Researchers have published research detailing their development of an AI framework to detect defects in additively ...

Researchers built an AI system that adapts to process changes, maintaining defect detection accuracy and lowering retraining costs in smart factories. (Nanowerk News) Artificial intelligence is ...

The AI model rapidly maps boundary conditions to molecular alignment and defect locations, replacing hours of simulation and enabling fast exploration and inverse design of advanced optical materials.

A deep learning model identifies atomic-scale defects in MoS2 with 95% accuracy, offering a faster route to quality control and quantum material research. Defects in 2D materials play a decisive role ...

A research team led by Dr. Jeong Min Park of the Nano Materials Research Division at the Korea Institute of Materials Science (KIMS), in collaboration with Dr. Jaemin Wang and Prof. Dierk Raabe of the ...

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during ...

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, ...

L&T Technology Services Limited has introduced TrackEi, an advanced AI-powered railway track inspection system. Leveraging the NVIDIA Jetson platform, TrackEi enables real-time defect detection and ...

Ekoten Tekstil, a weft knit fabric manufacturer based near İzmir in Turkey, has implemented an artificial intelligence-driven ...