AI captures particle accelerator behavior to optimize machine performance

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 ...
POWER Magazine

DOE Details 26 Genesis Mission AI Challenges, Targeting Nuclear Timelines, Grid Planning, and Energy Systems

The Department of Energy (DOE) has released specifications for 26 artificial intelligence (AI) challenges under its Genesis Mission that could reshape how ...

Machine learning reveals hidden landscape of robust information storage

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

When machine learning shows its reasoning, electrocatalyst discovery accelerates

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
College of Computing - Georgia Tech

Department of Energy Award to Power Nuclear Research with Machine Learning

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 ...
Frontiers

Advancing Georeservoir Performance using Artificial Intelligence

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

Intravital calcium imaging of meningeal macrophages reveals niche-specific dynamics and aberrant responses to brain hyperexcitability

This valuable study presents a technically sophisticated intravital two-photon calcium imaging approach to characterize Ca²⁺ dynamics in distinct populations of meningeal macrophages in awake, freely ...