Science and Technology Highlights

Schematic of semiconductor switch
// S&T Highlights
Livermore engineers have designed a new kind of laser-driven semiconductor switch that can achieve higher speeds at higher voltages than existing photoconductive devices.
Artist conception of abstract diamond ring shape within chamber
// S&T Highlights
Recent materials findings combined with a specialized additive manufacturing technology move consumer 3D printing-on-demand one step closer to reality.
Composite false-color image of the Andromeda galaxy
// S&T Highlights
Thousands of images of Earth and space have been taken by a compact space imaging payload developed by Livermore researchers and Tyvak Nano-Satellite Systems.
Abstract data graphs
// S&T Highlights
Livermore researchers build confidence in materials modeling using a statistics-based approach for assessing sources of uncertainty in material strength research.
Collage of images of four high-energy density research facilities
// S&T Highlights
A recent paper examines the various experimental techniques and key findings of material states under extreme high energy density (HED) conditions based on work conducted at Livermore and other facilities around the world.
Gold bar image superimposed on NIF test chamber and Z machine
// S&T Highlights
Shockless compression experiments establish new pressure scales.
The Z line VISAR final optics assembly
// S&T Highlights
Livermore and Sandia national laboratories continue their longstanding collaboration on high-energy-density research.
Silhouettes of two first responders against orange sky and buildings
// S&T Highlights
Meta and targeted genomic analysis and machine learning predict wound healing outcomes and lay the groundwork to potentially save lives.
Viruses with superimposed images of people in labs
// S&T Highlights
To help the United States fight the COVID-19 pandemic, Lawrence Livermore did what it does best: quickly bring together interdisciplinary teams and diverse technologies to address urgent national challenges.
Chemical formulae and structures
// S&T Highlights
A research team has created machine learning models that can predict molecules’ crystalline properties from their chemical structures alone, such as molecular density.