Katy Bradford: Cassette approach offers compelling construction solution
ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
Scientists at Oak Ridge National Laboratory have developed a solvent that results in a more environmentally friendly process to recover valuable materials from used lithium-ion batteries, supports a stable domestic supply chain for new batteries
Oak Ridge National Laboratory researchers have demonstrated that a new class of superalloys made of cobalt and nickel remains crack-free and defect-resistant in extreme heat, making them conducive for use in metal-based 3D printing applications.
A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.
Researchers at Oak Ridge National Laboratory developed self-healing elastomers that demonstrated unprecedented adhesion strength and the ability to adhere to many surfaces, which could broaden their potential use
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
Researchers at Oak Ridge National Laboratory were part of an international team that collected a treasure trove of data measuring precipitation, air particles, cloud patterns and the exchange of energy between the atmosphere and the sea ice.
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.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.