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ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

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. 
 

Chlorella Vulgaris

In the search for ways to fight methylmercury in global waterways, scientists at Oak Ridge National Laboratory discovered that some forms of phytoplankton are good at degrading the potent neurotoxin.

Saubhagya Rathore uses his modeling, hydrology and engineering expertise to improve understanding of the nation’s watersheds to better predict the future climate and to guide resilience strategies. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Growing up exploring the parklands of India where Rudyard Kipling drew inspiration for The Jungle Book left Saubhagya Rathore with a deep respect and curiosity about the natural world. He later turned that interest into a career in environmental science and engineering, and today he is working at ORNL to improve our understanding of watersheds for better climate prediction and resilience.

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Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.

Jerry Parks leads the Molecular Biophysics group at ORNL, leveraging his expertise in computational chemistry and bioinformatics to unlock the inner workings of proteins—molecules that govern cellular structure and function and are essential to life. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy

When reading the novel Jurassic Park as a teenager, Jerry Parks found the passages about gene sequencing and supercomputers fascinating, but never imagined he might someday pursue such futuristic-sounding science.

ORNL scientists mutated amino acids in a receptor protein, shown in green, which diminished interaction with the SARS-CoV-2 virus spike protein, shown in red. Mutating the receptor protein hampered the virus’s ability to infect host cells. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists exploring bioenergy plant genetics have made a surprising discovery: a protein domain that could lead to new COVID-19 treatments.

Oak Ridge National Laboratory led a team of scientists to design a molecule that disrupts the infection mechanism of the SARS-CoV-2 coronavirus and could be used to develop new treatments for COVID-19 and future virus outbreaks. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory designed a molecule that disrupts the infection mechanism of the SARS-CoV-2 coronavirus and could be used to develop new treatments for COVID-19 and other viral diseases.

Hydrologist Jesus Gomez-Velez brings his expertise in river systems and mathematics to ORNL’s modeling and simulation research to better understand flow and transport processes in the nation’s watersheds. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Hydrologist Jesús “Chucho” Gomez-Velez is in the right place at the right time with the right tools and colleagues to explain how the smallest processes within river corridors can have a tremendous impact on large-scale ecosystems.

Shown here is the structure of the NEMO protein. A team from ORNL conducted extensive molecular dynamics work on Summit by using both quantum mechanics and machine-learning methods to look at the binding affinity of NEMO and 3CLpro in humans and other species and to consider the structural models derived from the sequences of other coronaviruses. Image courtesy Nature Communications, Dan Jacobson/ORNL.

A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge National Laboratory.

A team of researchers used mathematics to predict which areas of the SARS-CoV-2 spike protein are most likely to mutate. Credit: Jill Hemman/ORNL, U.S. Dept. of Energy

Researchers from ORNL, the University of Tennessee at Chattanooga and Tuskegee University used mathematics to predict which areas of the SARS-CoV-2 spike protein are most likely to mutate.