Search Results (153)

Electromagnetic (EM) metamaterials have a wide range of applications due to their unique properties, but their design is often based on specific topological structures, which come with certain limitations. Designing with stochastic topologies can provide more diverse EM properties. However, this requires experienced designers to search and optimise in a vast design space, which is time-consuming and requires substantial computational resources. In this paper, we employ a deep learning network agent model to replace time-consuming full-wave simulations and quickly establish the mapping relationship between the metamaterial structure and its electromagnetic response. The proposed framework integrates a Convolutional Block Attention Module-enhanced Variational Autoencoder (CBAM-VAE) with a Transformer-based predictor. Incorporating CBAM into the VAE architecture significantly enhances the model’s capacity to extract and reconstruct critical structural features of metamaterials. The Transformer predictor utilises an encoder-only configuration that leverages the sequential data characteristics, enabling accurate prediction of electromagnetic responses from latent variables while significantly enhancing computational efficiency. The dataset is randomly generated based on the filling rate of unit cells, requiring only a small fraction of samples compared to the full design space for training. We employ the trained model for the inverse design of metamaterials, enabling the rapid generation of two cells for 1-bit coding metamaterials. Compared to a similarly sized metallic plate, the designed coding metamaterial radar cross-section (RCS) reduces by over 10 dB from 6 to 18 GHz. Simulation and experimental measurement results validate the reliability of this design approach, providing a novel perspective for the design of EM metamaterials. Full article

In order to establish a general design methodology for water-based electromagnetic metamaterial absorber microstructures, a topology optimization method for water-based metamaterial absorber microstructures design was proposed in this paper. According to Mie resonance and impedance matching theory, the realization mechanism and physical model of the broadband water-based metamaterial absorber were constructed. The highest average in-band absorption rate was taken as the design object; the topological optimization model for water-based metamaterial absorber design was established. A metamaterial absorber microstructure with 16 discretized water columns inside the unit cell was designed as an example. The obtained structure exhibited a very high average in band absorption rate in the specific frequency band. The proposed method was a collaborative optimization approach that employed a single type of design variable, namely water column height, to simultaneously adjust surface impedance matching and specific resonant modes. It provided a feasible method for achieving the highest average absorption rate within a specific band. Full article

We design a one-dimensional magnetoelastic phononic crystal slab composed of the smart magnetostrictive material Terfenol-D and pure tungsten. Band inversion and topological phase transitions are achieved by modifying the geometric parameters of the non-magnetic medium within the unit cell. The emergence of topological interface states within overlapping bandgaps, exhibiting distinct topological properties, along with their robustness against interfacial structural defects, is confirmed. The coupling effects between adjacent topological interface states in a sandwich-like supercell configuration are investigated, and their tunability under external magnetic fields is demonstrated. A Su-Schrieffer-Heeger (SSH) phononic crystal slab system under gradient magnetic fields is proposed. Critically, and in stark contrast to previous static or structurally graded designs, we achieve reconfigurable rainbow trapping of topological interface states solely by reprogramming the gradient magnetic field, leaving the physical structure entirely unchanged. This highly localized, compact, and broadband-tunable topological rainbow trapping system design holds significant promise for applications in elastic energy harvesting, wave filtering, and multi-frequency signal processing. Full article

Inference of the interactive network structure of the physical world that is captured by nonlinear dynamic systems is a long-standing goal for machine learning. Existing inference methods have shown limited incorporation of physical system information and solver interaction capabilities. We present a comprehensive Physical Information based Solver-Interactive (PISI) network structure identification framework that incorporates network topology, physical constraints, and bidirectional solver interaction in nonlinear dynamical systems. To this end, we first develop a physical information-based graphical neural network (PIGNN). The PIGNN cells are embedded as the basic integration units to iterative interact with dynamical solver. The dynamical systems’s physical information can be flexibly added to the iterative interaction for PIGNN training. The above stages are trained end-to-end using a Runge–Kutta solver. The network structure inferring capability of the proposed framework is demonstrated through two kuramoto systems. Our PISI methodology, integrating graph topology, physical constraints, and solver interactivity shows advantages in trajectory prediction and structure reconstruction compared to state-of-the-art methods. Full article

The characterization and mapping of urban landscape spatial form are critical for advancing sustainable planning and informed environmental management. From a morphometric perspective, this study introduces a novel, data-driven framework for typo-morphological analysis. First, morphological cells (MCs) are defined as objectively and universally applicable spatial units for morphometric investigation. Second, by integrating a multi-dimensional cognition of full-scale morphological and associated landscape elements, we construct a set of 48 spatial form indicators and attach them to morphological cells, enabling a precise description of each unit. Third, a Gaussian mixture model (GMM) is employed to cluster the metrical information within the spatially lagged context derived from the topological structure of the morphological cells, resulting in the delineation of distinct typo-morphological zones (TMZs). We then adopt Ward’s algorithm to establish a hierarchical relationship among identified urban landscape types. Using Wuxi City, China, as a case study, our results demonstrate the effectiveness of the proposed framework in capturing the heterogeneity and underlying connotation of urban landscape spatial characteristics. Building upon the unsupervised clustering results, we further apply the classification and regression tree (CART) to provide a supervised interpretation of the key spatial form conditions driving typological decisions. It facilitates the systematic identification of the components and formative mechanisms of spatial form. The findings contribute a scalable, reproducible, and interpretable typo-morphometric approach for analyzing urban landscape spatial characteristics, thereby providing a robust quantitative foundation for integrated decision-making in landscape planning, socio-ecological assessment, and urban design practices. More broadly, the study carries both applied and theoretical significance for advancing refined urban governance and fostering interdisciplinary research related to urban sustainable development. Full article

Given the decline in fossil energy reserves and the need for less pollution, achieving carbon zero is challenging in major industrial sectors. However, the emergence of large-scale hydrogen production systems powered by renewable energy sources offers an achievable option for carbon neutrality in specific applications. When combined with energy storage systems, static power converters are crucial in these production systems. This paper offers a comprehensive review of various power converter topologies, focusing on AC– and DC–bus architectures that interface battery storage units, electrolyzers, and fuel cells. The evaluation of DC/AC, AC/DC, and DC/DC converter topologies, considering cost, energy efficiency, control complexity, power level suitability, and power quality, represents a significant advancement in the field. Furthermore, the subsequent exploration of battery aging behavioral modeling, characterization methods, and real-time parameter estimation of the battery’s equivalent electrical circuit model enhances our understanding of these systems. Large-scale hydrogen production systems most often use an AC–bus architecture. However, DC–bus configuration offers advantages over AC–bus architecture, including high efficiency, simpler energy management, and lower system costs. In addition, MVDC or HVDC DC/DC converters, including isolated and non-isolated designs based on multiple cascaded DABs and MMC-type topologies, have also been studied to adapt the DC–bus to loads. Finally, this work summarizes several battery energy storage projects in the European Union, specifically supporting the large-scale integration of renewable energy sources. It also provides recommendations, discussion results, and future research perspectives from this study. Full article

We propose a single-phase chiral elastic metamaterial capable of simultaneously exhibiting negative effective mass density and negative bulk modulus in the ultrasonic frequency range. The unit cell consists of a regular hexagonal frame connected to a central circular mass through six obliquely oriented, slender aluminum beams. The design avoids the manufacturing complexity of multi-phase systems by relying solely on geometric topology and chirality to induce dipolar and rotational resonances. Dispersion analysis and effective parameter retrieval confirm a double-negative frequency region from 30.9 kHz to 34 kHz. Finite element simulations further demonstrate negative refraction behavior when the metamaterial is immersed in water and subjected to 32 kHz and 32.7 kHz incident plane wave. Equifrequency curves (EFCs) analysis shows excellent agreement with simulated refraction angles, validating the material’s double-negative performance. This study provides a robust, manufacturable platform for elastic wave manipulation using a single-phase metallic metamaterial design. Full article

This study compares the heat transfer and pressure drop of three cell structures, namely Kelvin cells (KCs), ellipsoidal Kelvin cells (EKCs), and body-centered cubic (BCC) structures, at the cell scale in order to identify the superior configuration. Then, we conducted numerical simulations on the heat exchangers based on porous media, and evaluate their comprehensive performance. It is shown that KCs have a superior heat transfer. Their volumetric heat transfer coefficient (h_V) is more than 50% higher than that of EKCs and more than 100% higher than that of BCC structures. EKCs exhibit a lower pressure drop. In the heat exchanger performance optimization study, the Kelvin structure demonstrated significant heat transfer characteristics. Simulation data show that the heat transfer performance at the hot end of the Kelvin heat exchanger (KCHE) is enhanced by more than 40% compared to the conventional plate-fin structure (FHE), but its flow channel pressure drop characteristics show a significant nonlinear increase. It is noteworthy that the improved Kelvin heat exchanger (EKCHE), optimized by introducing elliptic cell topology, maintains heat transfer while keeping the pressure loss increase within 1.22 times that of the conventional structure. The evaluation of the heat transfer and pressure drop characteristics is consistent for both scales. In addition, the EKC configuration exhibits a superior overall heat transfer capacity. To summarize, this work proposes a systematic numerical framework encompassing cell unit screening through heat exchanger design, offering valuable guidance for the structured development and analysis of porous media heat exchangers in relevant engineering domains. Full article

Direct methanol fuel cells (DMFCs) represent a promising pathway for energy conversion, yet their reliance on platinum-group metal (PGM)-based anode catalysts poses critical sustainability challenges, which stem from finite mineral reserves, environmentally detrimental extraction processes, and prohibitive lifecycle costs. Current anode catalysts for DMFCs are dominated by platinum materials; therefore, this review systematically evaluates the following three emerging eco-efficient design paradigms using platinum materials as a starting point: (1) the atomic-level optimization of low-Pt alloy surfaces to maximize catalytic efficiency per metal atom, (2) Earth-abundant transition metal compounds (e.g., nitrides and sulfides) and coordination-tunable metal–organic frameworks as viable PGM-free alternatives, and (3) mechanically robust carbon architectures with engineered topological defects that enhance catalyst stability through covalent metal–carbon interactions. Through comparative analysis with pure Pt benchmarks, we critically examine how these strategic material innovations collectively mitigate CO intermediate poisoning risks and improve electrochemical durability. Such fundamental advances in catalyst design not only address immediate technical barriers, but also establish essential material foundations for the development of DMFC technologies compatible with circular economy frameworks and United Nations Sustainable Development Goal 7 targets. Full article

The crystal–chemical behavior of two layered titanosilicate minerals with porous crystal structures, kupletskite, K₂NaMn₇²⁺Ti₂(Si₄O₁₂)₂O₂(OH)₄F, and kupletskite-(Cs), Cs₂NaMn₇²⁺Ti₂(Si₄O₁₂)₂O₂(OH)₄F, was investigated under high-temperature conditions using single-crystal and powder X-ray diffraction; infrared and optical absorption spectroscopy and electron-microprobe analysis. Both minerals undergo topotactic transformation to dehydroxylated and oxidized high-temperature (HT) modifications at temperature above 500 °C while maintaining the basic bond topology of the astrophyllite structure-type. The high-temperature structures show contraction of the unit-cell parameters similar to that of Fe²⁺-dominant astrophyllite, indicating that Mn²⁺ oxidizes along with Fe²⁺ in M(2)–M(4) sites. The oxidation of Mn²⁺ is confirmed by the increase of the Mn³⁺-related absorption (in optical spectra) that is inversely correlated with the intensity of O–H bands in the infrared spectra. The Fe,Mn-oxidation is also evident by the contraction of the M(2), M(3), and M(4)O₆ octahedra. The M(1)–O bond length increases slightly, indicating a preference for mono- and divalent cations to occupy the M(1) site in the heated structure; this may be due to site-selective oxidation and/or migration of unoxidized cations (as previously shown for lobanovite) to this site. The role of extra framework A-site cations (K, Cs) in thermal expansion of these minerals is discussed. Full article

This study presents a comparative analysis of the influence of open-cell and closed-cell topologies on the manufacturing quality and resultant elasticity of 3D printed thermoplastic polyurethane (TPU) lattice structures. Lattice samples were designed based on various open-cell and closed-cell configurations, varying in unit cell size and fabricated using extrusion-based additive manufacturing (AM) techniques. A microscopic analysis was conducted to assess manufacturing defects, while mechanical compression tests were performed to characterize the elasticity of the samples. The correlation between the obtained results enabled the evaluation of the relationship between the manufacturability of lattice topologies and their stiffness. The findings reveal substantial differences in the manufacturability of the topologies, with open-cell structures exhibiting more pronounced defects. Additionally, the unit cell size and the resulting density of the samples were found to provide design advantages, as closed-cell topologies demonstrated superior load resistance. The accumulation of manufacturing defects was identified as a critical factor influencing deviations in stiffness measurements. This study establishes a foundational framework for lattice structural design, emphasizing the impact of cell topology and unit cell size on mechanical performance. The significance of this research lies in its contribution to the optimization of 3D printed TPU-based lattice structures, providing valuable insights for product design applications. Full article

This study introduces a topological photonic slow-light waveguide based on a honeycomb unit cell, which allows for the convenient tuning of the group index and bandwidth through the valley-locked effect. The topological properties of the unit cell are initially assessed. By adjusting the air gap in the topologically protected photonic crystal (PhC) waveguide, it is possible to continuously vary the group index from 47 to 6 and the normalized group index–bandwidth product (NGBP) from 0.495 to 0.573. Furthermore, the chiral propagation characteristics and propagation loss of the topologically protected PhC waveguide are evaluated. The findings indicate that the structure supports chiral propagation and maintains a high transmission rate even after passing through sharp corners. The results contribute to a deeper understanding of topological photonics and suggest potential for applications in future photonic technologies, such as dynamic topological photonic retarders and nonlinear localization enhancers. Full article

Lattice structures have the characteristics of light weight, excellent heat dissipation and mechanical properties. Because of excellent properties, lattice structures have been widely used in aerospace, automobile manufacturing, biomedical and other fields. At present, additive manufacturing is the mainstream method for manufacturing lattice structures. This study reviews the existing literature on additive manufacturing of lattice structures, introduces manufacturing methods, and summarizes the influencing factors of forming quality. In addition, the topology optimization of the unit cell and the gradient design of the lattice structure are discussed, and the future research direction of the lattice structure is proposed. Full article

Shapes and topologies of lattice materials have been extensively studied, yet very few studies have dealt with shapes inspired by ancient mathematicians, such as the Platonic solids discovered by Plato in 360 BC or the mathematical behavior of the unexplored “semi-regular” solids of Pacioli (1445–1517). Using the finite element analysis method, the buckling and post-buckling behavior of Platonic and Paciolian cells subjected to a compressive load were analyzed. In these solids, the energy absorbed per unit mass is an increasing function with the number of faces, similar to porosity, which reaches a maximum value for solids comprised of 90–100 surfaces. Full article

One of the issues the modern hip implants face is that one side of the implant may detach due to stretching during its use. This leads to implant transverse compression and separation from the bone. This issue can be solved by using complex implants having one of the sides made of auxetic meta-biomaterials with negative Poisson’s ratio. On the contrary, the cross-section of such materials being stretched will increase, which results in bone growth stimulation and minimum possibility of implant detachment. The aim of this paper is to design and fabricate titanium alloy auxetic meta-biomaterials based on 3D unit cells with three types of topologies. The works involved computer simulation to determine the expected properties of the samples. The samples were fabricated by the selective laser melting method and their properties were determined. Auxetic meta-biomaterials with Poisson’s ratio values of −0.09 and −0.003 and elastic modulus values typical for a human trabecular bone were fabricated in the course of the works. Full article