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Meet EcoBOT: The Autonomous Lab Standardizing Plant-Microbe Research

A robotic arm in a high-tech laboratory holds up a small, clear plastic container that houses a single green plant seedling. Below the raised container is an out-of-focus grid of many similar clear plastic boxes. The scene is illuminated by bright, cool blue and green lights that reflect off the plastic and metallic machinery, giving it an automated, futuristic appearance.

Scientists Develop Predictive Roadmap to Boost Performance in Next-Gen Spintronics

Scanning electron microscope (SEM) image of a chiral 2D metal halide perovskite material synthesized with acetonitrile. Chiral perovskite films made with acetonitrile respond strongly to circularly polarized light.

New MatterChat Model Helps AI to ‘See’ the Language of Science

A conceptual diagram for "MatterChat: A Structure-Aware Multimodal LLM for Materials." The graphic shows a visual data flow starting from a 3D atomic structure on the left, passing through a bottleneck labeled "Bridge Model," and feeding into a digital interface labeled "LLM." The LLM interface lists various materials science terms like structure, property, synthesis, and stability, with a glowing AI brain floating on the far right.

OmniLearned Foundation Model Shows Promise Across Disciplines

Technical image of a hadronic jet

DL4SCI 2026 to Spotlight Discovery through Agentic AI, Foundation Models

Photo of a large group of people standing under a tree at Berkeley Lab

SciData Workshop Brings Community Together To Reflect, Collaborate, And Look Ahead

Mathematical Innovation Advances Complex Simulations for Science’s Toughest Problems

A two-part diagram illustrating a mathematical framework for simplifying complex models. The top diagram shows a V-shaped path of blue arrows enclosing a horizontal line that extends from a point labeled '0' towards an infinity symbol. Small circles along the line represent key numbers describing a system's dynamics. The blue path illustrates a calculation where orange and green segments at the far right can be ignored, allowing scientists to focus on the system's essential features for faster results. The bottom diagram shows a horizontal line with colored tick marks representing a random process visiting different states over time. Above the line, red brackets group larger sets of states into repeating loops, or cycles. Below the line, blue brackets highlight more specific cycles. This illustrates how analyzing these cycles can simplify and speed up complex simulations.

New ESnet Report Looks at AI-Powered Future for Scientific Networking

Illustration ESnet AI Rendered

Expert Interview: Sean Peisert on Cybersecurity Research

Deep Learning School Convenes AI Experts, Researchers

Taking Big Steps, Berkeley Lab Scientists Shape Improvements in Topological Optimization

A view of Mount Everest, the world's highest peak, covered in snow and ice.

Berkeley Lab Researchers Help Accelerate Fusion Progress Through Machine Learning Algorithms

An image of the Perlmutter supercomputer.
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