How AI and Automation Are Accelerating Scientific Discovery at Berkeley Lab

The Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) is advancing scientific research by embedding artificial intelligence (AI), automation, and data systems directly into the research process. This integration accelerates discovery across fields such as energy, materials science, and particle physics, enhancing national scientific capabilities and supporting the U.S. in global innovation efforts.

Berkeley Lab’s approach combines AI-enabled discovery platforms with shared resources, making research faster, smarter, and more effective. Below are four key areas where AI drives progress at the lab.

Automating Discovery: AI and Robotics for Materials Innovation

Materials science often involves testing thousands of potential compounds—a process that can be slow and labor-intensive. Berkeley Lab uses AI to speed up this cycle significantly.

A-Lab

At A-Lab, an automated materials facility, AI algorithms generate new compound candidates. Robots then prepare and test these materials, creating a rapid feedback loop that shortens validation time for technologies like batteries and electronics.

Autobot

The Molecular Foundry’s Autobot system uses robotics to explore new materials for applications ranging from energy solutions to quantum computing. This system increases both speed and flexibility in lab experiments.

Smarter Instruments: AI for Real-Time Optimization

Operating advanced instruments such as accelerators and light sources requires precise control. AI models help optimize these instruments during operation, improving stability and efficiency.

The Berkeley Lab Laser Accelerator (BELLA)

Machine learning at BELLA tunes laser and electron beams, reducing the need for manual calibration and enhancing performance. These improvements open new possibilities for scientific research and industrial uses.

The Advanced Light Source Upgrade (ALS-U)

Deep-learning AI controls are applied at the Advanced Light Source to optimize beam performance. These methods will be integral to the ALS-U upgrade, which aims to deliver one of the brightest soft x-ray sources worldwide for industry and research.

Speeding Up Data: Automated Analysis

Modern experiments generate massive data volumes. Berkeley Lab uses AI and automation to analyze data rapidly, sometimes in real time, enabling scientists to adjust experiments while they are still running.

Supercomputing for On-Demand Insights

Data from instruments like microscopes and telescopes is streamed to Berkeley Lab’s supercomputers. For example, the Molecular Foundry’s Distiller platform sends electron microscopy data to the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), where it is analyzed within minutes. This real-time processing allows immediate experimental adjustments, saving time and resources.

Fusion Research

At NERSC, machine learning predicts particle behavior in fusion plasmas. These insights have potential to guide control systems in future fusion reactors.

AI for Network Optimization at ESnet

Berkeley Lab’s high-performance network, ESnet, applies AI to forecast and resolve network traffic issues. As data volumes increase, this ensures smooth, high-speed collaboration across national labs and research partners.

Generating Breakthroughs: AI as Co-Creator

Probing AI Predictions

AI serves as a research partner, not just a tool. Berkeley Lab scientists validate AI-generated discoveries from other labs. For instance, after medical researchers designed a novel enzyme using AI, Berkeley Lab’s Advanced Light Source analyzed samples to confirm the design’s accuracy. This collaboration accelerates development of new proteins with applications in medicine, energy, and beyond.

AI Embedded in the Future of Science

Berkeley Lab’s integration of AI with robotics, instrumentation, and data systems is reshaping how science is conducted. By automating repetitive tasks and enabling real-time data analysis, researchers focus more on discovery. This smarter, faster infrastructure prepares the lab to tackle upcoming scientific challenges effectively.

The Advanced Light Source (ALS), National Energy Research Scientific Computing Center (NERSC), Energy Sciences Network (ESnet), and Molecular Foundry are user facilities under the DOE Office of Science.

About Lawrence Berkeley National Laboratory

Founded in 1931, Berkeley Lab conducts pioneering research in materials, chemistry, physics, biology, earth sciences, mathematics, and computing. It supports researchers worldwide with top-tier scientific facilities and has earned 16 Nobel Prizes. Managed by the University of California, the lab operates under the U.S. Department of Energy’s Office of Science, the country’s largest supporter of basic physical sciences research.

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