Topic: Materials Science

Research conducted on the Quartz supercomputer highlights findings made by scientists that reveal a missing aspect of the physics of hotspots in TATB and other explosives.

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StarSapphire is a collection of scientific data mining projects focusing on the analysis of data from scientific simulations, observations, and experiments.

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The SAMRAI library is the code base in CASC for exploring application, numerical, parallel computing, and software issues associated with structured adaptive mesh refinement.

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LLNL scientists have taken a step forward in the design of future materials with improved performance by analyzing its microstructure using artificial intelligence.

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Combining computer simulations with ultra-high-speed X-ray imaging, LLNL researchers have discovered a way to reduce defects in parts built through a laser-based metal 3D-printing process.

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An LLNL team developed ML tools that extract and structure information from the text and figures of nanomaterials articles using NLP, image analysis, computer vision, and visualization techniques.

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The HPC4EI Initiative seeks industry partners to work with DOE labs to solve key technical challenges in manufacturing and mobility.

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Livermore teams are applying innovative data analysis and interpretation techniques to advance fundamental science research.

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The HPC4EI program announced 9 public/private projects awarded more than $2 million from the DOE. This program is the umbrella entity for the HPC4Mfg and HPC4Mtls programs, headed out of LLNL.

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An LLNL team used LANL's Trinity supercomputer for a machine-learned surrogate representation of their laser-driven fusion implosion model.

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The HPC for Manufacturing Program (HPC4Mfg) announced the recipients of $1.2 million in federal funding for projects aimed at solving key manufacturing challenges through supercomputing.

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Highlights include debris an shrapnel modeling at NIF, scalable algorithms for complex engineering systems, magnetic fusion simulation, and data placement optimization on GPUs.

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Livermore researchers have developed an algorithm for the numerical solution of a phase-field model of microstructure evolution in polycrystalline materials. The system of equations includes a local order parameter, a quaternion representation of local orientation, and species composition. The approach is based on a finite volume discretization and an implicit time-stepping algorithm. Recent developments have been focused on modeling solidification in binary alloys, coupled with CALPHAD methodology.

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LLNL researchers are developing a truly scalable first-principles molecular dynamics algorithm with O(N) complexity and controllable accuracy, capable of simulating systems of sizes that were previously impossible with this degree of accuracy.

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LLNL’s version of Qbox, a first-principles molecular dynamics code, will let researchers accurately calculate bigger systems on supercomputers.

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A new algorithm for use with first-principles molecular dynamics codes enables the number of atoms simulated to be proportional to the number of processors available.

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