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Joon-Seok Kim Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.

Jiafu Mao, left, and Yaoping Wang discuss their analysis of urban and rural vegetation resilience across the United States in the EVEREST visualization lab at ORNL. Credit: Carlos Jones, ORNL/U.S. Dept. of Energy

Scientists at ORNL completed a study of how well vegetation survived extreme heat events in both urban and rural communities across the country in recent years. The analysis informs pathways for climate mitigation, including ways to reduce the effect of urban heat islands.

ORNL researcher Felicia Gilliland loads experiment samples into position for the newly installed UR5E robotic arm at the BIO-SANS instrument. The industrial-grade robot changes samples automatically, reducing the need for human assistance and improving sample throughput. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy

The BIO-SANS instrument, located at Oak Ridge National Laboratory’s High Flux Isotope Reactor, is the latest neutron scattering instrument to be retrofitted with state-of-the-art robotics and custom software. The sophisticated upgrade quadruples the number of samples the instrument can measure automatically and significantly reduces the need for human assistance.

Hood Whitson, chief executive officer of Element3, and Cynthia Jenks, associate laboratory director for the Physical Sciences Directorate, shake hands during the Element3 licensing event at ORNL on May 3, 2024. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A collection of seven technologies for lithium recovery developed by scientists from ORNL has been licensed to Element3, a Texas-based company focused on extracting lithium from wastewater produced by oil and gas production. 

A newly completed tunnel section will provide the turning and connecting point for the Spallation Neutron Source particle accelerator and the planned Second Target Station. Credit: ORNL, U.S. Dept. of Energy

The new section of tunnel will provide the turning and connecting point for the accelerator beamline between the existing particle accelerator at ORNL’s Spallation Neutron Source and the planned Second Target Station, or STS. When complete, the PPU project will increase accelerator power up to 2.8 megawatts from its current record-breaking 1.7 megawatts of beam power.

Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection

To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.

The Linac Coherent Light Source at DOE’s SLAC National Accelerator Laboratory in California reveals the structural dynamics of atoms and molecules through X-ray snapshots at ultrafast timescales. Pictured here is the LCLS-II tunnel. Credit: Jim Gensheimer/SLAC National Accelerator Laboratory

Plans to unite the capabilities of two cutting-edge technological facilities funded by the Department of Energy’s Office of Science promise to usher in a new era of dynamic structural biology. Through DOE’s Integrated Research Infrastructure, or IRI, initiative, the facilities will complement each other’s technologies in the pursuit of science despite being nearly 2,500 miles apart.

: Quantity of CCR and, if applicable, water held in the unit as of 2020/2021.

ORNL scientists contributed to a DOE technical study that found transitioning coal plants to nuclear power plants would create high-paying jobs at the converted plants and hundreds of new jobs locally. 

Study reveals flaw in long-accepted approximation used in water simulations

Computational scientists at ORNL have published a study that questions a long-accepted factor in simulating the molecular dynamics of water: the 2 femtosecond time step. According to the team’s findings, using anything greater than a 0.5 femtosecond time step can introduce errors in both the dynamics and thermodynamics when simulating water using a rigid-body description.

The AI for Energy Report provides a framework for using AI to accelerate decarbonization of the U.S. economy. Credit: Argonne National Laboratory

Groundbreaking report provides ambitious framework for accelerating clean energy deployment while minimizing risks and costs in the face of climate change.