Abstract: A copper-based nanocomposite includes a matrix including copper, and nanostructures dispersed in the matrix, wherein the nanocomposite has a yield strength of about 300 MPa or greater, and a ductility of about 5% or greater. Manufacturing methods of a copper-based nanocomposite are also provided.

Abstract: The limiting device includes a clamping portion and a movable portion; the clamping portion and the movable portion are both annular structures, two ends of the clamping portion and the movable portion are respectively connected to form a connected double-ring structure, and the ring diameter of the movable portion is larger than that of the clamping portion. The limiting device is disposed on a core rod, the clamping portion and the core rod are in interference fit, and the movable portion and the core rod are in clearance fit. When the movable portion cooperates with the core rod, the limiting device may slide relative to the core rod; when the clamping portion cooperates with the core rod, the limiting device and the core rod are in a fixed state, and the limiting device cannot slide relative to the core rod, thus achieving the purpose of limiting.

Abstract: A metal matrix nanocomposite includes: (1) a matrix including an aluminum alloy; and (2) nanostmctures dispersed in the matrix, wherein the matrix includes grains having aspect ratios of about 3 or less. Manufacturing processes include subjecting the nanocomposite to solidification processing, fusion welding, extrusion, thixocasting, additive manufacturing, and heat treatment.

Abstract: Methods and systems for determining one or more alignment parameters for use in a process performed on a specimen are provided. One method includes determining measures of similarity between images generated by an imaging system for corresponding locations in each of two or more pairs of dies on a specimen and performing cluster analysis based on the determined measures of similarity to identify the images that are most similar to each other and to assign different subsets of the images that are most similar to each other to different die clusters, respectively. The method also includes separately determining one or more alignment parameters for two or more of the different die clusters. The one or more alignment parameters are used for aligning images generated by the imaging system for the specimen or another specimen to a common reference.

Abstract: A biomedical device includes a zinc-based material including a matrix including zinc, and nanostructures dispersed in the matrix. Embodiments of this disclosure are directed to zinc (Zn)-based materials including dispersed nanostructures for biomedical applications and devices, such as bioresorbable vascular stents, bioresorbable ureteral stents, endoluminal springs for distraction enterogenesis, biodegradable bone implants with tunable modulus, guided bone generation membranes, bioresorbable dental membranes, and other biomedical implants, as well as other functional applications, such as biodegradable electronics and sensors.

Abstract: Systems and methods for detecting defects on a reticle are provided. One system includes computer subsystem(s) configured for performing at least one repeater defect detection step in front-end processing during an inspection process performed on a wafer having features printed in a lithography process using a reticle. The at least one repeater defect detection step performed in the front-end processing includes identifying any defects detected at corresponding locations in two or more test images by double detection and any defects detected by stacked defect detection as first repeater defect candidates. One or more additional repeater defect detections may be performed on the first repeater defect candidates to generate final repeater defect candidates and identify defects on the reticle from the final repeater defect candidates.

Abstract: An optical characterization system and a method of using the same are disclosed. The system comprises a controller configured to be communicatively coupled with one or more detectors configured to receive illumination from a sample and generate image data. One or more processors may be configured to receive images of dies on the sample, calculate dissimilarity values for all combinations of the images, perform a cluster analysis to partition the combinations of the images into two or more clusters, generate a reference image for a cluster of the two or more clusters using two or more of the combinations of the images in the cluster; and detect one or more defects on the sample by comparing a test image in the cluster to the reference image for the cluster.

Abstract: A method of forming a polymer-metal nanocomposite (PMNC) material with a substantially uniform dispersion of metal particles includes forming a composite solid preform by mixing a blend of micrometer-sized metal particles and polymer particles and subjecting the mixture to compression followed by sintering. The composite solid preform is drawn through a heated zone to form a reduced size fiber. The reduced size fiber is cut into segments and a next preform is formed using the bundle of the segments. The next preform is then drawn through the heated zone to form yet another reduced size fiber. This reduced size fiber may undergo one or more stack-and-draw operations to yield a final fiber having substantially uniform dispersion of nanometer-sized metal particles therein.

Abstract: Disclosed are an optical gradation system and method. The optical gradation system comprises: a first device configured to emit broad-spectrum linearly polarized light in a first polarization direction; a second device provided with at least one first region for splitting lights of different wavelengths mixed in the broad-spectrum linearly polarized light incident by the first device into emergent lights in different polarization directions without changing a beam propagation path; a third device configured to filter out linearly polarized light in a second polarization direction from the emergent lights from the second device in different polarization directions; and, a rotator configured to drive at least one of the first device, the second device and the third device to rotate, wherein the first device, the second device and the third device are arranged coaxially.

Abstract: In some embodiments, a system includes an artificial intelligence (AI) chip and a processor coupled to the AI chip and configured to receive an input image, crop the input image into a plurality of cropped images, and execute the AI chip to produce a plurality of feature maps based on at least a subset of the plurality of cropped images. The system may further merge at least a subset of the plurality of feature maps to form a merged feature map, and produce an output image based on the merged feature map. The cropping and merging operations may be performed according to a same pattern. The system may also include a training network configured to train weights of the CNN model in the AI chip in a gradient descent network. Cropping and merging may be performed over the training sample images in the training work in a similar manner.

Abstract: A method of semiconductor-wafer image alignment is performed at a semiconductor-wafer defect-inspection system. In the method, a semiconductor wafer is loaded into the semiconductor-wafer defect-inspection system. Pre-inspection alignment is performed for the semiconductor wafer. After performing the pre-inspection alignment, a first swath is executed to generate a first image of a first region on the semiconductor wafer. An offset of a target structure in the first image with respect to a known point is determined. Defect identification is performed for the first image, using the offset. After executing the first swath and determining the offset, a second swath is executed to generate a second image of a second region on the semiconductor wafer. While executing the second swath, run-time alignment of the semiconductor wafer is performed using the offset.

Abstract: Disclosed is a guide wire joint, comprising: a first cover board (1), a second cover board (2), a connecting part (3) connecting the first cover board and the second cover board, and a connecting piece (4); the connecting piece (4) can connect the guide wire joint to a medical device; a side of the first cover board (1) and a side of the second cover board (2), both are away from the connecting part (3), are contacted with or separated from each other to adjust closing and opening of the guide wire joint. When the guide wire joint is closed, a guide wire passage (10) is formed between the first cover board (1) and the second cover board (2) allowing the guide wire to pass through and penetrate into a guide wire cavity of a medical device having a C-shaped groove; and when the guide wire joint is opened, the guide wire can be rapidly detached from the guide wire joint, and can be rapidly separated from the medical device.

Abstract: A metal matrix nanocomposite includes: 1) a matrix including one or more metals; and 2) nanostructures uniformly dispersed and stabilized in the matrix at a volume fraction, including those greater than about 3% of the nanocomposite.

Abstract: A glass composition with high Young's modulus and specific modulus, wherein the glass composition includes the following components by weight percentage: 30-46% of SiO2, 0-6% of B2O3, 10-30% of Al2O3, 4-20% of CaO, 2-15% of MgO, and 13-32% of Y2O3. The glass composition uses common chemical raw materials. By reasonably arranging the contents of each component, the glass is good in heat resistance, chemical stability and press-molding devitrification resistance performance, low in high-temperature viscosity, convenient in bubble elimination, with specific modulus above 34 and Young's modulus above 100 GPa, and is suitable for hard disk substrate manufacturing, semiconductor sealing and other fields.

Abstract: Provided herein are nanocrystalline materials comprising, e.g., a matrix including one or more metals; and nanostructures dispersed in the matrix, wherein the matrix is polycrystalline and includes grains having an average size of about 1?m or less. Also provided herein are manufacturing methods of a nanocrystalline materials.

Abstract: A video retrieval system may include a feature extractor configured to extract first feature descriptors for multiple image frames in the query video. The system may also include a feature extractor to extract second feature descriptors for multiple image frames in a candidate video in a video database. The system may include a comparator to compare the first and second feature descriptors to determine a subset of image frames in the candidate video that are similar to the first video. The system may output die query output by displaying the subset of image frames in a slide show. The system may also output the query by displaying a video formed by at least the subset of image frames. The feature extractor may be implemented in a convolution neural network (CNN) in an artificial intelligence (AI) chip. The system may include key frame extractor to detect key frames in the video.

Abstract: An optical characterization system and a method of using the same are disclosed. The system comprises a controller configured to be communicatively coupled with one or more detectors configured to receive illumination from a sample and generate image data. One or more processors may be configured to receive images of dies on the sample, calculate dissimilarity values for all combinations of the images, perform a cluster analysis to partition the combinations of the images into two or more clusters, generate a reference image for a cluster of the two or more clusters using two or more of the combinations of the images in the cluster; and detect one or more defects on the sample by comparing a test image in the cluster to the reference image for the cluster.

Abstract: With the disclosed systems and methods for DRAM and 3D NAND inspection, an image of the wafer is received based on the output for an inspection tool. Geometric measurements of a design of a plurality of memory devices on the wafer are received. A care area with higher inspection sensitivity is determined based on the geometric measurements.

Abstract: A rice cooker assembly uses machine learning models to identify and classify different types of food stored. The rice cooker has a chamber including different compartments for storing different types of food. A camera is positioned to view an interior of the chamber. The camera captures images of the contents of the chamber. From the images, the machine learning model classifies the different types of food stored. The rice cooker determines a mixture of different types of food based on nutrition value and/or taste. The rice cooker creates the mixture and controls the cooking process accordingly. The one or more machine learning models may be resident in the rice cooker or it may be accessed via a network.