Search Results (46)

Van der Waals (vdW) heterostructures formed by stacking two distinct semiconductor monolayers have gained increasing research interest because of the various predicted and realized exotic phenomena that are absent in the corresponding monolayers. However, constructing such a vdW hetero-bilayer is very challenging and mostly relies on top-down mechanical methods. Here, we report a direct growth of an SnSe₂/SnSe hetero-bilayer by using molecular beam epitaxy (MBE), in which elaborate interface engineering is the key to success. Scanning tunneling microscopy (STM) characterization demonstrated the well-defined and uniform moiré patterns, indicating an atomic-scale clean and uniform SnSe₂/SnSe interface. In combination with first-principles density functional theory (DFT) calculations, we further unveiled a type-III band gap alignment between the SnSe₂ and SnSe monolayers. This work provides a new method for building vertical SnSe₂/SnSe hetero-bilayers and a novel platform for exploring functional devices based on the type-III band alignment. Full article

Long bone fractures are breaks or cracks in a long bone of the body typically caused by trauma like a fall, sport injury, accidents etc. This study investigates the effectiveness of experimental methods for fast and safe healing of long bone fractures in humans, highlighting both their advantages and disadvantages, respectively finding the most effective and safe methods for evaluating the types of fixators that can be used in the consolidation of fractured long bones. As for the preliminary data, numerical methods and applied mathematics were used to address this problem. After collecting of preliminary data there were performed a series of experimental analysis as follows: Electrical Strain Gauges (ESGs); the Moiré Fringes method; Photo-Elasticity, with the particular technique thereof, the so-called Photo-Stress method; Holographic Interferometry (HI); Speckle Pattern Interferometry (ESPI) and Shearography; and Video Image Correlation (VIC), which is also called Digital Image Correlation (DIC). By analyzing different methods, the following two methods resulted to be widely applicable, namely, ESG and DIC/VIC. The findings highlight the net advantages regarding the objective choice of these types of fixators, thereby contributing to a possible extension of these approaches for the benefit of medical surgical practice Full article

Cobalt–molybdenum $\eta$-carbides are attractive hydrodesulfurization (HDS) catalysts, yet controlling their phase composition and nanostructure remains challenging. Here, a ${\mathrm{Co}}_{25}{\mathrm{Mo}}_{25}{\mathrm{C}}_{50}$ powder was prepared by mechanical alloying in a horizontal mill, with and without superimposed vertical vibration. Phase composition was determined by X-ray diffraction using the reference-intensity-ratio method, and the nanostructure was examined by SEM and HRTEM. Aquathermolysis of a heavy crude was monitored by ATR-FTIR in the window characteristic of S–S and C–S vibrations. Both milling routes produced the $\eta$-carbides ${\mathrm{Co}}_3{\mathrm{Mo}}_3$C and ${\mathrm{Co}}_6{\mathrm{Mo}}_6$C, as well as ${\mathrm{Co}}_2{\mathrm{Mo}}_3$, ${\mathrm{Co}}_7{\mathrm{Mo}}_6$, and ${\mathrm{Co}}_3$C; vibration-assisted milling increased the ${\mathrm{Co}}_6{\mathrm{Mo}}_6$C fraction and generated thin lamellae exhibiting Moiré contrast. In FTIR, the ${\mathrm{Co}}_6{\mathrm{Mo}}_6$C-rich powder showed strong attenuation of the disulfide and thioether bands, whereas the ${\mathrm{Co}}_3{\mathrm{Mo}}_3$C-rich powder behaved similarly to the water-only baseline under mild conditions (100 °C, 4 h). These results indicate that mechanical alloying with superposed vibration enables control over phase and nanostructure, and that a higher ${\mathrm{Co}}_6{\mathrm{Mo}}_6$C fraction correlates with a stronger HDS response under aquathermolysis. The approach offers a scalable route to Co–Mo carbides that are active for desulfurization at 100 °C in water without added ${\mathrm{H}}_2$. Full article

This study introduces a novel, low-cost, and non-invasive method for characterizing the surface profile of transparent objects using double digital fringe projection (DDFP). By projecting dual sinusoidal patterns that generate a Moiré effect and applying a frequency-domain Gaussian filter, the system isolates relevant data for accurate phase recovery through the isotropic quadrature transform (IQT). Experimental validation with plastic and acrylic samples confirms the method’s high spatial resolution and robustness against ambient noise. Unlike traditional systems, this technique avoids coherent light sources and complex hardware, improving its accessibility for academic and industrial use in transparent surface metrology. Full article

Herein, the energy dispersion relationship and the density of states of triangular and rectangular moiré patterns are investigated using a tight binding model. Their characteristics of Hofstadter butterflies under different magnetic fields are also examined. The results indicate that, by analyzing different moiré superlattices, Hofstadter butterflies arising from different moiré pattern structures are obtained, exhibiting considerable fractal characteristics and self-similarities. Moreover, it is also observed that under an alternating magnetic field, the redistribution of electronic states leads to a significant change in the density of states curve, and the Van Hove peak changes with the increase in magnetic field intensity. This study enriches the understanding of the electronic behavior of moiré systems, but it also provides multiple potential application directions for future technological development. Full article

The remote sensing of seismic waves in challenging and hazardous environments, such as active volcanic regions, remains a critical yet unresolved challenge. Conventional methods, including laser Doppler interferometry, InSAR, and stereo vision, are often hindered by atmospheric turbulence or necessitate access to observation sites, significantly limiting their applicability. To overcome these constraints, this study introduces a Moiré-based apparatus augmented with active convolved illumination (ACI). The system leverages the displacement-magnifying properties of Moiré patterns to achieve high precision in detecting subtle ground movements. Additionally, ACI effectively mitigates atmospheric fluctuations, reducing the distortion and alteration of measurement signals caused by these fluctuations. We validated the performance of this integrated solution through over 1900 simulations under diverse turbulence intensities. The results illustrate the synergistic capabilities of the Moiré apparatus and ACI in preserving the fidelity of Moiré fringes, enabling reliable displacement measurements even under conditions where passive methods fail. This study establishes a cost-effective, scalable, and non-invasive framework for remote seismic monitoring, offering transformative potential across geophysics, volcanology, structural analysis, metrology, and other domains requiring precise displacement measurements under extreme conditions. Full article

This paper presents a simulation-based investigation of passive frequency tunability in frequency-selective surfaces (FSSs) enabled by Moiré pattern interference. By overlapping two identical hexagonal FSS layers and introducing rotational misalignment between them, we demonstrate that the resulting Moiré patterns induce significant shifts in the resonance frequency without any external bias or active components. Using full-wave simulations in HFSS, we show that rotating the second layer from 0° to 30° can shift the resonant frequency from 4.4 GHz down to 1.2 GHz. This tunable behavior emerges solely from geometrical manipulation, offering a low-complexity alternative to active tuning methods that rely on varactors or micro-electromechanical systems (MEMSs). We discuss the theoretical basis for this tuning mechanism based on effective periodicity modulation via rotational interference and highlight potential applications in passive reconfigurable filters and refractive index sensors. The proposed approach provides a promising route for implementing tunable electromagnetic structures without compromising simplicity, power efficiency, or integration compatibility. Full article

The Talbot wavemeter has attracted widespread attention from researchers in recent years due to its advantages of miniaturization and low cost. However, the impact of varying incident conditions caused by factors such as alignment has remained a challenge for spectral retrieval. This paper first derives the influence of different incident conditions on the interference pattern based on Fresnel diffraction and verifies the derivation through simulations. We propose a method to address the impact of incident conditions on the interference pattern. By adding a grating with a different periodicity in front of the detector, Moiré fringes are generated in the periodicity dimension, increasing the fringe period and thus enlarging the tolerance for angular misalignment. Finally, we constructed a Talbot wavemeter based on a double-grating structure, achieving a spectral resolution of 9 nm at 360 nm. This method provides a reference for the future development of a high-precision, high-resolution Talbot wavemeter. Full article

As one of the most crucial parts of face detection, the accuracy and the generalization of face anti-spoofing are particularly important. Therefore, it is necessary to propose a multi-branch network to improve the accuracy and generalization of the detection of unknown spoofing attacks. These branches consist of several frequency map encoders and one depth map encoder. These encoders are trained together. It leverages multiple frequency features and generates depth map features. High-frequency edge texture is beneficial for capturing moiré patterns, while low-frequency features are sensitive to color distortion. Depth maps are more discriminative than RGB images at the visual level and serve as useful auxiliary information. Supervised Multi-view Contrastive Learning enhances multi-view feature learning. Moreover, a two-stage feature fusion method effectively integrates multi-branch features. Experiments on four public datasets, namely CASIA-FASD, Replay–Attack, MSU-MFSD, and OULU-NPU, demonstrate model effectiveness. The average Half Total Error Rate (HTER) of our model is 4% (25% to 21%) lower than the Adversarial Domain Adaptation method in inter-set evaluations. Full article

A highly robust dual-frequency hierarchical temporal phase unwrapping (DHTPU) based on the novel spatial computer-generated Moiré profilometry (SCGMP) is proposed. The method requires only three patterns: a high-frequency fringe to provide robust surface information, a multi-period low-frequency fringe to eliminate the 2π-phase ambiguities, and a flat pattern to remove the average intensity of the two fringes. In decoding, different from traditional Moiré profilometries that rely on spectrum filters, SCGMP only employs spatial-domain calculations to extract the wrapped phase, thereby preserving more detailed information. Furthermore, we fully explore SCGMP’s capability to significantly alleviate phase ambiguity and provide an algorithm to determine the maximum measurable height range for a fixed system, enabling the direct extraction of the continuous basic phase from the multi-period low-frequency fringe. Consequently, the proposed basic phase exhibits an enhanced signal-to-noise ratio, compared to the traditional basic phase derived from the single-period fringes, effectively releasing the high-frequency restriction in the traditional DHTPU. The experimental results verify that the proposed DHTPU method has considerable accuracy and great potential for high-speed measurements, due to there being only three shots required. Full article

Transition metal dichalcogenides (TMDCs), represented by MX₂ (where M = Mo, W and X = S, Se, and Te), and more recently, their moiré superlattices (i.e., formed by superimposing layers of TMDCs with different rotation angles) have attracted considerable interest due to their excellent physical properties and unique nanoscale functionalities. Compared to graphene, the literature indicates that TMDCs offer a competitive advantage in optoelectronic technologies, primarily owing to their compositionally controlled non-zero bandgap. These two-dimensional (2D) nanostructured single or multiple layers exhibit remarkable properties that differ from their bulk counterparts. Moreover, stacking different TMDC monolayers also forms heterostructures and introduces unique quantum effects and extraordinary electronic properties, which is particularly promising for next-generation optoelectronic devices and photo(electro)catalytic applications. Therefore, in this review, we also highlight the new possibilities in the formation of 2D/2D heterostructures of MX₂-based materials with moiré patterns and discuss the main critical challenges related to the synthesis and large-scale applications of layered MX₂ and MX₂-based composites to spur significant advances in emerging optoelectronic and photo(electro)catalytic applications. Full article

Optical tracking of head pose via fiducial markers has been proven to enable effective correction of motion artifacts in the brain during magnetic resonance imaging but remains difficult to implement in the clinic due to lengthy calibration and set up times. Advances in deep learning for markerless head pose estimation have yet to be applied to this problem because of the sub-millimetre spatial resolution required for motion correction. In the present work, two optical tracking systems are described for the development and training of a neural network: one marker-based system (a testing platform for measuring ground truth head pose) with high tracking fidelity to act as the training labels, and one markerless deep-learning-based system using images of the markerless head as input to the network. The markerless system has the potential to overcome issues of marker occlusion, insufficient rigid attachment of the marker, lengthy calibration times, and unequal performance across degrees of freedom (DOF), all of which hamper the adoption of marker-based solutions in the clinic. Detail is provided on the development of a custom moiré-enhanced fiducial marker for use as ground truth and on the calibration procedure for both optical tracking systems. Additionally, the development of a synthetic head pose dataset is described for the proof of concept and initial pre-training of a simple convolutional neural network. Results indicate that the ground truth system has been sufficiently calibrated and can track head pose with an error of <1 mm and <1°. Tracking data of a healthy, adult participant are shown. Pre-training results show that the average root-mean-squared error across the 6 DOF is 0.13 and 0.36 (mm or degrees) on a head model included and excluded from the training dataset, respectively. Overall, this work indicates excellent feasibility of the deep-learning-based approach and will enable future work in training and testing on a real dataset in the MRI environment. Full article

Grating (moiré) interferometry is one of the well-known methods for full-field in-plane displacement and strain measurement. There are many design solutions for grating interferometers, including systems with a microinterferometric waveguide head. This article proposes a modification to the conventional waveguide interferometer head, enabling the implementation of a polarization fringe phase shift for automatic fringe pattern analysis. This article presents both the theoretical considerations associated with the proposed solution and its experimental verification, along with the concept of in-plane displacement/strain sensing using the described head. Full article

Moiré patterns caused by aliasing between the camera’s sensor and the monitor can severely degrade image quality. Image demoiréing is a multi-task image restoration method that includes texture and color restoration. This paper proposes a new multibranch wavelet-based image demoiréing network (MBWDN) for moiré pattern removal. Moiré images are separated into sub-band images using wavelet decomposition, and demoiréing can be achieved using the different learning strategies of two networks: moiré removal network (MRN) and detail-enhanced moiré removal network (DMRN). MRN removes moiré patterns from low-frequency images while preserving the structure of smooth areas. DMRN simultaneously removes high-frequency moiré patterns and enhances fine details in images. Wavelet decomposition is used to replace traditional upsampling, and max pooling effectively increases the receptive field of the network without losing the spatial information. Through decomposing the moiré image into different levels using wavelet transform, the feature learning results of each branch can be fully preserved and fed into the next branch; therefore, possible distortions in the recovered image are avoided. Thanks to the separation of high- and low-frequency images during feature training, the proposed two networks achieve impressive moiré removal effects. Based on extensive experiments conducted using public datasets, the proposed method shows good demoiréing validity both quantitatively and qualitatively when compared with the state-of-the-art approaches. Full article

Screen photos often suffer from moiré patterns, which significantly affect their visual quality. Although many deep learning-based methods for removing moiré patterns have been proposed, they fail to recover images with complex textures and heavy moiré patterns. Here, we focus on text images with heavy moiré patterns and propose a new demoiré approach, incorporating frequency-domain peak filtering and spatial-domain visual quality enhancement. We find that the content of the text image mainly lies in the central region, whereas the moiré pattern lies in the peak region, in the frequency domain. Based on this observation, a peak-filtering algorithm and a central region recovery strategy are proposed to accurately locate and remove moiré patterns while preserving the text parts. In addition, to further remove the noisy background and paint the missing text parts, an image enhancement algorithm utilising the Otsu method is developed. Extensive experimental results show that the proposed method significantly removes severe moiré patterns from images with better visual quality and lower time cost compared to the state-of-the-art methods. Full article