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 ...

Researchers at Sandia National Laboratories and Auburn University have developed a new method to more accurately detect ...

As the semiconductor world excitingly explores the potential of new advanced package solutions for their intricate and novel designs, challenges arise from undetected defects caused by the complexity ...

A recent review article published in Advanced Materials explored the potential of artificial intelligence (AI) and machine learning (ML) in transforming thermoelectric (TE) materials design. The ...

This study is led by Prof. Shuangyin Wang (College of Chemistry and Chemical Engineering, Hunan University) and Prof. Chen Chen (College of Chemistry and Chemical Engineering, Hunan University).

Applied Materials has launched the SEMVision™ H20, a new defect review system designed to enhance the analysis of nanoscale defects in advanced semiconductor chips. This system utilizes cutting-edge ...

Two-dimensional (2D) materials show great promise for photocatalysis, a key technology for sustainable energy solutions like water splitting. However, optimizing their performance requires precise ...

An international research team has pioneered a new technique to identify and characterize atomic-scale defects in hexagonal boron nitride (hBN), a two-dimensional (2D) material often dubbed 'white ...

Defect states refer to electronic energy levels that arise from imperfections or irregularities in the crystal structure of materials, particularly in semiconductors and insulators. These ...