Recent Progress in the Fabrication and Optical Properties of Nanoporous Anodic Alumina.

The fabrication of a thick oxide layer onto an aluminum surface via anodization has been a subject of intense research activity for more than a century, largely due to protective and decorative applications. The capability to create well-defined pores via a cost-effective electrochemical oxidation technique onto the surface has made a major renaissance in the field, as the porous surfaces exhibit remarkably different properties compared to a bulk oxide layer. Amongst the various nanoporous structures being investigated, nanoporous anodic alumina (NAA) with well-organized and highly ordered hexagonal honeycomb-like pores has emerged as the most popular nanomaterial due to its wide range of applications, ranging from corrosion resistance to bacterial repelling surfaces. As compared to conventional nanostructure fabrication, the electrochemical anodization route of NAA with well-controlled pore parameters offers an economical route for fabricating nanoscale materials. The review comprehensively reflects the progress made in the fabrication route of NAA to obtain the material with desired pore properties, with a special emphasis on self-organization and pore growth kinetics. Detailed accounts of the various conditions that can play an important role in pore growth kinetics and pore parameters are presented. Further, recent developments in the field of controlling optical properties of NAA are discussed. A critical outlook on the future trends of the fabrication of NAA and its optical properties on the emerging nanomaterials, sensors, and devices are also outlined.

A hybrid LIBS-Raman system combined with chemometrics: an efficient tool for plastic identification and sorting.

Classification of plastics is of great importance in the recycling industry as the littering of plastic wastes increases day by day as a result of its extensive use. In this paper, we demonstrate the efficacy of a combined laser-induced breakdown spectroscopy (LIBS)-Raman system for the rapid identification and classification of post-consumer plastics. The atomic information and molecular information of polyethylene terephthalate, polyethylene, polypropylene, and polystyrene were studied using plasma emission spectra and scattered signal obtained in the LIBS and Raman technique, respectively. The collected spectral features of the samples were analyzed using statistical tools (principal component analysis, Mahalanobis distance) to categorize the plastics. The analyses of the data clearly show that elemental information and molecular information obtained from these techniques are efficient for classification of plastics. In addition, the molecular information collected via Raman spectroscopy exhibits clearly distinct features for the transparent plastics (100% discrimination), whereas the LIBS technique shows better spectral feature differences for the colored samples. The study shows that the information obtained from these complementary techniques allows the complete classification of the plastic samples, irrespective of the color or additives. This work further throws some light on the fact that the potential limitations of any of these techniques for sample identification can be overcome by the complementarity of these two techniques. Graphical Abstract ᅟ.

Quantification and morphology studies of nanoporous alumina membranes: a new algorithm for digital image processing.

A new mathematical algorithm is reported for the accurate and efficient analysis of pore properties of nanoporous anodic alumina (NAA) membranes using scanning electron microscope (SEM) images. NAA membranes of the desired pore size were fabricated using a two-step anodic oxidation process. Surface morphology of the NAA membranes with different pore properties was studied using SEM images along with computerized image processing and analysis. The main objective was to analyze the SEM images of NAA membranes quantitatively, systematically, and quickly. The method uses a regularized shock filter for contrast enhancement, mathematical morphological operators, and a segmentation process for efficient determination of pore properties. The algorithm is executed using MATLAB, which generates a statistical report on the morphology of NAA membrane surfaces and performs accurate quantification of the parameters such as average pore-size distribution, porous area fraction, and average interpore distances. A good comparison between the pore property measurements was obtained using our algorithm and ImageJ software. This algorithm, with little manual intervention, is useful for optimizing the experimental process parameters during the fabrication of such nanostructures. Further, the algorithm is capable of analyzing SEM images of similar or asymmetrically porous nanostructures where sample and background have distinguishable contrast.