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HPC4Energy Innovation initiative launches new call for proposals
The Department of Energy (DOE) today launched the spring 2022 solicitation for the High Performance Computing for Energy Innovation (HPC4EI) initiative, seeking proposals from industry that address key energy and decarbonization-related challenges in domestic manufacturing. The latest HPC4EI funding opportunity is sponsored by the HPC4Manufacturing (HPC4Mfg) Program, one…
Laser-based ultrasound detects defect-producing features in metal 3D printing
Lawrence Livermore National Laboratory (LLNL) researchers have developed a new all-optical ultrasound technique capable of performing on-demand characterization of melt tracks and detecting formation of defects in a popular metal 3D printing process. In a paper published by Scientific Reports, Lab researchers propose a diagnostic using surface acoustic waves (SAW),…
NASA funds LLNL to demonstrate 'replicator' 3D printer to produce cartilage in space
The National Aeronautics and Space Administration (NASA) announced April 15 it has awarded Lawrence Livermore National Laboratory (LLNL) and a private company with funding to develop LLNL’s revolutionary volumetric additive manufacturing (VAM) 3D printing technology to produce artificial cartilage tissue in space. The award, one of eight projects selected by NASA’s In…
Livermore WiDS provides forum for women in data science
Lawrence Livermore National Laboratory (LLNL) celebrated the 2022 Global Women in Data Science (WiDS) conference on March 7 with its fifth annual regional event, featuring workshops, mentoring sessions and a discussion with LLNL Director Kim Budil, the first woman to hold that role. For the second straight year, the WiDS Livermore event was entirely virtual due to the…
Machine learning model finds COVID-19 risks for cancer patients
If a cancer patient tests positive for COVID-19, are they more likely to become hospitalized from the disease? That depends on certain risk factors, according to a new study by researchers at Lawrence Livermore National Laboratory (LLNL) and the University of California, San Francisco (UCSF), who looked to identify cancer-related risks for poor outcomes from COVID-19…
Register for materials-focused HPC4EI virtual event
Registration is open for the High Performance Computing for Energy Innovation (HPC4EI) initiative’s upcoming virtual event on April 8, a webinar highlighting the impact of high performance computing on material design and predicting material performance. Free to the public, the “Focus on Materials” event will feature talks by U.S. Department of Energy (DOE) national…
LLNL team models COVID-19 disease progression and identifies risk factors
A Lawrence Livermore National Laboratory (LLNL) team has developed a comprehensive dynamic model of COVID-19 disease progression in hospitalized patients, finding that risk factors for complications from the disease are dependent on the patient’s disease state. Using a machine learning algorithm on a dataset of electronic health records (EHRs) from more than 1,300…
Lawrence Livermore's Falgout wins SIAM Supercomputing Career Prize
The Society for Industrial and Applied Mathematics (SIAM) announced Lawrence Livermore National Laboratory computational mathematician Rob Falgout as the recipient of the 2022 SIAM Activity Group on Supercomputing Career Prize. Established in 2009, the career prize recognizes “broad and distinguished contributions to the field of algorithms research and development for…
Two LLNL scientists honored as 2022 Oppenheimer Science and Energy Leadership fellows
The Oppenheimer Science and Energy Leadership Program (OSELP) has selected Lawrence Livermore National Laboratory computer scientist Kathryn Mohror and materials scientist T. Yong Han as 2022 fellows. Established in 2017, OSELP is a distinguished fellowship program that brings together exceptional leaders to explore the complexities, challenges and opportunities facing the…
Unprecedented multiscale model of protein behavior linked to cancer-causing mutations
Lawrence Livermore National Laboratory (LLNL) researchers and a multi-institutional team of scientists have developed a highly detailed, machine learning-backed multiscale model revealing the importance of lipids to the signaling dynamics of RAS, a family of proteins whose mutations are linked to numerous cancers. Published by the Proceedings of the National Academy of…
LLNL establishes AI Innovation Incubator to advance artificial intelligence for applied science
Lawrence Livermore National Laboratory (LLNL) has established the AI Innovation Incubator (AI3), a collaborative hub aimed at uniting experts in artificial intelligence (AI) from LLNL, industry and academia to advance AI for large-scale scientific and commercial applications. LLNL has entered into a new memoranda of understanding with Google, IBM and NVIDIA, with plans to…
Newly funded HPC4Mfg project targets more energy-efficient steelmaking
A Lawrence Livermore National Laboratory (LLNL)-led collaboration targeted at using machine learning to reduce defects and carbon emissions in steelmaking is one of eight new projects receiving Department of Energy (DOE) funding through the High Performance Computing for Manufacturing (HPC4Mfg) Program. DOE’s Office of Energy Efficiency and Renewable Energy (EERE)…
Meet me in St. Louis (virtually or in person): First-ever hybrid Supercomputing conference sports strong Lab flavor
It was a Supercomputing conference like none other before it. For the first time ever, the 2021 International Conference for High Performance Computing, Networking, Storage and Analysis (SC21) went hybrid, with dozens of both in-person and virtual workshops, technical paper presentations, panels, tutorials and “birds of a feather” (BOF) sessions. Under the ongoing specter…
LLNL team wins SC21 Reproducibility Advancement Award
A suite developed by a Lawrence Livermore National Laboratory (LLNL) team to simplify evaluation of approximation techniques for scientific applications has won the first-ever Best Reproducibility Advancement Award at the 2021 International Conference for High Performance Computing, Networking, Storage and Analysis (SC21). Newly instituted by the conference, the award…
HPC for Energy Innovation issues new solicitation for clean energy projects
The U.S. Department of Energy's (DOE) High Performance Computing for Energy Innovation (HPC4EI) initiative, managed by Lawrence Livermore National Laboratory, is seeking proposals for projects that can leverage DOE supercomputing to advance clean energy technologies. The fall 2021 solicitation targets industry partners for collaborations with DOE national laboratories that…
U.S. Department of Energy to showcase national lab expertise at SC21
The scientific computing and networking leadership of the U.S. Department of Energy’s (DOE’s) national laboratories will be on display at SC21, the International Conference for High-Performance Computing, Networking, Storage and Analysis. The conference takes place Nov. 14-19 in St. Louis via a combination of on-site and online resources. The theme of this year’s…
LLNL-led team uses machine learning to derive black hole motion from gravitational waves
The announcement that the Laser Interferometer Gravitational-wave Observatory (LIGO) had detected gravitational waves during the merger of two black holes sent ripples throughout the scientific community in 2016. The earthshaking news not only confirmed one of Albert Einstein’s key predictions in his general theory of relativity, but also opened a door to a better…
LLNL researchers garner three awards among top 100 industrial inventions
Lawrence Livermore National Laboratory (LLNL) scientists and engineers have collected three awards among the top 100 industrial inventions worldwide. The trade journal R&D World Magazine announced the winners of the awards, often called the “Oscars of invention,” during a three-day virtual ceremony — Oct. 19-21 — and on the magazine’s website. With this year’s results,…
Tube-in-tube structure going strong
Similar to grass stems, Lawrence Livermore National Laboratory (LLNL) scientists have created nanostrut-connected tube-in-tubes that enable stronger low-density structural materials. Porous materials with engineered stretching-dominated lattice designs, which offer attractive mechanical properties with ultra-light weight and large surface area for wide-ranging applications…
LLNL joins Human Vaccines Project to accelerate vaccine development and understanding of immune response
Lawrence Livermore National Laboratory (LLNL) has joined the international Human Vaccines Project (HVP), bringing Lab expertise and computing resources to the consortium to aid development of a universal coronavirus vaccine and improve understanding of immune response. The HVP is a nonprofit, public-private partnership with a mission to decode the human immune system and…
