Accurately predicting ground shaking is vital for seismic hazard assessment and infrastructure safety. However, infrequent, large-magnitude events are difficult to model due to the paucity of data from ground motion sensors of past events a…
Predicting exactly how fuel burns in heavy-duty engines, gas turbines, and rocket motors is essential to optimizing performance and preventing equipment damage, but running physical experiments in these extreme environments is notoriously d…
Software Advancement Berkeley Lab researchers have developed a highly specialized AI assistant named AstraAI, specifically designed to help scientists write code for the world’s most powerful supercomputers. By studying the complex structur…
To harness biological systems (plants and microbes) for next-generation energy production and advanced materials, researchers are looking to beneficial plant-microbe interactions. Because these are complex systems, it has proven difficult t…
Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the spin of electrons in spin-based optoelectronics or spintronics, but getting them to perform consistently has proven di…
Breakthrough: Quantum computers offer a powerful tool for discovering new materials and chemical processes. But hardware limitations have largely confined computational studies of molecules to their most basic, resting states. Berkeley Lab
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models de…
Yelick is a leading computer scientist with a highly distinguished research and leadership career at UC Berkeley and Berkeley Lab. She is currently the Vice Chancellor for Research and the Robert S. Pepper Distinguished Professor of Electri…
One new foundation model developed by researchers at the National Energy Research Scientific Computing Center (NERSC) and collaborators represents major progress in the establishment of these models. OmniLearned, a new iteration of a previo…
They’ll host the 2026 Deep Learning for Science (DL4SCI) Summer School, a five-day intensive program assembling researchers and engineers to explore the latest advances in deep learning and AI. Hosted at Berkeley Lab from July 20–24, the 20…
Smaller than the full-size system, the EAS gives NERSC staff and the system vendor, Dell Technologies, the opportunity to refine assembly, delivery, installation, and integration processes, paving the way for seamless deployment of the full…
Today’s state-of-the-art quantum computers rely on powerful classical high‑performance computers for control, calibration, and error correction. As quantum processing units (QPUs) grow from dozens to thousands of qubits, the real‑time measu…