Science and Technology Highlights

Femtosecond X-ray diffraction of laser shocked aluminum-zirconium metals.
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It’s getting hot in here: lasers deliver powerful shocking punch

LLNL scientists use ultra-fast X-ray probes to track the thermal response of aluminum and zirconium on shock release from experiments. 

The image looks down the barrel of a metallic carbon nanotubes embedded in an array of closely-packed carbon nanotubes with different electronic properties.
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Molecules get a boost from metallic carbon nanotubes

LLNL scientists find that pure metallic carbon nanotubes are best at transporting molecules.

A machine-learning potential derived from first-principles calculations unveils the intricate mechanisms of CO2 capture in liquid ammonia.
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Probing carbon capture, atom-by-atom

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

Water gets weird under nano-confinement. This image shows an exotic phase of water trapped in tiny spaces, where it interacts surprisingly with electric fields.
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Confined water gets electric

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.

In inertial confinement fusion experiments, lasers at Lawrence Livermore National Laboratory’s National Ignition Facility focus on a tiny fuel capsule suspended inside a cylindrical x-ray oven called a hohlraum.
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LLNL researchers uncover key to resolving long-standing ICF hohlraum drive defi…

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

Despite the historical consensus, trivalent actinides and lanthanides exhibit distinct chemistries. By using polyoxometalate chelators, LLNL scientists provide crystallographic and spectroscopic evidence that americium and curium yield a variety of compounds that their lanthanide counterparts are unable to form.
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Unravelling the chemistry of heavy elements

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

Machine learning potential derived from first-principles calculations reveals that confinement in TiO2 nanopores enhances proton transfer by reducing activation energy, highlighting the interplay between confinement, surface chemistry and topology in accelerating water reactivity.
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Nano-confinement may be key to improving hydrogen production

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

Lawrence Livermore National Laboratory scientists have collaborated with Zap Energy in Everett, Washington, to measured plasma conditions on Z-pinch fusion experiments on the private-sector fusion company’s Fusion Z-pinch Experiment (FuZE) device.
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Advancements in Z-pinch fusion: New insights from plasma pressure profiles

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.

Shown is part of the Psyche Gamma Ray and Neutron Spectrometer (GRNS) and NASA Jet Propulsion Laboratory (JPL) instrument and operation teams at the JPL in Pasadena. Right to left are: Morgan Burks (Lawrence Livermore National Laboratory); Patrick Peplowski, John Goldsten and David Lawrence (all from Johns Hopkins Applied Physics Laboratory); and Maria De Soria Santacruz Pich and Nora Alonge (NASA JPL).
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LLNL gamma-ray sensor has the best resolution

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

Developed by LLNL and Portland State University researchers, innovative matrix-free solvers offer performance gains for complex multiphysics simulations.
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Matrix unloaded: Graphics processor-boosted solvers for diffusion physics

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