Tailoring the morphology of carbon nanotube assemblies using microgradients in the catalyst thickness

In addition to the structural control of individual carbon nanotubes (CNTs), the morphological control of their assemblies is crucial to realize miniaturized CNT devices. Microgradients in the thickness of catalyst are used to enrich the variety of available self-organized morphologies of CNTs. Microtrenches were fabricated in gate/spacer/cathode trilayers using a conventional self-aligned top-down process and catalyst exhibiting a microgradient in its thickness was formed on the cathode by sputter deposition through gate slits. CNTs, including single-walled CNTs, of up to 1μm in length were grown within 5-15 s by chemical vapor deposition. The tendency of thin CNTs to aggregate caused interactions between CNTs with different growth rates, yielding various morphologies dependent on the thickness of the catalyst. The field emission properties of several types of CNT assemblies were evaluated. The ability to produce CNTs with tailored morphologies by engineering the spatial distribution of catalysts will enhance their performance in devices. © 2011 The Japan Society of Applied Physics.

Morphological computation of multi-gaited robot locomotion based on free vibration.

In recent years, there has been increasing interest in the study of gait patterns in both animals and robots, because it allows us to systematically investigate the underlying mechanisms of energetics, dexterity, and autonomy of adaptive systems. In particular, for morphological computation research, the control of dynamic legged robots and their gait transitions provides additional insights into the guiding principles from a synthetic viewpoint for the emergence of sensible self-organizing behaviors in more-degrees-of-freedom systems. This article presents a novel approach to the study of gait patterns, which makes use of the intrinsic mechanical dynamics of robotic systems. Each of the robots consists of a U-shaped elastic beam and exploits free vibration to generate different locomotion patterns. We developed a simplified physics model of these robots, and through experiments in simulation and real-world robotic platforms, we show three distinctive mechanisms for generating different gait patterns in these robots.

Morphological computation for adaptive behavior and cognition

Traditionally, in robotics, artificial intelligence and neuroscience, there has been a focus on the study of the control or the neural system itself. Recently there has been an increasing interest in the notion of embodiment not only in robotics and artificial intelligence, but also in the neurosciences, psychology and philosophy. In this paper, we introduce the notion of morphological computation, and demonstrate how it can be exploited on the one hand for designing intelligent, adaptive robotic systems, and on the other hand for understanding natural systems. While embodiment has often been used in its trivial meaning, i.e. "intelligence requires a body", the concept has deeper and more important implications, concerned with the relation between physical and information (neural, control) processes. Morphological computation is about connecting body, brain and environment. A number of case studies are presented to illustrate the concept. We conclude with some speculations about potential lessons for neuroscience and robotics. © 2006 Elsevier B.V. All rights reserved.