An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.
At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.
Since the 1930s, scientists have been using particle accelerators to gain insights into the structure of matter and the laws of physics that govern our world.
A multi-institutional team, led by a group of investigators at Oak Ridge National Laboratory, has been studying various SARS-CoV-2 protein targets, including the virus’s main protease. The feat has earned the team a finalist nomination for the Association of Computing Machinery, or ACM, Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research.
The Department of Energy has selected Oak Ridge National Laboratory to lead a collaboration charged with developing quantum technologies that will usher in a new era of innovation.
From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.
With Tennessee schools online for the rest of the school year, researchers at ORNL are making remote learning more engaging by “Zooming” into virtual classrooms to tell students about their science and their work at a national laboratory.
In the early 2000s, high-performance computing experts repurposed GPUs — common video game console components used to speed up image rendering and other time-consuming tasks
In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.
We have a data problem. Humanity is now generating more data than it can handle; more sensors, smartphones, and devices of all types are coming online every day and contributing to the ever-growing global dataset.