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The illustrations show how the correlation between lattice distortion and proton binding energy in a material affects proton conduction in different environments. Mitigating this interaction could help researchers improve the ionic conductivity of solid materials.

Ionic conduction involves the movement of ions from one location to another inside a material. The ions travel through point defects, which are irregularities in the otherwise consistent arrangement of atoms known as the crystal lattice. This sometimes sluggish process can limit the performance and efficiency of fuel cells, batteries, and other energy storage technologies.

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.

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.

ORNL will use state-of-the-art R&D tools at the Battery Manufacturing Facility to develop new methods for separating and reclaiming valuable materials from spent EV batteries.

The use of lithium-ion batteries has surged in recent years, starting with electronics and expanding into many applications, including the growing electric and hybrid vehicle industry. But the technologies to optimize recycling of these batteries have not kept pace.

ORNL cybersecurity researchers Jared Smith (left) and Elliot Greenlee (right) participate in a demonstration day event to showcase how Akatosh, a new security analysis tool, quickly sorts through data to identify potential threats.

As technology continues to evolve, cybersecurity threats do as well. To better safeguard digital information, a team of researchers at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) has developed Akatosh, a security analysis tool that works in conjunctio...

Schematic drawing of the boron nitride cell. Credit: University of Illinois at Chicago.

A new microscopy technique developed at the University of Illinois at Chicago allows researchers to visualize liquids at the nanoscale level — about 10 times more resolution than with traditional transmission electron microscopy — for the first time. By trapping minute amounts of...

Rose Ruther and Jagjit Nanda have been collaborating to develop a membrane for a low-cost redox flow battery for grid-scale energy storage.

Oak Ridge National Laboratory scientists have developed a crucial component for a new kind of low-cost stationary battery system utilizing common materials and designed for grid-scale electricity storage. Large, economical electricity storage systems can benefit the nation’s grid ...

Ryan Kerekes is leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory. Photos by Genevieve Martin, ORNL.

As leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory, Kerekes heads an accelerated lab-directed research program to build virtual models of critical infrastructure systems like the power grid that can be used to develop ways to detect and repel cyber-intrusion and to make the network resilient when disruption occurs.

ORNL Director Thomas Zacharia (center, seated) visited Robertsville Middle School to present a check in support of the school’s CubeSat efforts.

Last November a team of students and educators from Robertsville Middle School in Oak Ridge and scientists from Oak Ridge National Laboratory submitted a proposal to NASA for their Cube Satellite Launch Initiative in hopes of sending a student-designed nanosatellite named RamSat into...

Arjun Shankar

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.

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...