Science and Technology Highlights

In a milestone for supercomputing-aided drug design, Lawrence Livermore National Laboratory and BridgeBio Oncology Therapeutics today announced clinical trials have begun for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer. The drug discovery work was powered by LLNL supercomputers Ruby (shown), Quartz and Lassen.
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LLNL and BridgeBio announce the commencement of clinical trials for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer.

A team of scientists from Lawrence Berkeley and Lawrence Livermore national laboratories have determined the 71Ge half-life with a set of carefully performed measurements. The research appears in the journal Physical Review C.
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Lawrence Berkeley and Lawrence Livermore national laboratories determine the 71Ge half-life with a set of carefully performed measurements.

Wei Li and Xavier Mayali used the NanoSims to measure nitrogen incorporation and exchange at single cell resolution of harmful algal blooms from Lake Erie.
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LLNL scientists and collaborators investigate several Microcystis cultures collected from algal blooms in Lake Erie.

Left to right: LLNL researchers Jimmy Shen, Lars Voss and Joel Varley have software that can efficiently and effectively automate and analyze point defects in materials.
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LLNL researchers create software that can efficiently and effectively automate and analyze point defects in crystalline materials. 

An artistic impression of WASP-107b.
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A LLNL scientist and international collaborators have characterized the atmosphere of the exoplanet, WASP-107b, using a transmission spectroscopy technique.

Elizabeth Grace (LLNL, right) and Filip Grepl (ELI Beamlines, left) assemble the PROBIES diagnostic, one of many instruments that fed data to the machine-learning optimizer algorithm.
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LLNL international scientists and collaborators collaborate on an experiment to optimize a high-intensity, high-repetition-rate laser using machine learning.  

Graphic of Earth.
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The American Geophysical Union showcases a paper by LLNL scientists and collaborators on global climate models.

Unveiled at the International Supercomputing Conference in Germany, the June 2024 Top500 lists three systems with identical components — one computing rack each from El Capitan’s “Early Delivery System” (EDS), LLNL’s newest unclassified supercomputer RZAdams and its unclassified “sister” system Tuolumne. All three registered 19.65 petaFLOPs on the High Performance Linpack (HPL) benchmark, ranking them among the world’s 50 fastest.
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Three new systems currently or soon-to-be sited at LLNL debuted on the latest Top500 list of most powerful supercomputers in the world.

Project DarkStar leverages artificial intelligence and machine learning to optimize shaped charges—explosive devices used to manipulate metals.
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LLNL researchers couple computing capabilities and manufacturing methods to rapidly develop and experimentally validate modifications to a shaped charge.

Artwork illustrating a new study combining atomistic simulations, machine learning potential, and data-driven methods to study the chemical speciation of amorphous carbon nitride using X-ray absorption near-edge structure (XANES) spectra.
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LLNL scientists develop a new approach that can rapidly predict the structure and chemical composition of heterogeneous materials.