Top down scale-up of semiconducting nanostructures for large area electronics

In this paper, we present a study on electrical and optical characteristics of n-type tin-oxide nanowires integrated based on top-down scale-up strategy. Through a combination of contact printing and plasma based back-channel passivation, we have achieved stable electrical characteristics with standard deviation in mobility and threshold voltage of 9.1% and 25%, respectively, for a large area of 1× 1 cm2 area. Through use of contact printing, high alignment of nanowires was achieved thus minimizing the number of nanowire-nanowire junctions, which serve to limit carrier transport in the channel. In addition, persistent photoconductivity has been observed, which we attribute to oxygen vacancy ionization and subsequent elimination using a gate pulse driving scheme. © 2014 IEEE.

Cognition from the bottom up: on biological inspiration, body morphology, and soft materials.

Traditionally, in cognitive science the emphasis is on studying cognition from a computational point of view. Studies in biologically inspired robotics and embodied intelligence, however, provide strong evidence that cognition cannot be analyzed and understood by looking at computational processes alone, but that physical system-environment interaction needs to be taken into account. In this opinion article, we review recent progress in cognitive developmental science and robotics, and expand the notion of embodiment to include soft materials and body morphology in the big picture. We argue that we need to build our understanding of cognition from the bottom up; that is, all the way from how our body is physically constructed.

Standing up with motor primitives

As observed in nature, complex locomotion can be generated based on an adequate combination of motor primitives. In this context, the paper focused on experiments which result in the development of a quality criterion for the design and analysis of motor primitives. First, the impact of different vocabularies on behavioural diversity, robustness of prelearned behaviours and learning process is elaborated. The experiments are performed with the quadruped robot MiniDog6M for which a running and standing up behaviour is implemented. Further, a reinforcement learning approach based on Q-learning is introduced which is used to select an adequate sequence of motor primitives. © 2006 Springer-Verlag Berlin Heidelberg.