For ultrathin metallic films (e.g., less than 5 nm), no knowledge is yet available on how electron scattering at surface and grain boundaries reduces the electrical and thermal transport. The thermal and electrical conduction of metallic films is characterized down to 0.6 nm average thickness. The electrical and thermal conductivities of 0.6 nm Ir film are reduced by 82% and 50% from the respective bulk values. The Lorenz number is measured as 7.08 × 10⁻⁸ W Ω K⁻², almost a twofold increase of the bulk value. The Mayadas-Shatzkes model is used to interpret the experimental results and reveals very strong electron reflection (>90%) at grain boundaries.

We report on a thermal diffusivity study of suspended graphene foam (GF) using the transient electro-thermal technique. Our Raman study confirms the GF is composed of two-layer graphene. By measuring GF of different lengths, we are able to exclude the radiation effect. Using Schuetz's model, the intrinsic thermal diffusivity of the free-standing two-layer graphene is determined with a high accuracy without using knowledge of the porosity of the GF. The intrinsic thermal diffusivity of the two-layer graphene is determined at 1.16-2.22 × 10(-4) m(2) s(-1). The corresponding intrinsic thermal conductivity is 182-349 W m(-1) K(-1), about one order of magnitude lower than those reported for single-layer graphene. Extensive surface impurity defects, wrinkles and rough edges are observed under a scanning electron microscope for the studied GF. These structural defects induce substantial phonon scattering and explain the observed significant thermal conductivity reduction. Our thermal diffusivity characterization of GF provides an advanced way to look into the thermal transport capacity of free-standing graphene with high accuracy and ease of experimental implementation.

Robotic grasping of deformable objects is difficult and under-researched, not simply due to the high computational cost of modeling. More fundamentally, several issues arise with the deformation of an object being grasped: a changing wrench space, growing finger contact areas, and pointwise varying contact modes inside these areas. Consequently, contact constraints needed for deformable modeling are hardly established at the beginning of the grasping operation. This paper presents a grasping strategy that squeezes the object with two fingers under specified displacements rather than forces. A ‘stable’ squeeze minimizes the potential energy for the same amount of squeezing, while a ‘pure’ squeeze ensures that the object undergoes no rigid body motion as it deforms. Assuming linear elasticity, a finite element analysis guarantees equilibrium and the uniqueness of deformation during a squeeze action. An event-driven algorithm tracks the contact regions as well as the modes of contact in their interiors under Coulomb friction, which in turn serve as the needed constraints for deformation update. Grasp quality is characterized as the amount of work performed by the grasping fingers in resisting a known push by some adversary finger. Simulation and multiple experiments have been conducted to validate the results over solid and ring-like 2D objects.

This paper describes a strategy for a robotic hand to pick up deformable 3D objects on a table. Inspired by human hand behavior, the robotic hand employs two rigid fingers to first squeeze such an object until it ''feels'' the object to be liftable. Such ''feeling'' is provided by a (virtual) liftability test that is repeatedly conducted during the squeeze. Passing of the test then triggers a lifting action. Throughout the manipulation the object's deformation and its state of contact with the fingers and the table are being tracked based on contact events. Deformable modeling uses the finite element method (FEM) while slip computation employs the homotopy continuation method to determine the contact displacements induced by finger movements. The experiment was conducted for everyday items ranging from vegetables to a toy. A simulation-based comparison between deformable grasping and rigid body grasping reveals why soft objects are easier to pick up than hard ones, and demonstrates how a rigid body grasping strategy may fail on soft objects in certain situations.

For sub-10 nm thin metallic films, very little knowledge is available so far on how electron scattering at surface and grain boundaries reduces the thermal transport. This work reports on the first time characterization of the thermal and electrical conductivities of gold films of 6.4 nm average thickness. The electrical (σ) and thermal (k) conductivities of the Au film are found to be reduced dramatically from their bulk counterparts by 93.7% (σ) and 80.5% (k). Its Lorenz number is measured as 7.44 × 10(-8) W Ω K(-2), almost a twofold increase from the bulk value. The Mayadas-Shatzkes model is used to interpret the experimental results and reveals very strong electron reflection (77%) at grain boundaries.

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Robotic grasping of a deformable object is difficult not simply due to the high computational cost of deformable modeling. More fundamentally, the difficulty lies in a wrench space that changes under deformation, with growing contact areas, and subject to varying slip/stick modes in these areas. This paper presents a grasping strategy by squeezing the object with two fingers. An analysis based on the finite element method (FEM) proves equilibrium and uniqueness of deformation during the action, and leads to a (improved) quadratic time deformation update from the displacements of as few as two contact nodes. An event-driven algorithm is then presented to track the contact regions during a squeeze, and determine the stick/slip mode of every node in contact. The contacts supply the constraints needed for deformation update using FEM. Several experiments with a Barrett Hand have been conducted for validation.