Samsung Electronics Co., Ltd.

Seoul National University

Mincheol Kang

Kihyun Kim

Sangwook Park

Sooyong Lee

Sooryong Lee

Jeeyong Lee

Kyenhee Lee

Donyun Kim

Yunhyoung Nam

SungJoon Park

Heungsuk Oh

Woojoo Sim

Useong Kim

Nohong Kwak

Bongsoo Kang

A computer networking device includes a plurality of ports, a memory, and a computing unit. The computing unit receives source information and destination information for a snapshot from the host; obtains a read-value of a memory area corresponding to the source information in a memory device through a port identified based on mapping information and the source information; and transmit, to a storage device, the read-value based on peer-to-peer communication for a write operation of writing in a memory area corresponding to the destination information in the storage device through a port identified based on the mapping information and the destination information.

Computer communication device with inter-device data copying

There are provided a method of accurately detecting a measurement error of SEM equipment by comparing and aligning a design image with an SEM image, and a method of accurately aligning SEM equipment based on a detected measurement error. The method of detecting a measurement error of SEM equipment includes acquiring SEM images of a measurement target, performing pre-processing on the SEM images and design images corresponding thereto, selecting training SEM images from among the SEM images, performing training by using the training SEM images and training design images and generating a conversion model between the SEM images and the design images, converting the SEM images into conversion design images by using the conversion model, extracting an alignment coordinate value by comparing and aligning the conversion design images with the design images, and determining a measurement error of the SEM equipment based on the alignment coordinate value.

Method of detecting measurement error of SEM equipment and method of aligning SEM equipment

The inventive concept provides a defect detection method of a semiconductor element, capable of promptly and accurately detecting a defect, and predicting a type of the defect with respect to various defects of the semiconductor element, and a semiconductor element manufacturing method including the defect detection method. The defect detection method is capable of promptly and accurately detecting the defect, and predicting the type of the defect with respect to various defects of the semiconductor element, by generating a first segmentation image and a second segmentation image; converting the first segmentation image and the second segmentation image into an image of a first color and a second color, respectively; generating a combination image; classifying the type of a defect; generating a defect detection model by using deep learning, and detecting a defect of the semiconductor element by using a defect detection process using the defect detection model.

Defect detection method of deep learning-based semiconductor device and semiconductor element manufacturing method including the defect detection method

Provided are a method of forming a mask, the method accurately and quickly restoring an image on the mask to the shape on the mask, and a mask manufacturing method using the method of forming the mask. The method of forming a mask includes obtaining first images by performing rasterization and image correction on shapes on the mask corresponding to first patterns on a wafer, obtaining second images by applying a transformation to the shapes on the mask, performing deep learning based on a transformation relationship between ones of the first images and ones of the second images corresponding to the first images, and forming a target shape on the mask corresponding to a target pattern on the wafer, based on the deep learning. The mask is manufactured based on the target shape on the mask.

Method of forming shape on mask based on deep learning, and mask manufacturing method using the method of forming the shape on mask

A method of fabricating a semiconductor device includes generating a mask based on second layout data obtained by applying an OPC model to first layout data and performing a semiconductor process using the mask on a substrate, obtaining a plurality of pattern images by selecting a plurality of sample patterns from the substrate, selecting sample images corresponding to the sample patterns from each of the first layout data, the second layout data, and simulation data obtained by performing a simulation based on the second layout data, generating a plurality of input images corresponding to the sample patterns by blending the sample images corresponding to the sample patterns, respectively, and generating an error prediction model for the OPC model by training a machine learning model using a data set including the input images and the pattern images.

Method of verifying error of optical proximity correction model

A method of manufacturing a semiconductor device includes forming a lower mold having lower layers stacked on a substrate and lower channel structures passing therethrough; forming an upper mold including upper layers stacked on the lower mold and upper channel structures passing therethrough; removing the upper mold to expose an upper surface of the lower mold; separating an upper original image in which traces of the upper channel structures are displayed, and a lower original image in which the lower channel structures are displayed, from an original image capturing the upper surface of the lower mold; inputting the upper original image into a learned neural network to acquire an upper restored image in which cross sections of the upper channel structures are displayed; and comparing the upper restored image with the lower original image to verify an alignment state of the upper and lower molds.

Growing community of inventors

Hwaseong-si, South Korea

Mincheol Kang