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Environmental Sciences Division Director Eric Pierce presented the organization’s 2023 Distinguished Achievement awards at a December 7 all-hands meeting. From left: Megan Johnson, Michael Jones, Maria Colberg, Rachel Pilla, Eric Pierce, Rocio Uria-Martinez, Gbadebo Oladosu and Paul Leiby. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL Environmental Sciences Division Director Eric Pierce presented the division’s 2023 Distinguished Achievement Awards at the organization’s December all-hands meeting.

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.

NEXTGENCOMPUTING students learned fundamental computing concepts through an HPC Crash Course before applying those concepts to an AI-based team project. From left to right, front row: Saahithi Gorti, Hannah Bao, Pragya Nidhi. Middle row: Kaiya Barnes, Brianna Andrews, Aninditha Nair, Olivia Heng, Disha Maheshwari, Emma Bohse, Sachi Griffin, Kevin Peng. Back row, Kieran Marci, Ronak Patel, Michael Batchelor, Matthew Tan, Richard Sances, Dhanvi Bharadwaj, Prabhash G C. Credit: ORNL

This summer, ORNL welcomed more than 500 students to campus through the lab’s range of internship programs, which are offered in areas such as biology, national security and computing.

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.

2023 Battelle Distinguished Inventors

Four scientists affiliated with ORNL were named Battelle Distinguished Inventors during the lab’s annual Innovation Awards on Dec. 1 in recognition of being granted 14 or more United States patents.

Hilda Klasky

Hilda Klasky, a research scientist in ORNL’s Computing and Computational Sciences Directorate, has been named a fellow of the American Medical Informatics Association.

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.