacture composites where fiber angles vary continuously—tow-steered composites. The additional freedom provided by tow-steered composites has the potential to increase structural performance; however, this approach comes with added design complexity. Numerical optimization can address this complexity, though it is critical that constraints are enforced to ensure that the resulting optimal tow-steered designs are manufacturable using current automatic fiber placement machines. In this work, we consider two manufacturing constraints: tow path curvature and gaps/overlaps. To develop these constraints, we consider a general tow-steered layer pattern as a 2D unit vector field, where the field streamlines represent the tow paths laid down by the automated fiber placing machine. This mathematical formulation provides a relationship between tow path curvature, gap/overlap propagation rate, vector curl, and divergence. These relationships also lead to a constraint on the minimum cut/add length of a tow for a given tow-steered pattern. We demonstrate the developed constraint formulations on two analytical examples, as well as on a structural optimization. We also explore the relationship between curl and divergence of rotated tow patterns. This analysis leads to the conclusion that layups featuring such patterns require strict constraints on bounds to ensure satisfaction of manufacturability requirements. Finally, we use these relationships to motivate a family of gap/overlap-free and curvature-free tow-steered patterns.

ALBATROS: adaptive line-based sampling trajectories for sequential measurements

Measurements in 2D or 3D spaces are ubiquitous among many fields of science and engineering. Often, data samples are gathered via autonomous robots or drones. The path through the measurement space and the location of the samples is traditionally determined upfront using a one-shot design of experiments. However, in certain cases, a sequential approach is preferred. For example, when dealing with a limited sampling budget or when a quick low-resolution overview is desired followed by a steady uniform increase in sampling density, instead of a slow high-resolution one-shot sampling. State-of-the-art sequential design of experiment methods are point-based and are often used to set up experiments both in virtual (simulation) as well as real-world (measurement) environments. In contrast to virtual experimentation, physical measurements require movement of a sensor probe through the measurement space. In these cases, the algorithm not only needs to optimize the sample locations and order but also the path to be traversed by sampling points along measurement lines. In this work, a sequential line-based sampling method is proposed which aims to gradually increase the sampling density across the entire measurement space while minimizing the overall path length. The algorithm is illustrated on a 2D and 3D unit space as well as a complex 3D space and the effectiveness is validated on an engineering measurement use-case. A computer code implementation of the algorithm is provided as an open-source toolbox.

Spoof surface plasmon polaritons excitation and wavefront control by Pancharatnam–Berry phase manipulating metasurface

Realizing fine control of surface plasmon polaritons (SPPs) and spoof surface plasmon polaritons (SSPPs) is highly desired in many integrated photonic and microwave applications, but the flexibility to control the wavefront of SPPs and SSPPs still need addressing. In this paper, a Pancharatnam–Berry (PB) phase manipulating metasurface (PMM) was designed to achieve SSPPs excitation and wavefront control. Under circular polarization (CP) incidence, simply by designing the rotation angle of the unit cells the reflection phase spatial distribution can be manipulated. By means of different phase profiles on the 2D unit cells array, the SSPPs can be excited with various wavefront shapes, without the need of special excitation structure pattern. Meanwhile, a plasmonic metal is also designed to support SSPPs with both TE and TM polarizations, which can efficiently guide out the energies from the input CP waves. As a proof of concept, a PB PMM composed of N-shape metallic structure was designed. Through designing the rotation of the unit cells, two typical phase profiles were designed to excite SSPPs in arbitrary slant direction or focusing. This scheme could be used to achieve SSPPs excitation with many other wavefront shapes, and would also enable promising applications in other spectra.