AI agents automate atom-by-atom simulations to accelerate discovery of new materials
A team from the U.S. Department of Energy’s (DOE) Argonne National Laboratory has successfully demonstrated an artificial intelligence (AI)-driven system to automate a powerful simulation method that predicts how atoms in materials interact. Known as atomistic simulations, this method can potentially accelerate the discovery of materials for areas such as batteries, aerospace and electronics. The research is published in the journal Digital Discovery.
Princeton researchers have created an artificial intelligence (AI) tool to predict the behavior of crystalline materials, a key step in advancing technologies such as batteries and semiconductors. Although computer simulations are commonly used in crystal design, the new method relies on a large language model, similar to those that power…
Scientific inquiry has always been a journey of curiosity, meticulous effort, and groundbreaking discoveries. Today, that journey is being redefined, fueled by the incredible capabilities of AI. It’s moving beyond simply processing data to actively participating in every stage of discovery, and Google Cloud is at the forefront of this…
Researchers at the University of New Hampshire have harnessed artificial intelligence to accelerate the discovery of new functional magnetic materials, creating a searchable database of 67,573 magnetic materials, including 25 previously unrecognized compounds that remain magnetic even at high temperatures.