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PROJECTS
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ETHOS

The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms.

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GOLLNLP

Responding to a DOE grid optimization challenge, an LLNL-led team developed the mathematical, computational, and software components needed to solve problems of the real-world power grid.

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libROM

libROM is a library designed to facilitate Proper Orthogonal Decomposition (POD) based Reduced Order Modeling (ROM).

PEOPLE
Carolyn Albiston working at a computer (Credit: Department of Energy)

Carolyn Albiston

Carolyn Albiston is a research software engineer in NIF Shot Data Systems. Her career is a culmination of her wide range of varied interests and skills.

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Brian Gunney

From wind tunnels and cardiovascular electrodes to the futuristic world of exascale computing, Brian Gunney has been finding solutions for unsolvable problems.

Kevin McLoughlin

Kevin McLoughlin

Kevin McLoughlin has always been fascinated by the intersection of computing and biology. His LLNL career encompasses award-winning microbial detection technology, a COVID-19 antiviral drug design…

NEWS
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LLNL, Amazon partner on groundbreaking AI integration at the National Ignition Facility

LLNL and Amazon Web Services are partnering to leverage the power of AI to enhance operations at the National Ignition Facility.

To-scale snapshots from molecular dynamics simulations illustrating hot-spot formation during pore collapse. The images show pores with diameters of 60, 100, 200 and 300 nanometers, illustrating that pores larger than 20 nanometers generate hot spots with scale-invariant (independent of size) temperature distributions.

Simulating hot-spot formation in insensitive high explosives

Using the Sierra supercomputer, an LLNL team has made significant progress in understanding how microscopic hot spots form in insensitive high explosives based on TATB.

red and teal antibody structure

LLNL scientists use AI to optimize antibodies against mutations and accelerate pandemic preparedness

Researchers from LLNL, in collaboration with other leading institutions, have successfully used an AI-driven platform to preemptively optimize an antibody to neutralize a broad diversity of SARS-CoV-2 variants.