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A new method for analyzing climate models brings together information from various lines of evidence to represent Earth’s climate sensitivity. Credit: Jason Smith/ORNL, U.S. Dept. of Energy

Researchers from institutions including ORNL have created a new method for statistically analyzing climate models that projects future conditions with more fidelity.

Sam Hollifield displays a prototype of the Secure Hijack, Intrusion and Exploit Layered Detector, or SHIELD, the device monitoring the cybersecurity of the semi-truck. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

As vehicles gain technological capabilities, car manufacturers are using an increasing number of computers and sensors to improve situational awareness and enhance the driving experience.

The OpeN-AM experimental platform, installed at the VULCAN instrument at ORNL’s Spallation Neutron Source, features a robotic arm that prints layers of molten metal to create complex shapes. This allows scientists to study 3D printed welds microscopically. Credit: Jill Hemman, ORNL/U.S. Dept. of Energy

Using neutrons to see the additive manufacturing process at the atomic level, scientists have shown that they can measure strain in a material as it evolves and track how atoms move in response to stress.

ORNL’s David Sholl is director of the new DOE Energy Earthshot Non-Equilibrium Energy Transfer for Efficient Reactions center to help decarbonize the industrial chemical industry. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

ORNL has been selected to lead an Energy Earthshot Research Center, or EERC, focused on developing chemical processes that use sustainable methods instead of burning fossil fuels to radically reduce industrial greenhouse gas emissions to stem climate change and limit the crisis of a rapidly warming planet.
 

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of its Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making. Credit: Rachel Green/ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.

Researchers used the open-source Community Earth System Model to simulate the effects that extreme climatic conditions have on processes like land carbon storage. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Researchers from Oak Ridge National Laboratory and Northeastern University modeled how extreme conditions in a changing climate affect the land’s ability to absorb atmospheric carbon — a key process for mitigating human-caused emissions. They found that 88% of Earth’s regions could become carbon emitters by the end of the 21st century. 

Yarom Polsky studio portrait

Yarom Polsky, director of the Manufacturing Science Division, or MSD, at the Department of Energy’s Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Mechanical Engineers, or ASME.

TIP graphic

Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.

Radu Custelcean's sustainable chemistry for capturing carbon dioxide from air has been licensed to Holocene. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

An innovative and sustainable chemistry developed at ORNL for capturing carbon dioxide has been licensed to Holocene, a Knoxville-based startup focused on designing and building plants that remove carbon dioxide

An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL

Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.