A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.
Scientists at ORNL used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.
A study led by researchers at ORNL could uncover new ways to produce more powerful, longer-lasting batteries and memory devices.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.
Critical Materials Institute researchers at 91°µĶų and Arizona State University studied the mineral monazite, an important source of rare-earth elements, to enhance methods of recovering critical materials for energy, defense
A team of researchers from 91°µĶų, the University of Tennessee and Hong Kong Baptist University developed a new workflow that combines advances in automated chemical synthesis and machine-learning techniques.
Gang Seob āGSā Jung has known from the time he was in middle school that he was interested in science.
A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19ās viral pathogenesis ā a theory that was posited two years ago by a team of researchers at the Department of Energyās Oak Ridge Nati
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the labās Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing