![closeup of molecular simulation](/sites/default/files/styles/front_page_card/public/first-principles-llnl-project-card.png?itok=hVPhZQXs)
First-Principles Molecular Dynamics
This scalable first-principles MD algorithm with O(N) complexity and controllable accuracy is capable of simulating systems that were previously impossible with such accuracy.
![symmetrical geometric shape on a graph](/sites/default/files/styles/front_page_card/public/high-order-llnl-project-card.png?itok=xTEfE-zt)
High-Order Finite Volume Methods
High-resolution finite volume methods are being developed for solving problems in complex phase space geometries, motivated by kinetic models of fusion plasmas.
![compute the electronic structure of atoms, molecules, solids, and liquids within the Density Functional Theory (DFT) formalism](/sites/default/files/styles/front_page_card/public/qbox-llnl-project-card.png?itok=C-tNeIQv)
Qbox
LLNL’s version of Qbox, a first-principles molecular dynamics code, will let researchers accurately calculate bigger systems on supercomputers.
![map of lower 48 states covered with grid points, plus an inset of Frontier](/sites/default/files/styles/front_page_card/public/2023-08/HiOp-comp-leaderboard_0.png?itok=WHcl4KaT)
Team reaches milestone in power grid optimization on world’s first exascale supercomputer
As part of the Exascale Computing Project’s ExaSGD project, a team including LLNL researchers ran HiOp, an open source optimization solver, on 9,000 nodes of Oak Ridge National Laboratory’s Frontier exascale supercomputer.
![students and mentors strike casual poses in the UCLCC meeting room](/sites/default/files/styles/front_page_card/public/2023-08/DSC-2023-comp-news.png?itok=ynVypMBI)
Data Science Challenge tackles ML-assisted heart modeling
The event brought together 35 University of California students—ranging from undergraduates to graduate-level students from a diversity of majors—to work in groups to solve four key tasks, using actual electrocardiogram data to predict heart health.
![Real scanning electron microscope image of TATB powder, alongside a hypothetical scanning electron microscope image of TATB powder made to optimize its peak stress. The hypothetical image is made of smaller grains.](/sites/default/files/styles/front_page_card/public/2023-07/XAI_TATB_432x285.jpg?itok=XMmChs4_)
Explainable artificial intelligence can enhance scientific workflows
Using explainable artificial intelligence techniques can help increase the reach of machine learning applications in materials science, making the process of designing new materials much more efficient.