Monitor Etch Defects on Dies in the Outer Regions Of The Wafer Using ISR


A technical paper titled "Detection of defective chips from nanostructures with a high-aspect ratio using hyperspectral imaging and deep learning" was published by researchers at Samsung Electronics. Abstract: "We have developed an imaging spectroscopic reflectometry (ISR) method based on hyperspectral imaging and deep learning to detect defects in the bottom region of high-aspect-ratio nan... » read more

Defect Challenges Grow At The Wafer Edge


Reducing defects on the wafer edge, bevel, and backside is becoming essential as the complexity of developing leading-edge chips continue to increase, and where a single flaw can have costly repercussions that span multiple processes and multi-chip packages. This is made more difficult by the widespread rollout of such processes as hybrid bonding, which require pristine surfaces, and the gro... » read more

A Framework For Improving Current Defect Inspection Techniques For Advanced Nodes


A technical paper titled “Improved Defect Detection and Classification Method for Advanced IC Nodes by Using Slicing Aided Hyper Inference with Refinement Strategy” was published by researchers at Ghent University, imec, and SCREEN SPE. Abstract: "In semiconductor manufacturing, lithography has often been the manufacturing step defining the smallest possible pattern dimensions. In recent ... » read more

Visual Fault Inspection Using A Hybrid System Of Stacked DNNs


A technical paper titled "Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks" was published by researchers at Chemnitz University of Technology (Germany). According to the paper, "this contribution introduces a novel hybrid multistage system of stacked deep neural networks (SH-DNN) which allows the localization... » read more

Finding Wafer Defects Using Quantum DL


New research paper titled "Semiconductor Defect Detection by Hybrid Classical-Quantum Deep Learning" by researchers at National Tsing Hua University. Abstract "With the rapid development of artificial intelligence and autonomous driving technology, the demand for semiconductors is projected to rise substantially. However, the massive expansion of semiconductor manufacturing and the develo... » read more