Defects in transistors, such as unwanted impurities and broken chemical bonds in the various layers of the semiconductor, can limit their performance and reliability. These defects are becoming harder ...

Instrumental's AI-powered Synchronized Learning detects defects in high-density connectors with 99.9% accuracy — ...

Scientists report the development of a method that determines the density of defects in two-dimensional nanomaterials due to measurements of spatial coherence of light that strike them. A UPM ...

Semiconductors based on gallium-nitride (GaN) substrates are increasingly important in the power-device landscape. Their thermal conductivity, and thus their ability to conduct and dissipate heat, is ...

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, ...

Whether you’re using a leading-edge process node to manufacture a very large system-on-chip (SoC), or using an established node for automotive or Internet of Things (IoT) electronics, critical area ...

Originating as a theoretical prediction in the 1940s, with experimental isolation from graphite in 2004, graphene has quickly become a desirable quantum material used in various application areas, ...

Chemical mechanical planarization (CMP) is required during semiconductor processing of many memory and logic devices. CMP is used to create planar surfaces and achieve uniform layer thickness during ...