Smooth thin film C/diamond membranes with controllable optical band gaps

Mixed phase carbon-diamond films which consist of small grain diamond in an a:C matrix were deposited on polished Si using a radio frequency CH4 Ar plasma CVD deposition process. Ellipsometry, surface profilometry, scanning electron microscopy (SEM) and spectrophotometry were used to analyse these films. Film thicknesses were typically 50-100 nm with a surface roughness of ± 30 A ̊ over centimetre length scans. SEM analysis showed the films were smooth and pinhole free. The Si substrate was etched using backside masking and a directional etch to give taut carbon-diamond membranes on a Si grid. Spectrophotometry was used to analyse the optical properties of these membranes. Band gap control was achieved by varying the dc bias of the deposition process. Band gaps of 1.2 eV to 4.0 eV were achieved in these membranes. A technique for controlling the compressive stress in the films, which can range from 0.02 to 7.5 GPa has been employed. This has allowed the fabrication of thin, low stress, high band gap membranes that are extremely tough and chemically inert. Such carbon-diamond membranes seem promising for applications as windows in analytical instruments. © 1992.

Multiple grasp-specific representations of tool dynamics mediate skillful manipulation.

Skillful tool use requires knowledge of the dynamic properties of tools in order to specify the mapping between applied force and tool motion. Importantly, this mapping depends on the orientation of the tool in the hand. Here we investigate the representation of dynamics during skillful manipulation of a tool that can be grasped at different orientations. We ask whether the motor system uses a single general representation of dynamics for all grasp contexts or whether it uses multiple grasp-specific representations. Using a novel robotic interface, subjects rotated a virtual tool whose orientation relative to the hand could be varied. Subjects could immediately anticipate the force direction for each orientation of the tool based on its visual geometry, and, with experience, they learned to parameterize the force magnitude. Surprisingly, this parameterization of force magnitude showed limited generalization when the orientation of the tool changed. Had subjects parameterized a single general representation, full generalization would be expected. Thus, our results suggest that object dynamics are captured by multiple representations, each of which encodes the mapping associated with a specific grasp context. We suggest that the concept of grasp-specific representations may provide a unifying framework for interpreting previous results related to dynamics learning.