New machine learning tool diagnoses electron beams in an efficient, non-invasive way

For the past few years, researchers at the Department of Energy’s SLAC National Accelerator Laboratory have been developing “virtual diagnostics” that use machine learning to obtain crucial information about electron beam quality in an efficient, non-invasive way. Now, a new virtual diagnostic approach incorporates additional information about the beam that allows the method to work in situations where conventional diagnostics have failed.

Intense Light Pulses Bounce on a Crystalline Bed without Rumpling the Atomic Blanket

Scientists developed a new technique that uses intense X-ray pulses to measure how atoms move in a sheet of material one molecule thick. Scientists showed that movement of the atoms in a tungsten-selenium “blanket” layer caused the layer to stretch but not wrinkle. The research can help produce materials with new optical and electronic properties.