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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Triply-twinned body-centred cubic lattices shift strut-scale deformation from bending to stretching, producing major gains in ...