The curling of a graphitic sheet to form carbon nanotubes produces a class of materials that seem to have extraordinary electrical and mechanical properties. In particular, the high elastic modulus of the graphite sheets means that the nanotubes might be stiffer and stronger than any other known material, with beneficial consequences for their application in composite bulk materials and as individual elements of nanometre-scale devices and sensors. The mechanical properties are predicted to be sensitive to details of their structure and to the presence of defects, which means that measurements on individual nanotubes are essential to establish these properties. Here we show that multiwalled carbon nanotubes can be bent repeatedly through large angles using the tip of an atomic force microscope, without undergoing catastrophic failure. We observe a range of responses to this high-strain deformation, which together suggest that nanotubes are remarkably flexible and resilient.

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Understanding the relative motion of objects in contact is essential for controlling macroscopic lubrication and adhesion, for comprehending biological macromolecular interfaces, and for developing submicrometre-scale electromechanical devices. An object undergoing lateral motion while in contact with a second object can either roll or slide. The resulting energy loss and mechanical wear depend largely on which mode of motion occurs. At the macroscopic scale, rolling is preferred over sliding, and it is expected to have an equally important role in the microscopic domain. Although progress has been made in our understanding of the dynamics of sliding at the atomic level, we have no comparable insight into rolling owing to a lack of experimental data on microscopic length scales. Here we produce controlled rolling of carbon nanotubes on graphite surfaces using an atomic force microscope. We measure the accompanying energy loss and compare this with sliding. Moreover, by reproducibly rolling a nanotube to expose different faces to the substrate and to an external probe, we are able to study the object over its complete surface.

The presence construct, most commonly defined as the sense of “being there,” has driven research and development of virtual environments (VEs) for decades. Despite that, there is not widespread agreement on how to define or operationalize this construct. The literature contains many different definitions of presence and many proposed measures for it. This article reviews many of the definitions, measures, and models of presence from the literature. We also review several related constructs, including social presence, copresence, immersion, agency, transportation, reality judgment, and embodiment. In addition, we present a meta-analysis of existing presence models and propose a model of presence informed by Slater’s Place Illusion and Plausibility Illusion constructs.

We propose the idea of simplification envelopes for generating a hierarchy of level-of-detail approximations for a given polygonal model. Our approach guarantees that all points of an approximation are within a user-specifiable distance from the original model and that all points of the original model are within a distance from the approximation. Simplification envelopes provide a general framework within which a large collection of existing simplification algorithms can run. We demonstrate this technique in conjunction with two algorithms, one local, the other global. The local algorithm provides a fast method for generating approximations to large input meshes (at least hundreds of thousands of triangles). The global algorithm provides the opportunity to avoid local "minima" and possibly achieve better simplifications as a result.Each approximation attempts to minimize the total number of polygons required to satisfy the above constraint. The key advantages of our approach are:General technique providing guaranteed error bounds for genus-preserving simplification Automation of both the simplification process and the selection of appropriate viewing distances Prevention of self-intersection Preservation of sharp features Allows variation of approximation distance across different portions of a model