LLNL researchers are partnering with Hexium, Inc. to address this national need for lithium isotopes.

In a recent study, published in Seismological Research Letters, scientists at LLNL and Lawrence Berkeley National Laboratory (LBNL) simulated earthquake scenarios on the Hayward fault and analyzed how the rupture and underground structure affect ground-motion intensity along the fault.

In a recent study, published in Nature Chemical Biology, a team at LLNL invented a high-throughput platform that screens proteins for their rare-earth element binding preferences at unprecedented scale.

LLNL has been named the 2026 Manufacturer of the Year in the large manufacturer category by the Association of Manufacturers Bay Area (AMBayArea), recognizing the Lab’s leadership in advanced manufacturing, engineering and national security innovation.

LLNL has been selected to lead a project that will receive $4.1 million in funding from the U.S. Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) as part of the Quantum Computing for Computational Chemistry (QC3) program.

Researchers from LLNL, Imperial College London and their collaborators used AI to optimize and 3D printing to create a target that effectively negates the RM instability.

Lawrence Livermore National Laboratory’s Wren Carr was recently selected as a Fellow of SPIE, the international society for optics and photonics.

Researchers from LLNL, the University of Illinois Urbana-Champaign and the University of Kentucky established a novel microbial platform that produces oxalic acid and purifies rare-earth elements.

Thirty-six Lawrence Livermore National Laboratory (LLNL) researchers have been named Distinguished Members of Technical Staff (DMTS) in recognition of their extraordinary scientific and technical contributions, as affirmed by their professional peers and the broader scientific community.

A LLNL-led team of scientists and computational engineers has identified several existing medications that may be associated with longer survival in people with amyotrophic lateral sclerosis (ALS), using one of the largest electronic health record datasets ever assembled for ALS.