Flexible broadband metamaterial absorber in long-wave infrared with visible transparency fabricated by laser direct writing.

Absorption of the long-wave infrared from human beings and the surroundings is a key step to infrared imaging and sensing. Here we demonstrate a flexible and transparent broadband infrared absorber using the photoresist-assisted metamaterials fabricated by one-step laser direct writing. The photoresist is patterned by the laser as an insulator layer as well as a mask to build the complementary bilayer metamaterials without lithography. The average absorptivity is 94.5% from 8 to 14 µm in experiment due to the broadband destructive interference of the reflected beam explained by the Fabry-Perot cavity model. The proposed absorber is applicable to various substrates with additional merits of polarization insensitivity and large angle tolerance, which offers a promising solution for thermal detection and management.

A Multi-foci Sparse-Aperture Metalens.

Multi-foci lenses are essential components for optical communications, virtual reality display and microscopy, yet the bulkiness of conventional counterparts has significantly hindered their widespread applications. Benefiting from the unprecedented capability of metasurfaces in light modulation, metalenses are able to provide multi-foci functionality with a more compact footprint. However, achieving imaging quality comparable to that of corresponding single-foci metalenses at each focal point poses a challenge for existing multi-foci metalenses. Here, a polarization-independent all-dielectric multi-foci metalens is proposed and experimentally demonstrated by spatially integrating single-foci optical sparse-aperture sub-metalenses. Such design enables the metalens to generate multiple focal points, while maintaining the ability to capture target information comparable to that of a single-foci metalens. The proposed multi-foci metalens is composed of square-nanohole units array fabricated by two-photon polymerization. The focusing characteristic and imaging capability are demonstrated upon the illumination of an unpolarized light beam. This work finds a novel route toward multi-foci metalenses and may open a new avenue for dealing with the trade-off between multi-foci functionality and high-quality imaging performance.

Label-free investigation of infected acute pyelonephritis tissue by FTIR microspectroscopy with unsupervised and supervised analytical methods.

Acute pyelonephritis (AP) is a severe urinary tract infection (UTI) syndrome with a large population of patients worldwide. Current approaches to confirming AP are limited to urinalysis, radiological imaging methods and histological assessment. Fourier transform infrared (FTIR) microspectroscopy is a promising label-free modality that can offer information about both morphological and molecular pathologic alterations from biological tissues. Here, FTIR microspectroscopy serves to investigate renal biological histology of a rat model with AP and classify normal cortex, normal medulla and infected acute pyelonephritis tissues. The spectra were experimentally collected by FTIR with an infrared Globar source through raster scanning procedure. Unsupervised analysis methods, including integrating, clustering and principal component analysis (PCA) were performed on such spectra data to form infrared histological maps of entire kidney section. In comparison to Hematoxylin & Eosin-stained results of the adjacent tissue sections, these infrared maps were proved to enable the differentiation of the renal tissue types. The results of both integration and clustering indicated that the concentration of amide II decreases in the infected acute pyelonephritis tissues, with an increased presence of nucleic acids and lipids. By means of PCA, the infected tissue was linearly separated from normal ones by plotting confident ellipses with the score values of the first and second principal components. Moreover, supervised analysis was performed based on the supported vector machines (SVM). Normal cortex, normal medulla and infected acute pyelonephritis tissues were classified by SVM models with the best accuracy of 96.11% in testing dataset. In addition, these analytical methods were further employed on synchrotron-based FTIR spectra data and successfully form high-resolution infrared histological maps of glomerulus and necrotic cell mass. This work demonstrates that FTIR microspectroscopy will be a powerful manner to investigate AP tissue and differentiate infected tissue from normal tissue in a renal infected model system.