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HPC, Simulation, and Data Science

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…

LLNL biologist James Thissen loads DNA samples for sequencing in a pathogen-agnostic method to identify respiratory viruses. (Image: Randy Wong / LLNL)

Pathogen-agnostic testing reveals hidden respiratory threats in negative samples

The COVID-19 pandemic brought the term “Polymerase Chain Reaction testing” into the mainstream. The PCR method is a type of nucleic acid amplification test (NAAT) that detects a pathogen by finding and amplifying components of its genetic material, and it is widely used to detect SARS-CoV-2. But these types of tests have a weakness: you have to know exactly what pathogen…

Shaun Kerr and Dean Rusby have refined the MeV x-ray generation of NIF’s Advanced Radiographic Capability, leading to unprecedented imaging of dense materials. Photo by Blaise Douros.

Advanced Radiographic Capability achievements featured in Physics of Plasmas

Lawrence Livermore National Laboratory’s National Ignition Facility (NIF) is the hottest place on earth for the briefest of moments during an experiment. Now, it can be one of the brightest places thanks to the Advanced Radiographic Capability (ARC), NIF’s laser-within-the-laser. How this is possible and how it’s measured is detailed in the cover paper of the December 2025…

HPC4 Energy Innovation

High Performance Computing for Manufacturing program awards funding to three LLNL-industry collaborations

The U.S. Department of Energy (DOE) on Feb. 19 announced $4.8 million for 12 projects under the High Performance Computing for Manufacturing (HPC4Mfg) program, including three collaborations involving Lawrence Livermore National Laboratory (LLNL). The HPC4Mfg program is part of the broader High Performance Computing for Energy Innovation (HPC4EI) initiative, which LLNL…

Researchers presented proposals for future LDRD projects to an audience of peers and program leads.

Mission challenge ideas day turns bold concepts into space security capabilities

Exploring new frontiers of space requires innovative approaches to anticipate and identify paths for integrating space domain awareness capabilities. To deliver solutions for these emergent challenges, Lawrence Livermore National Laboratory’s (LLNL) Global Security Directorate recently hosted a “Space LDRD Ideas Day.” Researchers from a broad range of disciplines attended…

Overview of the key processes that are fundamental for understanding single-crystal battery materials.

Advanced simulation and modeling pave a path forward for single-crystal battery materials

The performance of rechargeable batteries is governed by processes deep within their components. A fundamental understanding of electrochemistry, structure–property–performance relationships and the effects of processing and operating conditions is essential for accelerating the development of next-generation battery technologies capable of powering electric vehicles,…

LLNL scientist Gianpaolo Carosi (right) discusses the inner workings of the Axion Dark Matter eXperiment. Expertise in this cavity technology (shown here plated in copper) is enhancing current efforts in quantum computing.

Finding resonance: How LLNL expertise is amplifying collaboration in quantum computing

In November, the Department of Energy Office of Science renewed the Superconducting Quantum Materials and Systems Center (SQMS), hosted by Fermi National Accelerator Laboratory, with $125 million over the next five years to accelerate breakthroughs in quantum information science. The investment continues to unite more than 300 experts from 43 partner institutions across…

National Ignition Facility (NIF) Director Gordon Brunton (right foreground) shows NNSA Administrator Brandon Williams a target used for inertial confinement fusion experiments at NIF on Feb. 9.

NNSA Administrator Williams visits LLNL to discuss stockpile modernization, AI and future deterrence

U.S. Department of Energy (DOE) Under Secretary for Nuclear Security and Administrator of the National Nuclear Security Administration (NNSA) Brandon Williams visited Lawrence Livermore National Laboratory (LLNL) Feb. 9 for briefings and tours focused on stockpile modernization, AI, supercomputing and the future of deterrence. During the visit, Williams met with LLNL…

LLNL scientists Colin Ponce and Carolyn Fisher initiated and led a cross-disciplinary team that developed a machine learning model to distinguish opioids from other chemicals.

Fentanyl or phony? Machine-learning algorithm learns to pick out opioid signatures

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: how do you identify a chemical you’ve never seen before? Researchers at Lawrence Livermore National Laboratory (LLNL) aim to answer that question with a machine-learning model that can distinguish opioids from other chemicals with an accuracy over 95% in a laboratory setting. The…

Novel crossed-beam energy transfer (CBET) technique for measuring plasma conditions.

When lasers cross: LLNL finds a brighter way to measure plasma

Measuring conditions in volatile clouds of superheated gases known as plasmas are central to pursuing greater scientific understanding of how stars, nuclear detonations and fusion energy work. For decades, scientists have relied on a technique called Thomson scattering, which uses a single laser beam to scatter from plasma waves as a way to measure critical information…

The moon’s orbit is shown in light gray. The spacecraft follows the colored path over the six-year simulation period.

Simulations and supercomputing calculate one million orbits in cislunar space

Satellites and spacecraft in the vast region between the earth and moon and just beyond — called cislunar space — are crucial for space exploration, scientific advancement and national security. But figuring out where exactly to put them into a stable orbit can be a huge, computationally expensive challenge. In an open-access database and with publicly available code,…