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Combining fundamental chemistry with high-performance computing resources at ORNL, researchers demonstrate a more efficient method for recovering uranium from seawater, unveiling a prototype material that outperforms best-in-class uranium adsorbents. Credit: Alexander Ivanov/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Bio-inspired material targets oceans’ uranium stores for sustainable nuclear energy

Scientists have demonstrated a new bio-inspired material for an eco-friendly and cost-effective approach to recovering uranium from seawater.

ORNL collaborator Hsiu-Wen Wang led the neutron scattering experiments at the Spallation Neutron Source to probe complex electrolyte solutions that challenge nuclear waste processing at Hanford and other sites. Credit: Genevieve Martin/Oak Ridge National Laboratory, U.S. Dept. of Energy.

Focus on nuclear waste chemistry could help Hanford cleanup challenges

Researchers at the Department of Energy’s Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Washington State University teamed up to investigate the complex dynamics of low-water liquids that challenge nuclear waste processing at federal cleanup sites.

ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL

ORNL investigates complex uranium oxides with help from CADES resources

Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Modified deep-learning algorithms unveil features of shape-shifting proteins

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.

In ORNL’s Low Activation Materials Development and Analysis Laboratory, Field makes use of a transmission electron microscope to examine a sample made with a focused ion beam. He investigates the defects produced in a FeCrAl alloy bombarded with neutrons in HFIR. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy

Kevin Field: Developing radiation-tolerant materials for nuclear power systems

Kevin Field at the Department of Energy’s Oak Ridge National Laboratory synthesizes and scrutinizes materials for nuclear power systems that must perform safely and efficiently over decades of irradiation.

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Tree of life: Poplar studies yield human cancer insights

While studying the genes in poplar trees that control callus formation, scientists at Oak Ridge National Laboratory have uncovered genetic networks at the root of tumor formation in several human cancers.

Arjun Shankar

Arjun Shankar: Advancing national missions through smart data

The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades. Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued in...

Scientists will use ORNL’s computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy.

ORNL researchers turn to deep learning to solve science’s big data problem

A team of researchers from Oak Ridge National Laboratory has been awarded nearly $2 million over three years from the Department of Energy to explore the potential of machine learning in revolutionizing scientific data analysis. The Advances in Machine Learning to Improve Scient...

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3D printing yields advantages for US ITER engineers

ITER, the international fusion research facility now under construction in St. Paul-lez-Durance, France, has been called a puzzle of a million pieces. US ITER staff at Oak Ridge National Laboratory are using an affordable tool—desktop three-dimensional printing, also known as additive printing—to help them design and configure components more efficiently and affordably.