Abstract: A nanophotonic neural network, wherein the nanophotonic neural network comprises a large-kernel spatially-varying convolutional neural network. The large-kernel spatially-varying convolutional neural network is learned via a low-dimensional re-parameterization technique. The large-kernel spatially-varying convolutional neural network comprises a flat meta-optical system that encompasses an array of nanophotonic structures designed to induce angle-dependent responses. The large-kernel spatially-varying convolutional neural network comprises an extremely lightweight electronic backend with approximately 2K parameters configured to reach a 73.80% blind test classification accuracy on CIFAR-10 dataset.

Abstract: Digital content stylization techniques are described that leverage a neural photofinisher to generate stylized digital images. In one example, the neural photofinisher is implemented as part of a stylization system to train a neural network to perform digital image style transfer operations using reference digital content as training data. The training includes calculating a style loss term that identifies a particular visual style of the reference digital content. Once trained, the stylization system receives a digital image and generates a feature map of a scene depicted by the digital image. Based on the feature map as well as the style loss, the stylization system determines visual parameter values to apply to the digital image to incorporate a visual appearance of the particular visual style. The stylization system generates the stylized digital image by applying the visual parameter values to the digital image automatically and without user intervention.

Abstract: Metasurfaces and systems including metasurfaces for imaging and methods of imaging are described. In one embodiment, a method for acquiring images by an imaging system comprising a metalens includes: illuminating the metalens; acquiring light passing through the metalens as a first image by an image sensor; and processing the first image into a second image that is a deconvolved version of the first image by a post-processing engine. The metalens includes a plurality of nanoposts carried by a substrate.

Abstract: A semiconductor device includes a substrate, two semiconductor fins protruding from the substrate, an epitaxial feature over the two semiconductor fins and connected to the two semiconductor fins, a silicide layer over the epitaxial feature, a barrier layer over the silicide layer, and a metal layer over the barrier layer. The barrier layer includes a metal nitride. Along a boundary between the barrier layer and the metal layer, an atomic ratio of oxygen to metal nitride is about 0.15 to about 1.0.

Abstract: A semiconductor device includes a substrate, two semiconductor fins protruding from the substrate, an epitaxial feature over the two semiconductor fins and connected to the two semiconductor fins, a silicide layer over the epitaxial feature, a barrier layer over the silicide layer, and a metal layer over the barrier layer. The barrier layer includes a metal nitride. Along a boundary between the barrier layer and the metal layer, an atomic ratio of oxygen to metal nitride is about 0.15 to about 1.0.

Abstract: Metasurfaces and systems including metasurfaces for imaging and methods of imaging are described. In one embodiment, a method for acquiring images by an imaging system comprising a metalens includes: illuminating the metalens; acquiring light passing through the metalens as a first image by an image sensor; and processing the first image into a second image that is a deconvolved version of the first image by a post-processing engine. The metalens includes a plurality of nanoposts carried by a substrate.

Abstract: Digital content stylization techniques are described that leverage a neural photofinisher to generate stylized digital images. In one example, the neural photofinisher is implemented as part of a stylization system to train a neural network to perform digital image style transfer operations using reference digital content as training data. The training includes calculating a style loss term that identifies a particular visual style of the reference digital content. Once trained, the stylization system receives a digital image and generates a feature map of a scene depicted by the digital image. Based on the feature map as well as the style loss, the stylization system determines visual parameter values to apply to the digital image to incorporate a visual appearance of the particular visual style. The stylization system generates the stylized digital image by applying the visual parameter values to the digital image automatically and without user intervention.

Abstract: A semiconductor device includes a substrate, two semiconductor fins protruding from the substrate, an epitaxial feature over the two semiconductor fins and connected to the two semiconductor fins, a silicide layer over the epitaxial feature, a barrier layer over the silicide layer, and a metal layer over the barrier layer. The barrier layer includes a metal nitride. Along a boundary between the barrier layer and the metal layer, an atomic ratio of oxygen to metal nitride is about 0.15 to about 1.0.

Abstract: A semiconductor device includes a substrate, two semiconductor fins protruding from the substrate, an epitaxial feature over the two semiconductor fins and connected to the two semiconductor fins, a silicide layer over the epitaxial feature, a barrier layer over the silicide layer, and a metal layer over the barrier layer. The barrier layer includes a metal nitride. Along a boundary between the barrier layer and the metal layer, an atomic ratio of oxygen to metal nitride is about 0.15 to about 1.0.

Abstract: A method for learned hardware-in-the-loop phase retrieval for holographic near-eye displays includes generating simulated ideal output images of a holographic display. The method further includes capturing real output images of the holographic display. The method further includes learning a mapping between the simulated ideal output images and the real output images. The method further includes using the learned mapping to solve for an aberration compensating hologram phase and using the aberration compensating hologram phase to adjust a phase pattern of a spatial light modulator of the holographic display.

Abstract: A semiconductor device includes a substrate, two semiconductor fins protruding from the substrate, an epitaxial feature over the two semiconductor fins and connected to the two semiconductor fins, a silicide layer over the epitaxial feature, a barrier layer over the silicide layer, and a metal layer over the barrier layer. The barrier layer includes a metal nitride. Along a boundary between the barrier layer and the metal layer, an atomic ratio of oxygen to metal nitride is about 0.15 to about 1.0.

Abstract: A method includes providing a structure that includes a semiconductor substrate, an epitaxial source/drain feature over the semiconductor substrate, and one or more dielectric layers over the epitaxial source/drain feature; etching a hole into the one or more dielectric layer to expose a portion of the epitaxial source/drain feature; forming a silicide layer over the portion of the epitaxial source/drain feature; forming a conductive barrier layer over the silicide layer; and applying a plasma cleaning process to at least the conductive barrier layer, wherein the plasma cleaning process uses a gas mixture including N2 gas and H2 gas and is performed at a temperature that is at least 300° C.

Abstract: A method includes providing a structure that includes a semiconductor substrate, an epitaxial source/drain feature over the semiconductor substrate, and one or more dielectric layers over the epitaxial source/drain feature; etching a hole into the one or more dielectric layer to expose a portion of the epitaxial source/drain feature; forming a silicide layer over the portion of the epitaxial source/drain feature; forming a conductive barrier layer over the silicide layer; and applying a plasma cleaning process to at least the conductive barrier layer, wherein the plasma cleaning process uses a gas mixture including N2 gas and H2 gas and is performed at a temperature that is at least 300° C.