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HPC, Simulation, and Data Science

On May 7, Lawrence Livermore National Laboratory (LLNL) Director Kim Budil, fourth from left, joined a public-private panel on AI for science, where she highlighted LLNL capabilities and AI focus areas, including the National Ignition Facility, El Capitan, high-fidelity modeling and simulation and advanced materials and manufacturing. (Photo: Jeremy Thomas)

LLNL showcases AI-enabled science, national security and energy innovation at AI+ Expo

Lawrence Livermore National Laboratory (LLNL) leaders, scientists and engineers joined national voices at the Special Competitive Studies Project’s (SCSP) AI+ Expo May 7-9 in Washington, D.C., highlighting how AI is reshaping science, security and energy innovation. The public Expo brought together government, industry, academic and Department of Energy (DOE) national…

LLNL’s advanced optics system for Ocula, featuring the Lab’s state-of-the-art monolithic telescope, will capture high-resolution ultraviolet and visible images of the lunar surface onboard Firefly’s Elytra spacecraft in lunar orbit. (Photographer: Gary McLeod)

LLNL optics system set to fly to the moon with Firefly Aerospace for Ocula imaging service

A team of scientists at Lawrence Livermore National Laboratory (LLNL) recently delivered a high-resolution optics system to Firefly Aerospace in support of Firefly’s Ocula commercial lunar imaging service. The payload is scheduled to fly onboard Firefly’s Elytra spacecraft in lunar orbit as part of Blue Ghost Mission 2, targeted to launch no earlier than late 2026. The…

At LLNL’s STEM with Phones summer workshop, Daniel Kim participated in a demonstration on how a smartphone can be used for scientific research and data analysis. (Photo: Garry McLeod)

AI expands what research projects students can accomplish at LLNL’s STEM with Phones workshop

Forget spreadsheets. At Lawrence Livermore National Laboratory’s (LLNL) STEM with Phones student workshop, students are using smartphones and artificial intelligence (AI) to conduct advanced scientific analysis. Led by LLNL’s David Rakestraw, participants in the program discover how to turn a tool already in their pocket — a smartphone — into an instrument for…

LLNL scientists Nicholas Watkins and Sankar Raju Narayanasamy run a high-throughput screening system to test hundreds of enzymes for their ability to break down cellulose. (Photos: Blaise Douros/LLNL)

Screening enzymes to break down plant waste and produce valuable biofuels

Locked away inside the walls of plant cells lies a valuable source of energy: sugar. But to access that sugar — which could provide a domestic source of bioenergy that strengthens U.S. energy security — researchers must first break down cellulose, the structural component of plant cell walls. A team at Lawrence Livermore National Laboratory (LLNL) has designed two high…

The Big Ideas Lab podcast, with a nighttime satellite photo of the U.S.

Big Ideas Lab podcast spotlights how Skyfall defends the power grid from cyberattacks

A blackout spread across more than a hundred cities in Ukraine after malware infected the nation’s power grid. This sophisticated breach was the first of its kind, speaking the language of the industrial control systems to carry out a remote operation on physical infrastructure. The incident led U.S. Department of Energy national security experts to ask: what would happen…

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…

ARAC scientist Marv Dickerson keeps members of the media informed about the status of radioactive releases from the Chernobyl nuclear meltdown. (LLNL Archives)

Four decades after Chernobyl, National Atmospheric Release Advisory Center reflects on a defining moment

Documents were scattered across the floor as scientists hurriedly reviewed reports on weather patterns and radiation measurements, while colleagues in Europe awaited updates and information on the emerging radioactive crisis. Forty years later, the Chernobyl reactor accident response stands as critical experience that paved the way for what is now the National Atmospheric…

LLNL researchers invented a high-throughput platform that screens proteins for their rare earth element binding preferences at unprecedented scale. (Photos: Blaise Douros/LLNL)

New protein-screening platform accelerates rare-earth separation for U.S. supply chain

To ensure a robust domestic supply chain in the U.S., Lawrence Livermore National Laboratory (LLNL) scientists are using bacterial proteins to separate the rare-earth elements that are ubiquitous in magnets, batteries and electronics. These proteins, called lanmodulin, evolved in bacteria that use rare-earth elements to power their metabolism. But to scale up and advance…

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…

Adding an optimized void structure (top right) counteracts a shockwave-induced instability, reducing jetting (bottom right) that can interfere with inertial confinement fusion. Without this void, significant jetting occurs (bottom left). (Image: Strucka et al.)

Looking into the void to cancel out material instabilities

Picture two materials sandwiched together. The boundary between them may appear flat, but, in reality, it is full of tiny bumps and dents. Suddenly, the materials are hit with a shockwave. If that wave hits a bump in the material interface, it slows down. If it hits a dent, it accelerates forward. This imbalance creates fast, narrow jets of material — called the Richtmyer…

Lawrence Livermore National Laboratory has announced five research teams selected for awards through the Lab’s FY26 Academic Collaboration Team annual call for proposals.

Weapons Physics & Design ACT awards drive university partnerships and research

Lawrence Livermore National Laboratory (LLNL) has announced five research teams selected for awards through the Lab’s FY26 Academic Collaboration Team (ACT) annual call for proposals. Awards support university research partners for up to three years to perform research in collaboration with Lab scientists and offer an important way to build long-term connections with…

Big Ideas Lab podcast is marking a new milestone with the release of its 50th episode

All 50 episodes of the Big Ideas Lab now available on LLNL podcast page

Lawrence Livermore National Laboratory’s (LLNL) Big Ideas Lab podcast marks a new milestone with the release of its 50th episode. The latest episode, delving into high-performance computing for energy innovation, can be found alongside the entire series on the new LLNL podcast page. Since its debut in September 2024, the Big Ideas Lab has aimed to rethink how science…

Scientists from Lawrence Livermore National Laboratory are partnering with San Francisco Bay Area fusion energy startup Inertia Enterprises Inc. to advance fusion laser technology

LLNL partners with Inertia to develop fusion energy technology

Scientists from Lawrence Livermore National Laboratory (LLNL) are partnering with San Francisco Bay Area fusion energy startup Inertia Enterprises Inc. to advance fusion laser technology, as well as inertial fusion target manufacturing and designs. This collaboration is an expansive and integrated private sector-led partnership, unique in the history of LLNL and the DOE…

The latest Big Ideas Lab episode examines the how the Lawrence Livermore National Laboratory-managed High-Performance Computing for Energy Innovation program is translating advanced computing into measurable impact for U.S. industry and expanding what’s possible for American manufacturing, Listen on Apple or Spotify.

Big Ideas Lab explores how HPC for Energy Innovation advances U.S. industry

Some of the toughest challenges in American manufacturing are being solved without ever stepping onto a factory floor. Inside supercomputers, scientists are modeling systems too complex, costly or time-consuming to test in the real world. In the latest episode of the Big Ideas Lab podcast, Lawrence Livermore National Laboratory (LLNL) spotlights the High-Performance…

Big Ideas Lab energetic materials podcast graphic

Big Ideas Lab podcast explores energetic materials and the science behind explosive performance

In less than a millionth of a second, a high explosive can release its energy, generating pressures and temperatures that push materials to their limits. At Lawrence Livermore National Laboratory (LLNL), scientists in the Energetic Materials Center (EMC) study these extreme conditions using experiments, computation and specialized facilities. The latest episode of the Big…

A grain boundary defect with two phases (green and orange) in a tungsten crystal (blue) at 1848 degrees Kelvin. A new model gradually adds and removes atoms to calculate material structure and properties that were previously impossible to obtain. (Graphic: Dan Herchek)

Allowing atoms to come and go opens the door to better materials modeling

Most materials, especially metals and ceramics, are crystals. Their atoms are arranged in three-dimensional lattices that repeat the same exact pattern, over and over again. But there’s a well-known saying in materials science: “Crystals are like people. It is the defects that tend to make them interesting.” In a new study, published in Physical Review Letters, researchers…

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…

In a pioneering partnership to accelerate materials discovery with AI, researchers from Lawrence Livermore National Laboratory and Meta have created the world’s largest open dataset of atomistic polymer chemistry

LLNL, Meta co-develop groundbreaking polymer-chemistry dataset for training AI models

Polymers are fundamental to our daily lives, serving as the core components for a wide array of goods, including clothing, packaging, transportation infrastructure, construction materials and electronics. Advances in polymer science open pathways for recycling and upcycling waste materials into more valuable chemical feedstocks. They also can have an outsized environmental…