Feature Articles

On a clear April day in 2006, a team of engineers and scientists erupted with excitement from the control room of the Spallation Neutron Source (SNS), a newly built user facility at Oak Ridge National Laboratory. A pulse of protons — racing at nearly the speed of light — shot from the accelerator and struck liquid mercury at the facility’s first target station, freeing tens of millions of neutrons. That moment launched a new era of discovery science that continues to shape technologies we use every day, from spacecraft to smartphones. As the challenges we currently face require a historic national effort, comparable in urgency and ambition to the Manhattan Project, ORNL once again stands at the ready to answer the nation’s need for AI‑accelerated innovation and discovery.   

The Versatile Neutron Imaging Instrument (VENUS) at Oak Ridge National Laboratory’s Spallation Neutron Source has officially opened to users, demonstrating major advances in fast, high‑precision 3D neutron imaging. Early experiments led by Stuart Miller and Dayakar Penumadu validated a new dual‑camera system and transparent scintillator technology that boosts detection efficiency by 10–100× and sharply improves spatial resolution. Their results mark a milestone for neutron imaging, enabling clearer insights into materials—from composites to complex engineered systems—and underscoring VENUS’s role as a next‑generation tool for researchers across science and engineering.

For Adam Piotr Pikul of the Polish Academy of Sciences, there is always more to understand about the basic physics of uranium atoms. That’s why Pikul, a professor at the Institute of Low Temperature and Structure Research in Wrocław, is studying actinide quantum materials at the Idaho National Laboratory (INL) on a Fulbright Senior Award. Actinides are a group of 15 radioactive elements, including uranium.

At Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences, Yongtao Liu is building AI-driven “closed-loop” nanomaterials experiments that can plan measurements, interpret results in real time and choose the next step — accelerating discovery without removing human judgment. His focus is not just speed but trustworthy autonomy: systems must be interpretable, resilient to instrument artifacts and designed to avoid “false novelty,” where noise masquerades as new physics. Drawing on work such as novelty detection in conductive AFM studies of halide perovskites — linking local microstructure to unusual hysteresis behavior — Liu emphasizes that autonomous labs also demand better methods to validate and understand the massive data they produce. He is developing practical tools like AEcroscopy to standardize automated microscopy workflows and a Gated Active Learning Framework to prevent models from confidently learning from out-of-assumption data, while also pushing cross-facility autonomy that links fast measurements with slower synthesis. Ultimately, Liu envisions AI that helps scientists reason and explore vast experimental spaces — freeing researchers from repetitive tasks so they can focus on asking sharper questions.

Researchers at the Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) will share their discoveries and innovations at DOE’s Advanced Research Projects Agency-Energy (ARPA-E) Energy Innovation Summit in San Diego, California, April 7-9. ARPA-E funds high-risk, high-impact energy technologies that can be quickly and meaningfully advanced to catalyze bleeding-edge energy research.

Labeled glass containers full of liquids stirred by spinning magnets are connected to humming machines with neatly organized tubes. Here in this lab space at the Idaho National Laboratory, scientists are pioneering ways to extract critical materials from recycled waste products.