tag: semiconductor defects

Outsmarting Silent Data Corruption In AI Processors With Two-Stage Detection
By proteanTecs - 12 Nov, 2024 - Comments: 0

Silent data corruption is on the rise following advancements in semiconductor technology. The explosion in AI for speech, image, video, and text processing leads to a growing complexity and diversity of hardware systems, bringing an increased risk to data integrity. SDC rate is much higher than software engineers expect, undermining the hardware reliability they used to take for granted. Rec... » read more

Characterizing Defects Inside Hexagonal Boron Nitride (KAIST, NYU, et al.)
By Technical Paper Link - 23 Oct, 2024 - Comments: 0

A new technical paper titled "Characterizing Defects Inside Hexagonal Boron Nitride Using Random Telegraph Signals in van der Waals 2D Transistors" was published by researchers at KAIST, NYU, Brookhaven National Laboratory, and National Institute for Materials Science. Abstract: "Single-crystal hexagonal boron nitride (hBN) is used extensively in many two-dimensional electronic and quantu... » read more

Review of Automatic EM Image Algorithms for Semiconductor Defect Inspection (KU Leuven, Imec)
By Technical Paper Link - 22 Oct, 2024 - Comments: 0

A new technical paper titled "Electron Microscopy-based Automatic Defect Inspection for Semiconductor Manufacturing: A Systematic Review" was published by researchers at KU Leuven and imec. Abstract: "In this review, automatic defect inspection algorithms that analyze Electron Microscope (EM) images of Semiconductor Manufacturing (SM) products are identified, categorized, and discussed. Thi... » read more

Predicting Defect Properties In Semiconductors With Graph Neural Networks
By Technical Paper Link - 24 Oct, 2023 - Comments: 0

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, GE Research, and National Institute of Standards and Technology (NIST). Abstract: "Here, we develop a framework for the prediction and screening of native defects and functional impurities i... » read more

More Accurate And Detailed Analysis of Semiconductor Defects In SEM Images Using SEMI-PointRend
By Technical Paper Link - 10 Mar, 2023 - Comments: 0

A technical paper titled "SEMI-PointRend: Improved Semiconductor Wafer Defect Classification and Segmentation as Rendering" was published (preprint) by researchers at imec, University of Ulsan, and KU Leuven. Abstract: "In this study, we applied the PointRend (Point-based Rendering) method to semiconductor defect segmentation. PointRend is an iterative segmentation algorithm inspired by ima... » read more

Active Learning to Reduce Data Requirements For Defect Identification in Semiconductor Manufacturing
By Technical Paper Link - 24 Oct, 2022 - Comments: 0

A new technical paper titled "Exploring Active Learning for Semiconductor Defect Segmentation" was published by researchers at Agency for Science, Technology and Research (A*STAR) in Singapore. "We identify two unique challenges when applying AL on semiconductor XRM scans: large domain shift and severe class-imbalance. To address these challenges, we propose to perform contrastive pretrainin... » read more

Finding Wafer Defects Using Quantum DL
By Technical Paper Link - 13 Jun, 2022 - Comments: 0

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

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