Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...

A new low-power sensor node framework combines sensing and machine learning, with the potential to enhance real-time ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...

Can you design a mechanism that will trace out the shape of a heart? How about the shape of a moon, or a star? Mechanism ...

Stearns and Poletti present a technically impressive study that aims to uncover a deeper understanding of microsaccade function: their role in perceptual modulation and the associated temporal ...

South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.

Georeservoir engineering—including petroleum, geothermal, and CO₂ sequestration systems—plays a pivotal role in advancing global energy production, storage, ...

Spain and Portugal are still reeling from the largest power cut in recent European history, which struck just after midday on Monday. With power supplies mostly back to normal, attention is ...