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1191–1200 of 5256A century ago, scientists first detected the proton in the atomic nucleus. Yet, much about its contents remains a mystery. Scientists report a new theory for understanding what’s inside protons moving at the speed of light.
Some devastating diseases, like Alzheimer's and autoimmune conditions, are hard to diagnose correctly because doctors don’t yet know what genes or molecules to look for. But a new technique inspired by the Star Trek tricorder can spot disease without the clues, using infrared light and machine learning.
A process important to black holes and supernovas has for the first time been demonstrated in a laboratory at PPPL.
One effort toward better batteries for electric vehicles is hitting overdrive, thanks to new findings about silicon anodes.
Story tips: Carbon goes to space, cybersecurity put to the test, fusion’s power trip, cost-cutting controls and fungal infusion
Researchers at the Department of Energy’s SLAC National Accelerator Laboratory have uncovered a key step in the ionization of liquid water using the lab’s high-speed “electron camera,” MeV-UED. This reaction is of fundamental significance to a wide range of fields, including nuclear engineering, space travel, cancer treatment and environmental remediation. Their results were published in Science today.
Scientists used a nuclear dating technique to study the dynamics of the Floridan Aquifer. The findings show the promise of this emerging technique to help understand geological processes and to forecast the effects of climate change on coastal aquifers.
A team led by the Department of Energy’s Oak Ridge National Laboratory and the University of Michigan has discovered that certain bacteria can steal an essential compound from other microbes to break down methane and toxic methylmercury in the environment.
Accelerator scientists at the U.S. Department of Energy's Thomas Jefferson National Accelerator Facility have developed a model for a cheaper and easier preparation method for getting better performance from particle accelerators. Further, preliminary tests of the new model show that it may soon provide scientists the ability to predict the best material preparation method for specific performance goals. The results from this study were recently published in Applied Physics Letters.
Scientists identified structural and chemical defects that may be causing quantum information loss—an obstacle to practical quantum computation.
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