Mesoporous materials for clean energy technologies

Alternative energy technologies are greatly hindered by significant limitations in materials science. From low activity to poor stability, and from mineral scarcity to high cost, the current materials are not able to cope with the significant challenges of clean energy technologies. However, recent advances in the preparation of nanomaterials, porous solids, and nanostructured solids are providing hope in the race for a better, cleaner energy production. The present contribution critically reviews the development and role of mesoporosity in a wide range of technologies, as this provides for critical improvements in accessibility, the dispersion of the active phase and a higher surface area. Relevant examples of the development of mesoporosity by a wide range of techniques are provided, including the preparation of hierarchical structures with pore systems in different scale ranges. Mesoporosity plays a significant role in catalysis, especially in the most challenging processes where bulky molecules, like those obtained from biomass or highly unreactive species, such as CO2 should be transformed into most valuable products. Furthermore, mesoporous materials also play a significant role as electrodes in fuel and solar cells and in thermoelectric devices, technologies which are benefiting from improved accessibility and a better dispersion of materials with controlled porosity.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.