Researchers at large scientific facilities such as the ALS have applied a robust machine-learning technique to automatically optimize data gathering for a variety of experimental techniques. The work promises to enable experiments with large, complex datasets to be run more quickly, efficiently, and with minimal human intervention. Read more »
U.S. Energy Secretary Granholm Visits Berkeley Lab
In a visit to Berkeley Lab on August 20, Secretary Granholm and Congresswoman Barbara Lee met doctoral fellow Mikayla Barry at ALS Beamline 9.3.1. They also heard about extreme ultraviolet lithography and how protein crystallography enabled critical COVID research and Jennifer Doudna’s work on CRISPR. Read more »
Machine-Learning Team Receives 2021 Halbach Award
This year’s Halbach Award for Innovative Instrumentation at the ALS went to a team of accelerator physicists and computer scientists who were able to use machine-learning techniques to solve a problem that has plagued third-generation light sources for a long time: fluctuations in beam size due to the motion of insertion devices. Read more »
2021 Renner Award winner Andrea “Andi” Jones
At this year’s ALS User Meeting, Andrea “Andi” Jones, proposal coordinator in the User Services Office, was honored with the 2021 Tim Renner User Services Award. The ALS Users’ Executive Committee selected Jones for “her dedication and commitment in supporting the User Office that have allowed efficient proposal reviews and beamtime allocations during the pandemic.” Read more »
Sifting through Fragments for COVID-19 Treatments
COVID-19 vaccines are essential for preventing serious disease, but the identification of new drugs is still necessary for the treatment of patients who become sick as a result of SARS-CoV-2 infection. Here, scientists used computational docking and crystallography to screen large numbers of small molecules for potential use in drug compounds. Read more »
