We present numerical simulations of scattering-type scanning near-field optical microscopy (s-SNOM) of 1D plasmonic graphene junctions. A comprehensive analysis of simulated s-SNOM spectra is ...performed for three types of junctions. We find conditions when the conventional interpretation of the plasmon reflection coefficients from s-SNOM measurements does not apply. Our approach can be used for other conducting 2D materials to provide a comprehensive understanding of the s-SNOM techniques for probing the local transport properties of 2D materials.
This study investigates lubricating performances of oils through altering the working conditions in accelerated aging tests, observing the degradations on the lubricants’ performances and ...incorporating in-time detections for verification. To meet the aims, a new measuring system has been developed to observe alterations of the recorded viscosity index, color difference, thermal coefficient and torque transmission in the oil film under electrical discharges. To resolve the quality of lubricating oil in real time, the discharging waveforms and the acoustic indexes were applied to the marginal Hilbert spectrum for characterizing the time-frequency domain features. The Fisher score of the selected features successfully differentiated the new and used lubricants. The physical effects in association with the degradations of oil films are reported in detail.
van der Waals (vdW) crystals are promising candidates for integrated phase retardation applications due to their large optical birefringence. Among the two major types of vdW materials, the ...hyperbolic vdW crystals are inherently inadequate for optical retardation applications since the supported polaritonic modes are exclusively transverse‐magnetic (TM) polarized and relatively lossy. Elliptic vdW crystals, on the other hand, represent a superior choice. For example, molybdenum disulfide (MoS2) is a natural uniaxial vdW crystal with extreme elliptic anisotropy in the frequency range of optical communication. Both transverse‐electric (TE) polarized ordinary and TM polarized extraordinary waveguide modes can be supported in MoS2 microcrystals with suitable thicknesses. In this work, low‐loss transmission of these guided modes is demonstrated with nano‐optical imaging at the near‐infrared (NIR) wavelength (1530 nm). More importantly, by combining theoretical calculations and NIR nanoimaging, the modal birefringence between the orthogonally polarized TE and TM modes is shown to be tunable in both sign and magnitude via varying the thickness of the MoS2 microcrystal. This tunability represents a unique new opportunity to control the polarization behavior of photons with vdW materials.
In a well‐designed van der Waals (vdW) waveguide, the orthogonally polarized ordinary and extraordinary guided modes can be degenerate and propagate with the same phase velocity. This means that the photons propagate through the anisotropic waveguide without altering their polarization state, just like they propagate through an isotropic bulk material. In this sense, the observed phenomenon can be summarized as “isotropy from anisotropy.”
Inspired by the sparse and hierarchical features representation in the ventral stream of the human visual system, the biologically inspired multi-scale contourlet attention network (BMCAnet) is ...proposed to extract robust discriminative features. First, we constructed the multi-scale contourlet filter banks as a population of neurons in the primary visual cortex (V1), and extracted sparse features in a multi-scale and multi-direction way. It simulated a simple cell in V1 that responds to stimuli in a specific direction. Second, in order to refine contourlet features adaptively, the Shannon block attention module (SBAM) is introduced by integrating Shannon entropy as the third branch of the channel attention module (CAM), thus the weights of contourlet coefficients can be learned adaptively. Third, the responses of the spatial and spectral features are pooled by the proposed contourlet pooling layer to obtain the invariant structure features with the specified rules, which roughly stimulate the pooling process of complex cells in the V1 area. Last, the combination of global average pooling (GAP) and full connection (FC) is used for classification. The competitive results on eight databases demonstrate that the BMCAnet can effectively extract sparse and effective features for the classification tasks.
For accurate segmentation, effective feature extraction has always been a challenging problem, since the variability of appearance and the fuzziness of object boundaries. Convolutional neural ...networks have recently gained recognition in feature representation learning. However, it is only conducted in the spatial domain, and lacks effective representation of directionality, singularity and regularity in the spectral domain for anomaly detection of images. This is the key to feature learning representation of high-order singularity. To solve this problem, a multi-scale contourlet knowledge guide learning network is proposed in this paper. It is novel in this sense that, different from the CNNs in the spatial domain, the proposed method learns the multi-scale contourlet sparse representation to obtain more effective and sparse features in multi-scales and multi-directions. Furthermore, the contourlet knowledge guide learning can enhance the representation of spectral domain features. It is shown that the proposed network can learn the multi-level discriminative features and capture the more accurate object boundaries. The segmentation ability in theoretical analysis and experiments on five polyp segmentation datasets (CVC-ColonDB, CVC-ClinicDB, Kvasir-SEG, ETIS-LaribPolypDB, EndoSceneStill) and two building datasets (Massachusetts, WHU) are compared with developed methods. It must be emphasized that there is potential in effective feature learning representation and the generalization capability of the proposed method in deep learning, recognition and interpretation.
This study investigates if the vibration frequency and amplitude, coupled with cutting parameters could reduce the thrust force in the drilling of CFRP/Al stacks. In the ANOVA and main-effect plots, ...the contributions (PCRs) of the vibrating amplitude were high (CFRP: 80.14%, Al: 48.14%). When drilling in the steady states, the interactions between the employed vibration parameters with the machine tool and the fixation system were interpreted using the empirical mode decomposition (EMD) and Fourier spectrum with appreciable results (CFRP: R2=84.1%, Al: R2=93.9%). When drilling in the CFRP layer at the cutting onsets, the resolved spectrums perfectly matched the mechanical effects in the cutting stage (19.5–1367Hz), with chattered-induced vibration (683.6 and 1367Hz). When drilling of the Al layer, the damping-induced vibration led to an increase in the background noises (39.1–117.2Hz), whereas the frequencies produced by the spindle remained largely the same.
Turbid media, made of wavelength-scale inhomogeneous particles, can give rise to many significant imaging and spectroscopy challenges. The random variation of the refractive index within such media ...distorts the spherical wavefronts, resulting in smeared and speckly images. The scattering-induced artifacts can obscure the characteristic spectral fingerprints of the chemicals in a sample. This in turn prevents accurate chemical imaging and characterization of the materials cloaked with a diffusive medium. In this work, we present a novel computational technique for creating spatially- and spectrally-resolved chemical maps through a diffusive cloak using terahertz time-domain spectroscopy. We use the maximal overlap discrete wavelet transform to obtain a multiresolution spectral decomposition of THz extinction coefficients. We define a new spectroscopic concept dubbed the “bimodality coefficient spectrum” using the skewness and kurtosis of the spectral images. We demonstrate that broadband wavelet-based reconstruction of the bimodality coefficient spectrum can resolve the signature resonant frequencies through the scattering layers. Additionally, we show that our approach can achieve spectral images with diffraction-limited resolution. This technique can be used for stand-off characterization of materials and spectral imaging in nondestructive testing and biological applications.
The modeling of the near-field interaction in the scattering-type scanning near-field optical microscope (s-SNOM) is rapidly advancing, although an accurate yet versatile modeling framework that can ...be easily adapted to various complex situations is still lacking. In this work, we propose a time-efficient numerical scheme in the quasi-electrostatic limit to capture the tip-sample interaction in the near field. This method considers an extended tip geometry, which is a significant advantage compared to the previously reported method based on the point-dipole approximation. Using this formalism, we investigate, among others, nontrivial questions such as uniaxial and biaxial anisotropy in the near-field interaction, the relationship between various experimental parameters (e.g. tip radius, tapping amplitude, etc.), and the tip-dependent spatial resolution. The demonstrated method further sheds light on the understanding of the contrast mechanism in s-SNOM imaging and spectroscopy, while also representing a valuable platform for future quantitative analysis of the experimental observations.
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