Materials scientists at Rice University have developed a new workflow methodology for measuring microscopic defects in ...

Detecting sub-5nm defects creates huge challenges for chipmakers, challenges that have a direct impact on yield, reliability, and profitability. In addition to being smaller and harder to detect, ...

Detecting macro-defects early in the wafer processing flow is vital for yield and process improvement, and it is driving innovations in both inspection techniques and wafer test map analysis. At the ...

A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.

In the realm of engineering and material science, detecting hidden structures or defects within materials is crucial. Traditional terahertz imaging systems, which rely on the unique property of ...

Semiconductors are used in devices such as memory chips and solar cells, and within them may exist invisible defects that interfere with electrical flow. A joint research team has developed a new ...

Researchers in China have developed a novel deep learning model to detect defects in photovoltaic panels. The approach leverages high-resolution visible light imaging to identify defects using an ...

SiC is extensively used in microelectronic devices owing to its several unique properties. However, low yield and high cost of the SiC manufacturing process are the major challenges that must be ...