Science and Technology Highlights

LLNL scientists develop a machine-learning model to gain an atomic-level understanding of CO2 capture in amine-based sorbents.

LLNL scientists and a collaborator at University of Texas at Austin turn to simulations to explain the first-order response of confined water to applied electric fields.

LLNL researchers make advancements in understanding and resolving the long-standing "drive-deficit" problem in indirect-drive ICF experiments.

LLNL researchers develop a new technique for synthesizing molecular compounds with heavy elements.

LLNL Researchers discover a new mechanism that can boost the efficiency of hydrogen production through water splitting.

LLNL scientists report advancements in understanding plasma pressure profiles within flow-stabilized Z-pinch fusion, a candidate for achieving net gain fusion energy in a compact device.

An instrument designed and built by LLNL researchers is the highest-resolution gamma ray sensor that has ever flown in space.

LLNL mathematician and collaborators publish a recent paper introducing specialized solvers optimized for simulations running on graphics processing unit (GPU)–based supercomputers.

LLNL researchers and collaborators unlock new secrets about the interiors of super-Earth exoplanets, potentially revolutionizing our understanding of these distant worlds.

LLNL scientist and collaborators find the unique temperature trend patterns associated with natural climate variability for 1980–2022.