Structurally programmed capillary folding of carbon nanotube assemblies.

We demonstrate the fabrication of horizontally aligned carbon nanotube (HA-CNT) networks by spatially programmable folding, which is induced by self-directed liquid infiltration of vertical CNTs. Folding is caused by a capillary buckling instability and is predicted by the elastocapillary buckling height, which scales with the wall thickness as t(3/2). The folding direction is controlled by incorporating folding initiators at the ends of the CNT walls, and the initiators cause a tilt during densification which precedes buckling. By patterning these initiators and specifying the wall geometry, we control the dimensions of HA-CNT patches over 2 orders of magnitude and realize multilayered and multidirectional assemblies. Multidirectional HA-CNT patterns are building blocks for custom design of nanotextured surfaces and flexible circuits.

Non-destructive characterization of structural hierarchy within aligned carbon nanotube assemblies

Understanding and controlling the hierarchical self-assembly of carbon nanotubes (CNTs) is vital for designing materials such as transparent conductors, chemical sensors, high-performance composites, and microelectronic interconnects. In particular, many applications require high-density CNT assemblies that cannot currently be made directly by low-density CNT growth, and therefore require post-processing by methods such as elastocapillary densification. We characterize the hierarchical structure of pristine and densified vertically aligned multi-wall CNT forests, by combining small-angle and ultra-small-angle x-ray scattering (USAXS) techniques. This enables the nondestructive measurement of both the individual CNT diameter and CNT bundle diameter within CNT forests, which are otherwise quantified only by delicate and often destructive microscopy techniques. Our measurements show that multi-wall CNT forests grown by chemical vapor deposition consist of isolated and bundled CNTs, with an average bundle diameter of 16 nm. After capillary densification of the CNT forest, USAXS reveals bundles with a diameter 4 m, in addition to the small bundles observed in the as-grown forests. Combining these characterization methods with new CNT processing methods could enable the engineering of macro-scale CNT assemblies that exhibit significantly improved bulk properties. © 2011 American Institute of Physics.

Bending of nanoscale filament assemblies by elastocapillary densification

We report a mechanism by which nanoscale filaments self-assemble into asymmetric aggregates by elastocapillary action. Specifically, capillary rise of liquid into an asymmetric pattern of vertically aligned filaments causes the filaments to deflect laterally during elastocapillary densification. We quantitatively show that the lateral deflection can be controlled precisely by the pattern shape and the coupling strength among the filaments. We exploit this mechanism to fabricate asymmetric micropillars and multidirectional bridges of densely packed carbon nanotubes. Analogous behavior occurs as biological filaments interact with liquids, and these findings enable scalable fabrication of anisotropic filament assemblies for manipulating surface interactions between solids and liquids. © 2010 The American Physical Society.

Detailed thermal modelling of a tubular linear machine for marine renewable generation

A detailed lumped-parameter thermal model is presented for a tubular linear machine that has been designed for use in a marine environment. The model has been developed for a static machine, the worst-case thermal scenario, and is used to establish a rating for the machine. The model has been validated against a large range of experimental tests and shows good correlation to both steady-state and transient experimental results. The model was constructed from a mostly theoretical basis with very little calibration, suggesting that the techniques used are applicable in a more general sense. © 2013 IEEE.

Linear regression under fixed-rank constraints: A Riemannian approach

In this paper, we tackle the problem of learning a linear regression model whose parameter is a fixed-rank matrix. We study the Riemannian manifold geometry of the set of fixed-rank matrices and develop efficient line-search algorithms. The proposed algorithms have many applications, scale to high-dimensional problems, enjoy local convergence properties and confer a geometric basis to recent contributions on learning fixed-rank matrices. Numerical experiments on benchmarks suggest that the proposed algorithms compete with the state-of-the-art, and that manifold optimization offers a versatile framework for the design of rank-constrained machine learning algorithms. Copyright 2011 by the author(s)/owner(s).

Synchronization in networks of identical linear systems

The paper investigates the synchronization of a network of identical linear state-space models under a possibly time-varying and directed interconnection structure. The main result is the construction of a dynamic output feedback coupling that achieves synchronization if the decoupled systems have no exponentially unstable mode and if the communication graph is uniformly connected. The result can be interpreted as a generalization of classical consensus algorithms. Stronger conditions are shown to be sufficient-but to some extent, also necessary-to ensure synchronization with the diffusive static output coupling often considered in the literature. © 2009 Elsevier Ltd. All rights reserved.

Synchronization in networks of identical linear systems

The paper investigates the synchronization of a network of identical linear time-invariant state-space models under a possibly time-varying and directed interconnection structure. The main result is the construction of a dynamic output feedback coupling that achieves synchronization if the decoupled systems have no exponentially unstable mode and if the communication graph is uniformly connected. Stronger conditions are shown to be sufficient - but to some extent, also necessary - to ensure synchronization with the diffusive static output coupling often considered in the literature. © 2008 IEEE.

Improving the performance of low-gain designs for bounded control of linear systems

An online scheduling of the parameter ensuring in addition to closed loop stability was presented. Attention was given to saturated linear low-gain control laws. Null controllability of the considered linear systems was assumed. The family of low gain control laws achieved semiglobal stabilization.