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Light moves through a fiber and stimulates the metal electrons in nanotip into collective oscillations called surface plasmons, assisting electrons to leave the tip. This simple electron nano-gun can be made more versatile via different forms of material composition and structuring. Credit: Ali Passian/ORNL, U.S. Dept. of Energy

Scientists at ORNL and the University of Nebraska have developed an easier way to generate electrons for nanoscale imaging and sensing, providing a useful new tool for material science, bioimaging and fundamental quantum research.

Kübra Yeter-Aydeniz

Kübra Yeter-Aydeniz, a postdoctoral researcher, was recently named the Turkish Women in Science group’s “Scientist of the Week.”

Starch granules

Scientists at the Department of Energy’s Oak Ridge National Laboratory have developed a new method to peer deep into the nanostructure of biomaterials without damaging the sample. This novel technique can confirm structural features in starch, a carbohydrate important in biofuel production.

quantum mechanics to advance a range of technologies including computing, fiber optics and network communication

Three researchers at Oak Ridge National Laboratory will lead or participate in collaborative research projects aimed at harnessing the power of quantum mechanics to advance a range of technologies including computing, fiber optics and network communication.

Quantum—Widening the net

Scientists at Oak Ridge National Laboratory studying quantum communications have discovered a more practical way to share secret messages among three parties, which could ultimately lead to better cybersecurity for the electric grid 

Quantum—Squeezed light cuts noise

Oak Ridge National Laboratory physicists studying quantum sensing, which could impact a wide range of potential applications from airport security scanning to gravitational wave measurements, have outlined in ACS Photonics the dramatic advances in the field.

Computing—Routing out the bugs

A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool