Direct observation of ideal electromagnetic fluids

Near-zero-index (NZI) media have been theoretically identified as media where electromagnetic radiations behave like ideal electromagnetic fluids. Within NZI media, the electromagnetic power flow obeys equations similar to those of motion for the velocity field in an ideal fluid, so that optical turbulence is intrinsically inhibited. Here, we experimentally observe the electromagnetic power flow distribution of such an ideal electromagnetic fluid propagating within a cutoff waveguide by a semi-analytical reconstruction technique. This technique provides direct proof of the inhibition of electromagnetic vorticity at the NZI frequency, even in the presence of complex obstacles and topological changes in the waveguide. Phase uniformity and spatially-static field distributions, essential characteristics of NZI materials, are also observed. Measurement of the same structure outside the NZI frequency range reveals existence of vortices in the power flow, as expected for conventional optical systems. Therefore, our results provide an important step forward in the development of ideal electromagnetic fluids, and introduce a tool to explore the subwavelength behavior of NZI media including fully vectorial and phase information. © 2022, The Author(s).Y.L. acknowledges partial support from National Natural Science Foundation of China (NSFC) under grant 62022045. I.L. acknowledges support from Ramón y Cajal fellowship RYC2018-024123-I and project RTI2018-093714-301J-I00 sponsored by MCIU/AEI/FEDER/UE and ERC Starting Grant 948504

Equirectangular image construction method for standard CNNs for Semantic Segmentation

360{\deg} spherical images have advantages of wide view field, and are typically projected on a planar plane for processing, which is known as equirectangular image. The object shape in equirectangular images can be distorted and lack translation invariance. In addition, there are few publicly dataset of equirectangular images with labels, which presents a challenge for standard CNNs models to process equirectangular images effectively. To tackle this problem, we propose a methodology for converting a perspective image into equirectangular image. The inverse transformation of the spherical center projection and the equidistant cylindrical projection are employed. This enables the standard CNNs to learn the distortion features at different positions in the equirectangular image and thereby gain the ability to semantically the equirectangular image. The parameter, {\phi}, which determines the projection position of the perspective image, has been analyzed using various datasets and models, such as UNet, UNet++, SegNet, PSPNet, and DeepLab v3+. The experiments demonstrate that an optimal value of {\phi} for effective semantic segmentation of equirectangular images is 6{\pi}/16 for standard CNNs. Compared with the other three types of methods (supervised learning, unsupervised learning and data augmentation), the method proposed in this paper has the best average IoU value of 43.76%. This value is 23.85%, 10.7% and 17.23% higher than those of other three methods, respectively

Geometry-independent antenna based on Epsilon-near-zero medium

It is well known that electromagnetic radiation from radiating elements (e.g., antennas, apertures, etc.) shows dependence on the element’s geometry shape in terms of operating frequencies. This basic principle is ubiquitous in the design of radiators in multiple applications spanning from microwave, to optics and plasmonics. The emergence of epsilon-near-zero media exceptionally allows for an infinite wavelength of electromagnetic waves, manifesting exotic spatially-static wave dynamics which is not dependent on geometry. In this work, we analyze theoretically and verify experimentally such geometry-independent features for radiation, thus presenting a novel class of radiating resonators, i.e., antennas, with an operating frequency irrelevant to the geometry shape while only determined by the host material’s dispersions. Despite being translated into different shapes and topologies, the designed epsilon-near-zero antenna resonates at a same frequency, while exhibiting very different far-field radiation patterns, with beams varying from wide to narrow, or even from single to multiple. Additionally, the photonic doping technique is employed to facilitate the high-efficiency radiation. The material-determined geometry-independent radiation may lead to numerous applications in flexible design and manufacturing for wireless communications, sensing, and wavefront engineering. © 2022, The Author(s).Y.L. acknowledges partial support from National Natural Science Foundation of China (NSFC) under grant 62022045, and in part by supported by Tsinghua University Initiative Scientific Research Program. I.L. acknowledges support from Ramón y Cajal fellowship RYC2018-024123-I, project RTI2018-093714-301J-I00 sponsored by MCIU/AEI/FEDER/UE, and ERC Starting Grant 948504

Dispersion coding of ENZ media via multiple photonic dopants

Epsilon-near-zero (ENZ) media are opening up exciting opportunities to observe exotic wave phenomena. In this work, we demonstrate that the ENZ medium comprising multiple dielectric photonic dopants would yield a comb-like dispersion of the effective permeability, with each magnetic resonance dominated by one specific dopant. Furthermore, at multiple frequencies of interest, the resonant supercouplings appearing or not can be controlled discretely via whether corresponding dopants are assigned or not. Importantly, the multiple dopants in the ENZ host at their magnetic resonances are demonstrated to be independent. Based on this platform, the concept of dispersion coding is proposed, where photonic dopants serve as “bits” to program the spectral response of the whole composite medium. As a proof of concept, a compact multi-doped ENZ cavity is fabricated and experimentally characterized, whose transmission spectrum is manifested as a multi-bit reconfigurable frequency comb. The dispersion coding is demonstrated to fuel a batch of innovative applications including dynamically tunable comb-like dispersion profiled filters, radio-frequency identification tags, etc.© 2022, The Author(s).Y.L. acknowledges partial support from the National Natural Science Foundation of China (NSFC) under grant 62022045, and in part by the Beijing Nova Program of Science and Technology under Grant Z191100001119082, as well as the support from the Beijing National Research Center for Information Science and Technology. I.L. acknowledges support from project RTI2018-093714-J-I00 sponsored by MCIU/AEI/FEDER/UE

Study on the damage law of coal rock affected by different alternating periods of cold and heat

Temperature is an important factor affecting the physical properties of coal and rock, and as a solid medium, coal and rock have the properties of thermal expansion and contraction. The alternation of cold and heat will cause irreversible damage to the coal rock due to deformation, which will eventually lead to the damage and destruction of the original fracture structure of the coal rock. In order to study the damage law of coal and rock affected by different alternating cycles of cold and heat, the long-flame coal in Fuxin area of Liaoning Province was selected to make a cube specimen with a size of 100 mm×100 mm×100 mm. The mechanical parameters and surface dimensions of the coal samples before and after the experiment were measured by using the research method of reciprocating the application of temperature loads in a low temperature storage box(–15 °C) and room temperature(20 °C). Furthermore, the expansion law and damage mechanism of the coal sample fracture structure with the alternating cycle of cooling and heating are revealed. The results show ① The coal sample cracks expand and expand under the alternating action of cold and heat, and the expansion amount and expansion rate of the cracks on the surface of the coal sample gradually increase with the cycle of the alternating cycle of cold and heat. ② The mechanical properties of coal samples are weakened under the action of multi-cycle temperature loads, the damage is serious, and the compressive strength of coal samples gradually decreases with the cycle of alternating cycles of cold and heat. ③ The damage mechanics model of coal sample structure is established by ABAQUS software, and the simulation results are in good agreement with the experimental results. The overall structural damage degree of the coal sample is aggravated, indicating that the alternating action of cold and heat is an important factor for the structural damage of the coal sample

Overcoming the Size Limit of First Principles Molecular Dynamics Simulations with an In-Distribution Substructure Embedding Active Learner

Large-scale first principles molecular dynamics are crucial for simulating complex processes in chemical, biomedical, and materials sciences. However, the unfavorable time complexity with respect to system sizes leads to prohibitive computational costs when the simulation contains over a few hundred atoms in practice. We present an In-Distribution substructure Embedding Active Learner (IDEAL) to enable efficient simulation of large complex systems with quantum accuracy by maintaining a machine learning force field (MLFF) as an accurate surrogate to the first principles methods. By extracting high-uncertainty substructures into low-uncertainty atom environments, the active learner is allowed to concentrate on and learn from small substructures of interest rather than carrying out intractable quantum chemical computations on large structures. IDEAL is benchmarked on various systems and shows sub-linear complexity, accelerating the simulation thousands of times compared with conventional active learning and millions of times compared with pure first principles simulations. To demonstrate the capability of IDEAL in practical applications, we simulated a polycrystalline lithium system composed of one million atoms and the full ammonia formation process in a Haber-Bosch reaction on a 3-nm Iridium nanoparticle catalyst on a computing node comprising one single A100 GPU and 24 CPU cores