An advance in a topological insulator material — whose interior behaves like an electrical insulator but whose surface behaves like a conductor — could revolutionize the fields of next-generation electronics and quantum computing, according to scientists at ORNL.
To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
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.
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.
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
The type of vehicle that will carry people to the Red Planet is shaping up to be “like a two-story house you’re trying to land on another planet.
Using the Titan supercomputer at Oak Ridge National Laboratory, a team of astrophysicists created a set of galactic wind simulations of the highest resolution ever performed. The simulations will allow researchers to gather and interpret more accurate, detailed data that elucidates how galactic winds affect the formation and evolution of galaxies.
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.