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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. 

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.

Researchers at Stanford University, the European Center for Medium-Range Weather Forecasts, or ECMWF, and ORNL used the lab’s Summit supercomputer to better understand atmospheric gravity waves, which influence significant weather patterns that are difficult to forecast. 

The National Center for Computational Sciences, located at the Department of Energy’s 91����, made a strong showing at computing conferences this fall. Staff from across the center participated in numerous workshops and invited speaking engagements.

Daryl Yang is coupling his science and engineering expertise to devise new ways to measure significant changes going on in the Arctic, a region that’s warming nearly four times faster than other parts of the planet. The remote sensing technologies and modeling tools he develops and leverages for the Next-Generation Ecosystem Experiments in the Arctic project, or NGEE Arctic, help improve models of the ecosystem to better inform decision-making as the landscape changes.

A newly established internship between ORNL and Maryville College is bringing cybersecurity careers to a local liberal arts college. The internship was established by a Maryville College alumni who recently joined ORNL. 

91���� scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.

John Lagergren, a staff scientist in 91����’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.

Rigoberto “Gobet” Advincula, a scientist with joint appointments at ORNL and the University of Tennessee, has been named a Fellow of the American Institute for Medical and Biological Engineering.

In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.