Contactless Spin Switch Sensing by Chemo-Electric Gating of Graphene

Direct electrical probing of molecular materials is often impaired by their insulating nature. Here, graphene is interfaced with single crystals of a molecular spin crossover complex, [Fe(bapbpy)(NCS)₂], to electrically detect phase transitions in the molecular crystal through the variation of graphene resistance. Contactless sensing is achieved by separating the crystal from graphene with an insulating polymer spacer. Next to mechanical effects, which influence the conductivity of the graphene sheet but can be minimized by using a thicker spacer, a Dirac point shift in graphene is observed experimentally upon spin crossover. As confirmed by computational modeling, this Dirac point shift is due to the phase-dependent electrostatic potential generated by the crystal inside the graphene sheet. This effect, named as chemo-electric gating, suggests that molecular materials may serve as substrates for designing graphene-based electronic devices. Chemo-electric gating, thus, opens up new possibilities to electrically probe chemical and physical processes in molecular materials in a contactless fashion, from a large distance, which can enhance their use in technological applications, for example, as sensors.     

Structural Orientation and Anisotropy in Biological Materials: Functional Designs and Mechanics

Biological materials exhibit anisotropic characteristics because of the anisometric nature of their constituents and their preferred alignment within interfacial matrices. The regulation of structural orientations is the basis for material designs in nature and may offer inspiration for man‐made materials. Here, how structural orientation and anisotropy are designed into biological materials to achieve diverse functionalities is revisited. The orientation dependencies of differing mechanical properties are introduced based on a 2D composite model with wood and bone as examples; as such, anisotropic architectures and their roles in property optimization in biological systems are elucidated. Biological structural orientations are designed to achieve extrinsic toughening via complicated cracking paths, robust and releasable adhesion from anisotropic contact, programmable dynamic response by controlled expansion, enhanced contact damage resistance from varying orientations, and simultaneous optimization of multiple properties by adaptive structural reorientation. The underlying mechanics and material‐design principles that could be reproduced in man‐made systems are highlighted. Finally, the potential and challenges in developing a better understanding to implement such natural designs of structural orientation and anisotropy are discussed in light of current advances. The translation of these biological design principles can promote the creation of new synthetic materials with unprecedented properties and functionalities.     

3D modeling and motion parallax for improved videoconferencing

Computational Visual Media - We consider a face-to-face videoconferencing system that uses a Kinect camera at each end of the link for 3D modeling and an ordinary 2D display for output. The Kinect...     

Continuous prediction of manufacturing performance throughout the production lifecycle

We describe methods for continual prediction of manufactured product quality prior to final testing. In our most expansive modeling approach, an estimated final characteristic of a product is updated after each manufacturing operation. Our initial application is for the manufacture of microprocessors, and we predict final microprocessor speed. Using these predictions, early corrective manufacturing actions may be taken to increase the speed of expected slow wafers (a collection of microprocessors) or reduce the speed of fast wafers. Such predictions may also be used to initiate corrective supply chain management actions. Developing statistical learning models for this task has many complicating factors: (a) a temporally unstable population (b) missing data that is a result of sparsely sampled measurements and (c) relatively few available measurements prior to corrective action opportunities. In a real manufacturing pilot application, our automated models selected 125 fast wafers in real-time. As predicted, those wafers were significantly faster than average. During manufacture, downstream corrective processing restored 25 nominally unacceptable wafers to normal operation.