Interpretable AI in materials discovery: Uncovering how models make predictions

A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has ...
EurekAlert!

Interpretable AI unlocks new thermal material frontiers

The calculation and/or the measurement of the thermal conductivity of materials is a fundamental challenge in materials science, essential for developing technologies in energy management, electronics ...
Science Daily

Novel machine learning model can predict material failure before it happens

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...
EurekAlert!

Reinforcement learning world models for catalyst surface reconstruction: state-of-the-art review

This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...
Microsoft

Discoveries in weeks, not years: How AI and high-performance computing are speeding up scientific discovery

Computing has already accelerated scientific discovery. Now scientists say a combination of advanced AI with next-generation cloud computing is turbocharging the pace of discovery to speeds ...