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Image of Giuseppe Barca looking at two computer monitors, representing the team using Frontier to perform the first quantum chemistry calculations to exceed an exaflop.

Researchers led by the University of Melbourne, Australia, have been nominated for the Association for Computing Machinery’s 2024 Gordon Bell Prize in supercomputing for conducting a quantum molecular dynamics simulation 1,000 times greater in size and speed than any previous simulation of its kind.

A large group of attendees are pictured outside of Jackson Center in Huntsville, Alabama

ORNL and NASA co-hosted the fourth iteration of this invitation-only event, which brings together geospatial, computational, data and engineering experts around a theme. This year’s gathering focused on how artificial intelligence foundation models can enable geospatial digital twins. 

Pictured is a 3D printer that creates objects using electron beam melting, looks like a glowing orb.

Researchers have developed and 3D printed the lightest crack-free alloy capable of operating without melting at temperatures above 2,400 degrees Fahrenheit, which could enable additively manufactured turbine blades to better handle extreme temperatures, reducing the carbon footprint of gas turbine engines such as those used in airplanes.

An image depicting the process of parallel quantum-enhanced sensing

Researchers from ORNL have taken a major step forward in using quantum mechanics to enhance sensing devices, a new advancement that could be used in a wide range of areas, including materials characterization, improved imaging and biological and medical applications.

Larry York is sitting in front of a computer screen showing an image of plant phenotyping

The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.

A graphic representation of AI

The Department of Energy announced a $67 million investment in several AI projects from institutions in both government and academia as part of its AI for Science initiative. Six ORNL-led (or co-led) projects received funding.

This is a simulated image of the project to build a new network that artificial intelligence and machine learning to steer experiments and analyze data faster and more accurately. will enable

To bridge the gap between experimental facilities and supercomputers, experts from SLAC National Accelerator Laboratory are teaming up with other DOE national laboratories to build a new data streaming pipeline. The pipeline will allow researchers to send their data to the nation’s leading computing centers for analysis in real time even as their experiments are taking place. 

Team working on in green composites design for their fully-recyclable wind turbine blade tip incorporating low-cost carbon fiber

ORNL researchers were honored with a prestigious ACE Award for Composites Excellence by the American Composites Manufacturers Association. The team won the “innovation in green composites design” prize for creating a fully recyclable, lightweight wind turbine blade tip that incorporates low-cost carbon fiber and conductive coating for enhanced protection against lightning strikes. 

ORNL’s Prasanna Balaprakash joined leading computing experts to provide insight into how supercomputing, AI and meteorology can work together to advance weather and climate research as part of a panel for the United States Senate.

Prasanna Balprakash, director of AI programs for ORNL, discussed advancing climate and weather research through high performance computing and artificial intelligence as part of a September 18 panel for the United States Senate. 

MedUSE wire-arc

Researchers at ORNL are using advanced manufacturing techniques to revitalize the domestic production of very large metal parts that weigh at least 10,000 pounds each and are necessary for a variety of industries, including clean energy.