Katherine Derbyshire

Humans are still necessary, and no tool does everything, but the potential is significant. Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development. Whether the goal is to identify new applicat... See more

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven software tools that promise to accelerate all three. Many of ... See more

Researchers focus on limiting data movement to reduce power and latency in edge devices. In popular media, “AI” usually means large language models running in expensive, power-hungry data centers. For many applications, though, smaller models running on l... See more

The search for a replacement metal at advanced nodes appears to have a winner — at least for now. Molybdenum is looking increasingly promising as a replacement for a variety of metals commonly used in semiconductor manufacturing today, especially at leadi... See more