Abstract: Provided herein is a method of coating a conductive surface with a multi-layer mesoporous structure, by coating a conductive surface with a first photocatalytic dispersion to form a first layer over the conductive surface, curing or partially curing the first layer at temperatures of less than 400° C. to form a porous structure, and coating the porous first layer with the one or more additional photocatalytic dispersions to form one or more additional layers that can penetrate or partially penetrate the pores of the structure in the first layer. The first photocatalytic dispersion includes photocatalytic particles, polymeric binder and a dispersion medium. The one or more additional photocatalytic dispersions include photocatalytic particles and a dispersion medium.

Abstract: Embodiment methods and structures include a resonant plasmonic nanostructure located within a thin-film solar cell. This plasmonic nanostructure may trap light and thereby improve the efficiency and light absorption of the cell without increasing physical thickness. In various embodiments, the plasmonic nanostructure may be located within a p-type semiconductor layer of the solar cell. In further embodiments, the index of refraction may vary within the p-type semiconductor layer.

Abstract: The oxygen content of metal species in a heterogeneous catalyst is determined using volumetric adsorption measurements. Such measurements are employed to quantify the amount of reduction gas that it takes to reduce metal species of a catalyst sample, and the oxygen content is derived from this amount and the reaction stoichiometry. This method can be applied to mono-metallic and multi-metallic heterogeneous catalysts and has been shown to provide at least 10 times better detection sensitivity than typical TCDs in TPR-TCD methods.

Abstract: A catalyst sample may contain both small and large metal particle distributions simultaneously. Characterizing the properties of the metal particles contained in each distribution is important to help describe catalytic performance and optimize catalysts. Monte Carlo simulations and dispersion measurements are employed to determine the relationship between dispersion parameters of each metal particle distribution. Various properties, such as the atom fraction and the surface atom fraction of each distribution can be determined.

Abstract: A relationship between dispersion and surface-averaged metal particle size is provided so that either dispersion can be determined from measured surface-averaged metal particle size or surface-averaged metal particle size can be determined from measured dispersion. The method can be applied to catalysts having a single metal species as well as catalysts having multiple metal species. The size of the supported metal particles in the catalyst sample may be determined using transmission electron microscopy images of supported metal particles in the catalyst sample. The dispersion of the supported metal particles in the catalyst sample may be determined using chemisorption tests on the catalyst sample.

Abstract: Three-dimensional (3D) shapes of particles are characterized from a two-dimensional (2D) image of the particles that is obtained using TEM. The 3D shape characterization method includes the steps of obtaining a 2D image of a batch of nanoparticles, determining 2D shapes of the nanoparticles from the 2D image, and deriving six distributions, each of which corresponds to a 2D shape and a 3D shape associated with the 2D shape. The first size distribution is derived from the nanoparticles having the 2D triangle shape. The second and third size distributions are derived from the nanoparticles having the 2D tetragon shape. The fourth, fifth and sixth size distributions are derived from the nanoparticles having the 2D round shape. Based on these six size distributions, three size distributions, each of which corresponds to one of three 3D shape classes, are estimated.

Abstract: The size distributions corresponding to the three-dimensional (3D) shapes of particles are estimated from a 3D-to-2D projection matrix and a two-dimensional (2D) image of the particles that is obtained using TEM. Two different methods to generate a 3D-to-2D projection matrix are described. The first method determines the matrix coefficients assuming equal probability for all high-symmetry projections. The second method employs a large set of 3D-to-2D projection matrices with randomly generated coefficients satisfying the high-symmetry projection constraint. The second method is a general method to determine 3D-to-2D projection matrices based on the assumption that certain high-symmetry projections are present for the system under investigation.