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Interphases — the multicomponent interlayer structures that emerge between electrodes and electrolytes in batteries — critically determine the performance and durability of electrochemical cells. (Graphic: Sabrina Wan)

Machine learning uncovers how battery interphases can boost lithium-ion transport

Sandwiched between the electrolyte and electrodes in a lithium-ion battery is a remarkably thin layer of material that strongly dictates battery performance and durability: the interphase. Although typically only a few to tens of nanometers thick, interphases are among the least understood components of an operating battery cell. Their complex and constantly evolving…

NASA Administrator Jared Isaacman’s remarks focused on achieving NASA’s goals of returning to the Moon through the Artemis missions, future efforts to explore Mars and beyond, and the potential for nuclear-powered propulsion for those missions. Photo: Blaise Douros.

NASA administrator Isaacman visits LLNL on ‘Inspiration Tour’

NASA Administrator Jared Isaacman led a return visit to Lawrence Livermore National Laboratory (LLNL) on Sept. 2 as part of NASA’s “Inspiration Tour,” meeting with Lab scientists and engineers to highlight LLNL’s capabilities in areas including space science, national security, fusion, computing and other advanced technologies. Isaacman, who was joined by Department of…

Participants in the Drone Design & Application Teacher Research Academy pose outside the drone pen after flight instruction from Claire Knight, Mechanical Team Lead for the Autonomous Sensors Program, far left. Photo Credit: Randy Wong, LLNL.

Teacher Research Academy connects educators to LLNL science

For nearly 30 years, LLNL has offered Teacher Research Academy (TRA) to middle school, high school and community college teachers looking for unique professional development experiences. At no cost to educators, TRA workshops offer classroom-focused applications of LLNL’s groundbreaking science and technology. Over two weeks this summer, four different TRAs were offered as…

LLNL and NIST researchers have found a more robust method for entangling qubits by applying a ramped force (top). The approach controls trajectories in phase space (bottom) and allows for more precise entanglement control.

A more robust way to create entanglement in trapped ion qubits

While quantum computing could be the future, it is currently plagued by finicky hardware. To make the technology practical, researchers must demonstrate that it consistently and continuously works and performs at scale. In a new study, published in Physical Review Letters, researchers at Lawrence Livermore National Laboratory (LLNL) and the Ion Storage Group at the…

Attendees at the first Decision Superiority Summit hosted by Lawrence Livermore National Laboratory.

First Decision Superiority Summit explores making better decisions faster

“The history of failure in war can almost be summed up in two words: too late.” General Douglas MacArthur’s warning underscored the urgency and importance of the first Decision Superiority Summit, hosted this summer by Lawrence Livermore National Laboratory (LLNL), where Department of War (DOW) decision makers, scientists, engineers and analysts explored how computer…

A new episode of the Big Ideas Lab podcast takes listeners inside STARMOC at Lawrence Livermore National Laboratory. Available now on Apple and Spotify.

Big Ideas Lab podcast explores STARMOC: LLNL’s mission operations center

From off-roading in rural Nevada to commuting during rush hour on the 405 in Los Angeles, the space domain has undergone a rapid transformation over the past five years. What began as a vast landscape with a few high-profile, large-scale missions is now a heavily trafficked orbital freeway, rife with accident debris and security risks. To navigate this new environment,…

Nearly 100 Lawrence Livermore National Laboratory students, mentors and staff joined colleagues from across the Department of Energy complex on July 10 for a hands-on clinic focused on using agentic artificial intelligence tools in real scientific and technical work.

LLNL students, mentors put agentic AI tools to work at cross-laboratory clinic

Nearly 100 Lawrence Livermore National Laboratory (LLNL) students, mentors and staff joined colleagues from across the Department of Energy (DOE) complex recently for a hands-on clinic focused on using agentic artificial intelligence tools in real scientific and technical work. Held in the Lab’s Research Library, the 2026 Cross-Laboratory AI Clinic combined shared…

Lawrence Livermore National Laboratory is increasingly looking to AI, robotics and automation to help speed the process of advanced manufacturing. Pictured are (l-r) Robotics and Automation scientists and engineers Tony Qin, Karly Knox, Abhik Sarkar, Aldair Gongora and Michael Troksa. Photo: Blaise Douros/LLNL.

How LLNL is using AI, robotics and automation to accelerate advanced manufacturing

Lawrence Livermore National Laboratory (LLNL) scientists and engineers, in conjunction with the Department of Energy (DOE) and National Nuclear Security Administration (NNSA), are increasingly looking to AI, robotics and automation to help accelerate advanced manufacturing, materials discovery and experimental science. The work is part of a broader push to move faster from…

Genesis Mission graphic

LLNL selected to lead 10 projects under DOE’s Genesis Mission

Lawrence Livermore National Laboratory (LLNL) scientists and engineers have been selected to lead 10 Phase I projects under the U.S. Department of Energy’s (DOE’s) Genesis Mission, applying AI to challenges spanning high-performance computing (HPC), fusion energy, Earth systems science, materials discovery, biology, quantum technologies and fundamental physics. LLNL…

Battery diagram

With machine learning, LLNL researchers embrace the atomic-scale complexity of batteries

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National Laboratory (LLNL) scientists are tackling that challenge in many ways, but one approach is making a significant impact: physics-informed machine learning. In two recent publications, LLNL researchers examined how integrating molecular dynamics…

Participants and instructors work through a hands-on activity at the 2025 Real-World Quantum Computing workshop.

Registration open for Real-World Quantum Computing workshop at LLNL

Registration is now open for the 2026 Real-World Quantum Computing workshop, jointly hosted by Lawrence Livermore National Laboratory (LLNL) and San Jose State University (SJSU). The two-day workshop is designed for upper-level undergraduates and graduate students in engineering, physics or related fields. Interns are encouraged to apply. Applications will be accepted on a…

Officials with the National Nuclear Security Administration (NNSA), Lawrence Livermore National Laboratory, the NNSA Livermore Field Office and project management teams cut the ribbon marking the completion of the Digital Infrastructure Capability Expansion facility on June 9. The event celebrated a major milestone in a decade-long effort to modernize one of the Lab’s most critical infrastructure systems. Photo: Glenn Silva/LLNL

NNSA, LLNL officials celebrate completion of critical Lab digital infrastructure upgrade

Officials with the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laboratory (LLNL) celebrated the completion of the Digital Infrastructure Capability Expansion (DICE) facility on June 9, marking a major milestone in a decade-long effort to modernize one of the Lab’s most critical infrastructure systems. The 13,000-square-foot facility,…

A complex system of cooling towers, chillers, pumps, heat exchangers, sensors and more than 2,000 feet of pipes all work together to remove heat from the liquid-cooled exascale supercomputer El Capitan. Graphic: Dan Herchek.

Meet the machines that matter: How El Capitan keeps its cool

LLNL tackles the nation’s toughest security challenges through bold, multidisciplinary science powered by advanced facilities and instruments. In this four-part series, meet the machines that work behind the scenes at the Laboratory to drive discovery, push boundaries and enable excellence. From inspecting optics and trapping ions to cooling supercomputers and detecting…

Big Ideas Lab genesis mission graphic

Big Ideas Lab explores how the Genesis Mission aims to accelerate scientific discovery

Scientific discovery has always moved through a familiar cycle: question, hypothesis, experiment and a result. In the latest episode of the Big Ideas Lab podcast, Lawrence Livermore National Laboratory (LLNL) explores how the Department of Energy’s (DOE) Genesis Mission aims to accelerate that process by uniting AI, high-performance computing (HPC), experiments and the…

HPC4 Energy Innovation

DOE opens new HPC4EI call to connect US manufacturers with national-lab supercomputing

The U.S. Department of Energy (DOE) has opened a new call for proposals under the High-Performance Computing for Energy Innovation (HPC4EI) program, a national initiative managed by Lawrence Livermore National Laboratory (LLNL) that connects U.S. manufacturers with the computing power and scientific expertise of DOE’s national laboratories. The program invites companies to…

Ground motion simulation of a magnitude 7 earthquake on the Hayward fault using the Lawrence Berkeley National Laboratory-Lawrence Livermore National Laboratory Earthquake Simulation platform.

Simulations predict ground motion for earthquakes on Bay Area’s Hayward fault

The Hayward fault, part of the larger San Andreas fault system, runs 74 miles through the East Bay of the San Francisco Bay Area. The fault is overdue for an earthquake that could cause extensive damage to such a dense population zone. In a recent study, published in Seismological Research Letters, scientists at Lawrence Livermore National Laboratory (LLNL) and Lawrence…

With recently awarded funding, LLNL will develop quantum and machine learning-accelerated software tools and apply them to discovering ultra-strong, lightweight magnets that are crucial for electronic motors, generators and high-performance information technology. (Image: Janelle Cataldo / LLNL)

LLNL to harness quantum computing for next-generation magnets

Lawrence Livermore National Laboratory (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. QC3 seeks to develop and apply quantum algorithms to accelerate simulations of chemistry…

Connie Castaneda Aniceto, a senior technical recruiter LLNL’s Talent Acquisition team, helps connect candidates with roles across the Lab and supports hiring managers through the recruitment process. (Photo: Garry McLeod/LLNL)

Meet LLNL: Senior Technical Recruiter Connie Castaneda Aniceto

For the past three years, Connie Castaneda Aniceto has helped people take an important step: joining Lawrence Livermore National Laboratory (LLNL). Aniceto is a senior technical recruiter on LLNL’s Talent Acquisition team, where she has worked since March 2023 supporting organizations including the National Ignition Facility, Computing, Engineering and Global Security…

Lawrence Livermore National Laboratory scientists and computational engineers report on using machine learning to analyze electronic health records of more than 11,000 veterans diagnosed with amyotrophic lateral sclerosis (ALS)

LLNL-led study uses machine learning, veterans’ health records to identify ALS drug-repurposing candidate

A Lawrence Livermore National Laboratory (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. Published in The Lancet Digital Health, the study…

The 2026 DMTS cohort is pictured here

LLNL honors 36 as 2026 Distinguished Members of Technical Staff

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. As distinguished citizens of the Laboratory and their respective fields, DMTS honorees…