MicroBooNE, Machine Learning, and Liquid Argon
The MicroBooNE experiment demonstrates the use of machine learning to interpret images made by a liquid-argon particle detector.
The MicroBooNE experiment demonstrates the use of machine learning to interpret images made by a liquid-argon particle detector.
New crime scene investigation technique offers a hard look at the traces that particles leave before fleeing the scene.
Scientists developed a method to better distinguish the tracks that particles leave behind in liquid argon.
A careful consideration of electric fields could lead to faster industrial processes that use less energy and release less waste.
Element-selective method reveals interfacial properties of materials used for water purification, catalysis, energy conversion, and more.
Recovery of more than 1500 microbial genomes shines light on how carbon is metabolized as permafrost thaws.
Six cameras are revolutionizing observations of shallow cumulus clouds.
New insights into molecular-level processes could help prevent corrosion and improve catalytic conversion.
Scientists discover key types of microbes that degrade organic matter and release carbon dioxide and methane into the atmosphere.
Artificial intelligence on Summit to discover atomic-scale structures.
Ultrafine aerosol particles produce bigger storm clouds and more precipitation than larger aerosols in pristine conditions.
Scientists explore how drought-tolerant plants communicate to nearby microorganisms, suggesting ways to engineer more resilient bioenergy crops.