A core-satellites metal nanostructure with high local electromagnetic (EM) intensity and density has shown great potential in ultrasensitive detection technologies, but complexity and uncontrollability of fabrication is a major obstacle for further application. Here, only by controlling the deposited Ag thickness, we facilely achieved 2D hetero core-satellites patterned Ag nanoparticle (NP) arrays for surface-enhanced Raman scattering (SERS) detection. The Ag nanoparticles were assembled by electron beam evaporation of Ag onto the anodized patterned aluminum template (APAlT) at a temperature above 0.24 times the melting point of Ag. The plasmonic bands can be continuously tuned from the visible to near-infrared region. The SERS enhancement factor (EF) and relative standard deviation (RSD) of as-prepared SERS active substrates for R6G molecules reached 10 ⁷ and about 5%, respectively, and a SERS detection limit down to 10 ⁻⁹ M was obtained. Finite-difference time-domain (FDTD) simulations revealed that the high SERS activity originates mainly from the local electromagnetic (EM) enhancement in the gaps between the core and satellites. The simple and controllable fabrication strategy and superior SERS performance make the 2D hetero core-satellites patterned Ag NPs arrays promising candidates for SERS-based sensor applications and provide a new approach for developing an inexpensive, efficient, and mass-produced SERS active substrate.

This paper presents a modified Bidirectional Reflectance Distribution Function (BRDF) model based on the Cauchy–Lorentz distribution that accurately characterizes the reflected energy distribution of typical materials, such as metals and coatings in hemispherical space. The proposed model overcomes the problem of large errors in classical models when detecting angles far away from the specular reflection angle by dividing the reflected light into specular reflection, directional diffuse reflection, and ideal diffuse reflection components. The newly added directional diffuse reflection component is represented by the Cauchy–Lorentz distribution, and its parameters are directly obtained from experimental measurement curves without distribution fitting. Surface morphology and model parameters are determined through measurements, and the comparison between simulation and actual measurement results shows that the modified BRDF model is in excellent agreement with the measured data. The proposed model not only achieves higher accuracy and universality, but it also represents a significant advancement in the field of BRDF modeling research. Its contributions have profound implications for advancing the state of the art in BRDF modeling, as well as having a broader impact on computer graphics and computer vision domains.

This paper presents a novel approach for clustering spectral polarization data acquired from space debris using a fuzzy C-means (FCM) algorithm model based on hierarchical agglomerative clustering (HAC). The effectiveness of the proposed algorithm is verified using the Kosko subset measure formula. By extracting characteristic parameters representing spectral polarization from laboratory test data of space debris samples, a characteristic matrix for clustering is determined. The clustering algorithm’s parameters are determined through a random selection of points in the external field. The resulting algorithm is applied to pixel-level clustering processing of spectral polarization images, with the clustering results rendered in color. The experimental results on field spectral polarization images demonstrate a classification accuracy of 96.92% for six types of samples, highlighting the effectiveness of the proposed approach for space debris detection and identification. The innovation of this study lies in the combination of HAC and FCM algorithms, using the former for preliminary clustering, and providing a more stable initial state for the latter, thereby improving the effectiveness, adaptability, accuracy, and robustness of the algorithm. Overall, this work provides a promising foundation for space debris classification and other related applications.

The optical path difference (OPD) equations of the dual Wollaston prisms (DWP) with an adjustable air gap (AG) are derived by the wave normal tracing method, which is suitable for arbitrary incidence plane and angle. The spatial distribution of the OPD for various AG is presented. The validity of the OPD equation is verified by comparing the calculated interferograms with experimentally observed one. The performance of a novel static birefringent Fourier transform imaging spectrometer (SBFTIS) based on the DWP is investigated. The spectral resolution can be adjusted by changing the AG and the field of view can reach 10.0°, which is much larger than that predicted by our previous work. The results obtained in this article provide a theoretical basis for completely describing the optical transmission characteristic of the DWP and developing the high-performance birefringent spectral zooming imaging spectrometer.