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 ...

The School of Chemical Engineering (CHEM School) is one of the six schools of Aalto University. It combines natural sciences and engineering in a unique way. We are now looking for: ...

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

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

Using machine learning and math, a Brigham Young University student improved a key tool firefighters rely on during wildfire ...

Long overlooked and underestimated, glial cells – non-neuronal cells that support, protect and communicate with neurons – are ...

Brigham Young University graduate Jane Housley's research could help make a widely used wildfire modeling tool faster and ...

Quantum machine learning (QML) is transitioning from research to practical business applications. Discover how QML is ...

The simulation market is rapidly evolving, driven by advancements in AI, digital twins, and cloud technologies. Industries like automotive, industrial, and smart buildings are adopting simulation for ...

The melting point of lithium chloride can be accurately predicted from simulations by converting liquid salt into a gas (top) and solid crystal into a ...

Scientists have developed a new machine learning approach that accurately predicted critical and difficult-to-compute properties of molten salts, materials with diverse nuclear energy applications.