Feature Articles

Every time scientists study a new material, they must wade through an ocean of data. Today, a whole ecosystem of scientific tools creates a wild variety of data to be explored. This exploration will now get a lot easier thanks to scientists at the National Synchrotron Light Source II. Their freshly rolled-out software tool—called Tiled—allows researchers to see, slice, and study their data more conveniently than ever before.

At Argonne National Laboratory, staff scientist Jinlong Zhang performs R&D on the CERN ATLAS and DAQ systems. These systems select and collect data from the billion-plus proton-proton collisions per second in particle physics experiments.

Scientists have devised a way to engineer yeast to produce sustainable, eco-friendly commodity chemicals using computing power as a guide.

Gina Tourassi is the director of the National Center for Computational Sciences, leading world-class computing infrastructure programs and projects. This is one in a series of profiles on the directors of the SC-stewarded user facilities.

Jefferson Lab has appointed David J. Dean as its Deputy Director for Science. This key leadership position oversees the science and technology aspects of the laboratory’s mission. Dean will take on the responsibilities of this role in January 2022.

With multiple clinical trials under way, it’s likely both a drug using Ac-225 and increased demand for the radioisotope are in the near future — and the U.S. Department of Energy wants to be ready. Since 2015, DOE’s Isotope Program has sponsored the Tri-Lab Effort to Provide Accelerator-produced Ac-225 for Radiotherapy. Thorium-232 targets are irradiated in proton accelerators at Los Alamos and Brookhaven national laboratories, then sent to ORNL for processing in hot cells dedicated to alpha radiation. The purpose: producing bigger batches, faster. In June, ORNL processed the largest batch of Ac-225 ever put in inventory.

A team of collaborators from the U.S. Department of Energy’s Oak Ridge National Laboratory, Google Inc., Snowflake Inc. and Ververica GmbH has tested a computing concept that could help speed up real-time processing of data that stream on mobile and other electronic devices.

A team has used machine learning descriptions of interatomic interactions on the 200-petaflop Summit supercomputer at ORNL to model more than a billion carbon atoms at quantum accuracy and observe how diamonds behave under some of the most extreme pressures and temperatures imaginable.