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Lawrence Livermore National Laboratory scientists and engineers, including Aldair Gorgora (right) and Timothy Yee are addressing longstanding challenges in 3D-printed lattice structures by using machine learning and artificial intelligence to accelerate lattice designs optimized with unprecedented speed and efficiency.
// S&T Highlights

LLNL scientists and engineers look to incorporating machine learning (ML) and artificial intelligence to accelerate design of lattice structures.

Lawrence Livermore National Laboratory’s Zhi Liao has been elected as a senior member of SPIE, the international society for optics and photonics.
// Recognition

LLNL Zhi Liao has been elected as a senior member of SPIE, the international society for optics and photonics. 

LLNL’s Brent Stuart and Paul Armstrong have been named Optica senior members.
// Recognition

LLNL researchers have been named senior members of Optica in recognition for more than 10 years of professional experience in optics or an optics-related field.

LLNL scientist Alan Hidy used the Center for Accelerator Mass Spectrometry to study fossils from Greenland.
// S&T Highlights

LLNL researchers and collaborators examine Iceland's core to discover clear evidence of ice-free times.

LLNL researchers combined phase-field simulations (background), topological feature extraction (inside the magnifying glass, showing a pore-size analysis), property calculations and machine learning analysis to uncover the microstructure-property relationship in polymeric porous materials.
// S&T Highlights

LLNL scientists develop an efficient and comprehensive computational framework to decipher implications of porous microstructures and their properties.

Joe Ralph, co-lead author and inertial confinement fusion research physicist at Lawrence Livermore National Laboratory, discusses the critical role of implosion symmetry in achieving a burning plasma state at the National Ignition Facility.
// S&T Highlights

LLNL researchers retrospectively confirm that implosion asymmetry was a major aspect for fusion experiments.

Wenyu Sun, Aditya Prajapati and Jeremy Feaster in the lab where their research takes place.
// S&T Highlights

Using thin film nickel anodes, a team of LLNL scientists and collaborators figure out how to clean up chemical production.

Femtosecond X-ray diffraction of laser shocked aluminum-zirconium metals.
// S&T Highlights

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.
// S&T Highlights

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.
// S&T Highlights

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