Polyphase wireless power transfer system achieves 270-kilowatt charge, s...
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 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 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.
As the second-leading cause of death in the United States, cancer is a public health crisis that afflicts nearly one in two people during their lifetime.
Scientists at have experimentally demonstrated a novel cryogenic, or low temperature, memory cell circuit design based on coupled arrays of Josephson junctions, a technology that may be faster and more energy efficient than existing memory devices.
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
As a computational hydrologist at Oak Ridge National Laboratory, Ethan Coon combines his talent for math with his love of coding to solve big science questions about water quality, water availability for energy production, climate change, and the
Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.