A potential drug target has been identified in a newly mapped protein of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). The structure was solved by a team including the University of Chicago (U of C), the U.S. Department of Energy's (DOE) Argonne National Laboratory, Northwestern University Feinberg School of Medicine and the University of California, Riverside School of Medicine (UCR).
Scientists at Argonne National Laboratory report fabricating and testing a superconducting nanowire device applicable to high-speed photon counting. This pivotal invention will allow nuclear physics experiments that were previously thought impossible.
Researchers have put a new technique based on machine learning to work uncovering the secrets of buried interfaces and edges in a material.
Laser-induced melting occurs nonuniformly in polycrystalline gold thin films--a finding that may be important for precision part micromachining.
ORNL's Story Tips: Antidote chasing, traffic control and automatic modeling, for March 2020
Researchers at Oak Ridge National Laboratory and the University of Tennessee achieved a rare look at the inner workings of polymer self-assembly at an oil-water interface to advance materials for neuromorphic computing and bio-inspired technologies.
New application of deep learning allows prediction of disruptions from raw, high-resolution data from fusion energy experiments.
Berkeley Lab scientists have made a surprising discovery that could help explain our risk for developing chronic diseases or cancers as we get older, and how our food decomposes over time.
Nuclear physicists have entered a new era for probing the strongest force in the universe at its very heart with a novel method of accessing the space between protons and neutrons in dense environments. The research, which was carried out at the Department of Energy's Thomas Jefferson National Accelerator Facility, has been published in the journal Nature and opens the door for more precision studies of the strongest part of the strong nuclear force and the structure of neutron stars.
A cheap technique could detect neutrinos in polar ice, eventually allowing researchers to expand the energy reach of IceCube without breaking the bank.
In a multi-institutional field campaign with NOAA and other laboratories, researchers at Argonne National Laboratory are working to better identify and forecast the occurrence of cold pool events.
Advanced design of the world's largest and most powerful stellarator demonstrates the ability to moderate heat loss from the plasma that fuels fusion reactions.
Particle beam could help map Earth's magnetic field to understand how space weather impacts the planet
Magnetic field lines that wrap around the Earth protect our planet from cosmic rays. Researchers at PPPL have now found that beams of fast-moving particles launched toward Earth from a satellite could help map the precise shape of the field.
Scientists at the U.S. Department of Energy's Ames Laboratory have discovered that applying vibrational motion in a periodic manner may be the key to preventing dissipations of the desired electron states that would make advanced quantum computing and spintronics possible.
Dinosaur blood vessels, giant viruses, and antibiotic-building enzymes
Scientists have taken an unprecedented look at proteins involved in endometrial cancer, commonly known as uterine cancer. The study offers insights about which patients will need aggressive treatment and which won't, and offers clues about why a common cancer treatment is not effective with some patients.
A team of scientists from the Department of Energy's SLAC National Accelerator Laboratory and Stanford University has gained insight into how electric fields affect the way energy from light drives molecular motion and transformation in a protein commonly used in biological imaging.
Researchers uncover a technique known as molecular layer etching which aid in building intricate 3D nanostructures for semiconductor devices and other microelectronics.
To better leverage cancer data for research, scientists at ORNL are developing an artificial intelligence (AI)-based natural language processing tool to improve information extraction from textual pathology reports. In a first for cancer pathology reports, the team developed a multitask convolutional neural network (CNN)--a deep learning model that learns to perform tasks, such as identifying key words in a body of text, by processing language as a two-dimensional numerical dataset.
Cryogenic electron microscopy can in principle make out individual atoms in a molecule, but distinguishing the crisp from the blurry parts of an image can be a challenge. A new mathematical method may help.
A detailed analysis of evolution of the trigger that sets off fast magnetic reconnection.
The researchers examined satellite imagery, air temperature data and phenology (plant life cycle) models for 85 large cities and their surrounding rural areas from 2001 through 2014 to better understand changes in tree leaf emergence, also called budburst, on a broad scale across the United States. The study can help scientists improve their modeling of the potential impacts of future warming.
Photosensitizers are molecules that absorb sunlight and pass that energy along to generate electricity or drive chemical reactions. A SLAC study looked at how an inexpensive photosensitizer, iron carbene, stores energy from sunlight, and why it's not better at its job.
Story Tips: Fusion squeeze, global image mapping, computing mental health and sodium batteries
Imagine being able to manufacture complex devices whenever you want and wherever you are. It would create unforeseen possibilities even in the most remote locations, such as building spare parts or new components on board a spacecraft. 3D printing, or additive manufacturing, could be a way of doing just that.