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Dave Weston studies how microorganisms influence plant health and stress tolerance, using the Advanced Plant Phenotyping Laboratory to accelerate research on plant-microbe interactions and develop resilient crops for advanced fuels, chemicals and materials.

ORNL took part in the “1,000 Scientists AI Jam Session,” a first-of-its-kind virtual event that brought together leading scientists from nine national laboratories to test generative artificial intelligence models for their functionality in scientific research.

During his first visit to 91, Energy Secretary Chris Wright compared the urgency of the Lab’s World War II beginnings to today’s global race to lead in artificial intelligence, calling for a “Manhattan Project 2.”

Working at nanoscale dimensions, billionths of a meter in size, a team of scientists led by ORNL revealed a new way to measure high-speed fluctuations in magnetic materials. Knowledge obtained by these new measurements could be used to advance technologies ranging from traditional computing to the emerging field of quantum computing.

A workshop led by scientists at ORNL sketched a road map toward a longtime goal: development of autonomous, or self-driving, next-generation research laboratories.

Not only did ORNL take home top honors at the 2024 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24), but the lab’s computing staff also shared career advice and expertise with students eager to enter the world of supercomputing.

Neus Domingo Marimon, leader of the Functional Atomic Force Microscopy group at the Center for Nanophase Materials Sciences of ORNL, has been elevated to senior member of the Institute of Electrical and Electronics Engineers.

Massimiliano (Max) Lupo Pasini, an R&D data scientist from ORNL, was awarded the National Energy Research Scientific Computing Center’s High Performance Computing Achievement Award for High Impact Scientific Achievement for his work in “Groundbreaking contributions to scientific machine learning, particularly through the development of HydraGNN.”

Phong Le is a computational hydrologist at ORNL who is putting his skills in hydrology, numerical modeling, machine learning and high-performance computing to work quantifying water-related risks for humans and the environment.