The Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) is at the forefront of a global shift in how science gets done—one driven by artificial intelligence, automation, and powerful data systems. By integrating these tools, researchers are transforming the speed and scale of discovery across disciplines, from energy to materials science to particle physics.

This integrated approach is not just advancing research at Berkeley Lab—it’s strengthening the nation’s scientific enterprise. By pioneering AI-enabled discovery platforms and sharing them across the research community, Berkeley Lab is helping the U.S. compete in the global race for innovation, delivering the tools and insights needed to solve some of the world’s most pressing challenges.

From accelerating materials discovery to optimizing beamlines and more, here are four ways Berkeley Lab is using AI to make research faster, smarter, and more impactful.

At the heart of materials science is a time-consuming process: formulating, synthesizing, and testing thousands of potential compounds. AI is helping Berkeley Lab speed that up—dramatically.

A-Lab
At Berkeley Lab’s automated materials facility, A-Lab, AI algorithms propose new compounds, and robots prepare and test them. This tight loop between machine intelligence and automation drastically shortens the time it takes to validate materials for use in technologies like batteries and electronics.

Autobot
Exploratory tools like Autobot, a robotic system at the Molecular Foundry, are being used to investigate new materials for applications ranging from energy to quantum computing, making lab work faster and more flexible.