Material demands for storage technologies in a hydrogen economy

A hydrogen economy is needed, in order to resolve current environmental and energy-related problems. For the introduction of hydrogen as an important energy vector, sophisticated materials are required. This paper provides a brief overview of the subject, with a focus on hydrogen storage technologies for mobile applications. The unique properties of hydrogen are addressed, from which its advantages and challenges can be derived. Different hydrogen storage technologies are described and evaluated, including compression, liquefaction, and metal hydrides, as well as porous materials. This latter class of materials is outlined in more detail, explaining the physisorption interaction which leads to the adsorption of hydrogen molecules and discussing the material characteristics which are required for hydrogen storage application. Finally, a short survey of different porous materials is given which are currently investigated for hydrogen storage, including zeolites, metal organic frameworks (MOFs), covalent organic frameworks (COFs), porous polymers, aerogels, boron nitride materials, and activated carbon materials.

A Comparative Study of Registration Methods for RGB-D Video of Static Scenes

The use of RGB-D sensors for mapping and recognition tasks in robotics or, in general, for virtual reconstruction has increased in recent years. The key aspect of these kinds of sensors is that they provide both depth and color information using the same device. In this paper, we present a comparative analysis of the most important methods used in the literature for the registration of subsequent RGB-D video frames in static scenarios. The analysis begins by explaining the characteristics of the registration problem, dividing it into two representative applications: scene modeling and object reconstruction. Then, a detailed experimentation is carried out to determine the behavior of the different methods depending on the application. For both applications, we used standard datasets and a new one built for object reconstruction.