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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 Oak Ridge National Laboratory, 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.”

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.

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.”

By editing the polymers of discarded plastics, ORNL chemists have found a way to generate new macromolecules with more valuable properties than those of the starting material.

P&G is using simulations on the ORNL Summit supercomputer to study how surfactants in cleaners cause eye irritation. By modeling the corneal epithelium, P&G aims to develop safer, concentrated cleaning products that meet performance and safety standards while supporting sustainability goals.

Benjamin Manard, a nuclear analytical chemist at ORNL, has been named the 2025 winner of the Emerging Leader in Atomic Spectroscopy Award from Spectroscopy magazine.

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.