News

Photo of glowing, pink diamond-shaped figure. This is illuminated with light, encircled with a wreath of around 70 blue tube-like shapes.
Promethium’s secrets exposed
Male student wearing clear safety goggles peering through a 3D-printed item.
tnAchieves students learn about lab careers
Photo of a man in a black jacket suit with a blue shirt crossing his arms outside. He is smiling.
Wagner receives ASME Medal

Filter News

Area of Research

News Type

Date

News Topics

Media Contacts

Connect with ORNL

Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

ORNL neural network study harnesses made-to-order design to pair properties to materials

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

ORNL multimodal study sheds new light on promising photovoltaic material

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.

Mars Rover 2020

Secretary’s Honor Awards recognize dozens of ORNL employees

More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.