Paul Kent, a computational nanoscience researcher in ORNL’s Computing and Computational Science Directorate, received the ORNL Director’s Award for Outstanding Individual Accomplishment in Science and Technology.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
A team led by Dan Jacobson of Oak Ridge National Laboratory used the Summit supercomputer at ORNL to analyze genes from cells in the lung fluid of nine COVID-19 patients compared with 40 control patients.
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
Oak Ridge National Laboratory researchers have built a novel microscope that provides a “chemical lens” for viewing biological systems including cell membranes and biofilms.
Ada Sedova’s journey to Oak Ridge National Laboratory has taken her on the path from pre-med studies in college to an accelerated graduate career in mathematics and biophysics and now to the intersection of computational science and biology
With the rise of the global pandemic, Omar Demerdash, a Liane B. Russell Distinguished Staff Fellow at ORNL since 2018, has become laser-focused on potential avenues to COVID-19 therapies.
In the fight against the COVID-19 pandemic, it’s a race against the clock not only to find a vaccine but also to supply healthcare workers with life-saving equipment such as face shields, masks and test kits.
Researchers at the Department of Energy’s Oak Ridge National Laboratory have used Summit, the world’s most powerful and smartest supercomputer, to identify 77 small-molecule drug compounds that might warrant further study in the fight against the SARS-CoV-2 coronavirus, which is responsible for the COVID-19 disease outbreak.
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.