Hydrogen storage in engineered carbon nanospaces.

It is shown how appropriately engineered nanoporous carbons provide materials for reversible hydrogen storage, based on physisorption, with exceptional storage capacities (approximately 80 g H2/kg carbon, approximately 50 g H2/liter carbon, at 50 bar and 77 K). Nanopores generate high storage capacities (a) by having high surface area to volume ratios, and (b) by hosting deep potential wells through overlapping substrate potentials from opposite pore walls, giving rise to a binding energy nearly twice the binding energy in wide pores. Experimental case studies are presented with surface areas as high as 3100 m(2) g(-1), in which 40% of all surface sites reside in pores of width approximately 0.7 nm and binding energy approximately 9 kJ mol(-1), and 60% of sites in pores of width>1.0 nm and binding energy approximately 5 kJ mol(-1). The findings, including the prevalence of just two distinct binding energies, are in excellent agreement with results from molecular dynamics simulations. It is also shown, from statistical mechanical models, that one can experimentally distinguish between the situation in which molecules do (mobile adsorption) and do not (localized adsorption) move parallel to the surface, how such lateral dynamics affects the hydrogen storage capacity, and how the two situations are controlled by the vibrational frequencies of adsorbed hydrogen molecules parallel and perpendicular to the surface: in the samples presented, adsorption is mobile at 293 K, and localized at 77 K. These findings make a strong case for it being possible to significantly increase hydrogen storage capacities in nanoporous carbons by suitable engineering of the nanopore space.

Spatial correlation coefficient images for ultrasonic detection.

In ultrasonics, image formation and detection are generally based on signal amplitude. In this paper, we introduce correlation coefficient images as a signal-amplitude independent approach for image formation. The correlation coefficients are calculated between A-scans digitized at adjacent measurement positions. In these images, defects are revealed as regions of high or low correlation relative to the background correlations associated with noise. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular ring and crack detection in an aluminum aircraft structure.

Identifying the signal of interest for partially overlapping ultrasonic echoes.

The basic problem addressed in this paper is to discriminate between two signals that are at approximately the same time, but which originate at different echo sources. The proposed solution is to systematically perturb the field and discriminate between signals based on differences in amplitude variations between the two signals.

Attenuation coefficient estimation using experimental diffraction corrections with multiple interface reflections.

The ultrasonic attenuation coefficient of a fluid or solid is an acoustic parameter routinely estimated for the purpose of materials characterization and defect/disease detection. This paper describes a broadband attenuation coefficient estimation technique that combines two established estimation approaches. The key elements of these two approaches are: (1) the use of magnitude spectrum ratios of front surface, first back surface, and second back surface reflections from interfaces of materials with plate-like geometries, and (2) the use of an experimental diffraction correction approach to avoid diffraction losses. The combined estimation approach simplifies the attenuation coefficient estimation process by eliminating the need to explicitly make diffraction corrections or calculate reflection/transmission coefficients. The approach yields estimates of the attenuation coefficient, reflection coefficient, and material density. Models, experimental procedures, and signal analysis procedures, which support implementation of the approach, are presented. Attenuation coefficient and reflection coefficient estimates are presented for water and solid samples with estimates based on measurements made with multiple transducers.