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The AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE

A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules. 

Image of circuitry representing AI.

Research performed by a team, including scientists from ORNL and Argonne National Laboratory, has resulted in a Best Paper Award at the 19th IEEE International Conference on eScience.

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.

ORNL’s Climate Change Science Institute and Georgia Tech co-hosted a Southeast Decarbonization Workshop in November 2023. Credit: ORNL, U.S. Dept. of Energy

ORNL's Climate Change Science Institute and the Georgia Institute of Technology hosted a Southeast Decarbonization Workshop in November that drew scientists and representatives from government, industry, non-profits and other organizations to 

The Frontier exascale supercomputer at Oak Ridge National Laboratory. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL has joined a global consortium of scientists from federal laboratories, research institutes, academia and industry to address the challenges of building large-scale artificial intelligence systems and advancing trustworthy and reliable AI for

Scientists at Oak Ridge National Laboratory contributed to several chapters of the Fifth National Climate Assessment, providing expertise in complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling. Credit: ORNL, U.S. Dept. of Energy

Scientists at ORNL used their knowledge of complex ecosystem processes, energy systems, human dynamics, computational science and Earth-scale modeling to inform the nation’s latest National Climate Assessment, which draws attention to vulnerabilities and resilience opportunities in every region of the country.

Frontier’s exascale power enables the Energy, Exascale and Earth System Model-Multiscale Modeling Framework — or E3SM-MMF — project to run years’ worth of climate simulations at unprecedented speed and scale. Credit: Mark Taylor/Sandia National Laboratories, U.S. Dept. of Energy

The world’s first exascale supercomputer will help scientists peer into the future of global climate change and open a window into weather patterns that could affect the world a generation from now.

ORNL scientists developed a method that improves the accuracy of the CRISPR Cas9 gene editing tool used to modify microbes for renewable fuels and chemicals production. This research draws on the lab’s expertise in quantum biology, artificial intelligence and synthetic biology. Credit: Philip Gray/ORNL, U.S. Dept. of Energy

Scientists at ORNL used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.

red and green sphagnum moss

A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions. 

ORNL’s Fulvia Pilat and Karren More recently participated in the inaugural 2023 Nanotechnology Infrastructure Leaders Summit and Workshop at the White House, held Sept. 11–13. Credit: ORNL, U.S. Dept. of Energy

ORNL’s Fulvia Pilat and Karren More recently participated in the inaugural 2023 Nanotechnology Infrastructure Leaders Summit and Workshop at the White House.