Techniques such as Raman spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), and ...

Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

Researchers have used machine learning to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the ...

Businesses are still new at this. Here are some things to know about how to go about AI integration the right way.

IoT-based sensors, when deployed within biofloc tanks, can continuously track critical parameters such as dissolved oxygen ...

A response to recent largesse of large language modeling material. Reading the Communications March 2025 issue, it struck me ...

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

XRM microscopy, combined with machine learning, revolutionizes materials research by enhancing imaging techniques for failure ...

As companies rush to adopt new AI solutions, business leaders must understand the different types and how AI compares to ...

I am a computational biologist interested in interpretable machine learning for genomics and health care. Interpretable ...

Semiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the ...

Conventional robots, like those used in industry and hazardous environments, are easy to model and control, but are too rigid ...