Researchers at Lawrence Livermore National Laboratory and Stanford University announced in December they have demonstrated a new 3D nanofabrication approach that they say transforms two-photon lithography (TPL) from a slow, lab-scale technique into a wafer-scale manufacturing tool without sacrificing submicron precision. Published in Nature, the team’s TPL platform uses large arrays of metalenses — engineered, ultrathin […]
LLNL, Stanford Researchers Report 3D Nanofabrication Approach for TPL Wafer-Scale Manufacturing
January 6, 2026 by
Livermore Lab to Host HPC4EI Manufacturing Workshop Oct. 28-30
September 29, 2025 by
Sept. 29 — The U.S. Department of Energy’s (DOE) High-Performance Computing for Energy Innovation (HPC4EI) initiative will host an in-person workshop, Tuesday-Thursday, Oct. 28-30, to review program operations and explore future directions. The event will take place at the University of California Livermore Collaboration Center at Lawrence Livermore National Laboratory in Livermore, CA. The program […]
AI for Science: Livermore Lab Expands Deployment of Anthropic AI
July 9, 2025 by
Lawrence Livermore National Laboratory is expanding its deployment of Anthropic’s Claude for Enterprise to its entire laboratory. Claude will be available to about 10,000 scientists ….
HPC News Bytes 20250106: ‘Beyond’ EUV Lithography, China Chip Sanction Workaround, Microsoft’s $80B AI Build-Out, TSMC 2nm in 2025
January 6, 2025 by
Here’s a rapid (5:54) rundown of recent news from the HPC-AI sector, including: DOE and LLNL lead effort to go ‘beyond’ EUV lithography, report: ByteDance pursues chip trade sanction workaround, Microsoft’s $80B AI ….
Livermore Lab Team Boosts Trust in AI for Science by Making Machine Learning Explainable
August 1, 2023 by
As machine learning techniques become increasingly used in the sciences, a team of researchers in Lawrence Livermore National Laboratory’s Computing and Physical and Life Sciences directorates are trying to provide a reasonable starting place for scientists who want to apply machine learning but lack a strong ML background. The goal is to help users understand […]
