News archive

Browse the full collection of SLAC press releases and news features and stay up to date on the latest scientific advancements at the laboratory.

The future of experimental particle physics is exciting –  and energy intensive. SLAC physicists are thinking about how to make one proposal, the Cool Copper Collider, more sustainable.

The view down a copper tube.

The American Physical Society recognized the SLAC and Stanford physicist for decades of groundbreaking work studying the strange behavior of electrons at the interfaces between materials.

Photo - Harold Hwang

The Secretary celebrated LCLS-II first light with 600 SLAC staff and collaborators Oct. 26.

Secretary of Energy Jennifer M. Granholm and SLAC staff celebrate LCLS-II first light

LaserNetUS funding will allow scientists to explore fundamental plasma science and inertial fusion energy research and technology.

Matter in Extreme Conditions (MEC) Hutch 6, located in the LCLS Far Experimental Hall.
News Feature · Stanford School of Humanities and Sciences 

Stanford-SLAC study shows how modifying enzymes’ electric fields boosts their speed

A   swap of metals and a mutation ramp up the electric field strength at the active site of an enzyme, making it   works an astonishing 50 times faster than its unmodified analog.  

Illustration of an enzyme modified to work 50 times faster

Developing a new, light-activated method to produce the molecule opens doors for future biomedical applications.

An illustration of an X-ray spectroscopy experiment.

New research has implications for understanding Earth's evolution, interpreting unusual seismic signals and the study of exoplanets.

Illustration of earth with laser

The award recognizes Driver’s contribution toward attosecond X-ray capabilities.

A portrait of Taran Driver.

As the SLAC-Stanford institute celebrates its 20th anniversary, three Kavli Institute for Particle Astrophysics and Cosmology researchers share what they’re most excited for in years to come. 

A cluster of bright galaxies on a black background.

The research reveals the potential for machine learning in understanding the complex behavior of quantum materials.

machine learning

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