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This image depicts a visualization of an outflow of galactic wind at a single point in time using Cholla. Credit: Evan Schneider/University of Pittsburgh

A trio of new and improved cosmological simulation codes was unveiled in a series of presentations at the annual April Meeting of the American Physical Society in Minneapolis.

Each dot represents a Twitterer discussing COVID-19 from April 16 to April 22, 2021. The closer the dots are to the center, the greater the influence. The brighter the color, the stronger the intent. Image credit: ORNL

Using disinformation to create political instability and battlefield confusion dates back millennia. However, today’s disinformation actors use social media to amplify disinformation that users knowingly or, more often, unknowingly perpetuate. Such disinformation spreads quickly, threatening public health and safety. Indeed, the COVID-19 pandemic and recent global elections have given the world a front-row seat to this form of modern warfare.

The newest Gaea system provides increased performance for more advanced climate modeling and simulation

Oak Ridge National Laboratory, in partnership with the National Oceanic and Atmospheric Administration, is launching a new supercomputer dedicated to climate science research. The new system is the fifth supercomputer to be installed and run by the National Climate-Computing Research Center at ORNL.

Students from UC Merced collect water samples at Guadalupe Reservoir in Santa Clara County, California. Credit: UC Merced

Environmental scientists at ORNL have recently expanded collaborations with minority-serving institutions and historically Black colleges and universities across the nation to broaden the experiences and skills of student scientists while bringing fresh insights to the national lab’s missions.

Distinguished staff fellow Gang Seob “GS” Jung knew from an early age he wanted to be a scientist. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Gang Seob “GS” Jung has known from the time he was in middle school that he was interested in science.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

Earth Day

Tackling the climate crisis and achieving an equitable clean energy future are among the biggest challenges of our time. 

This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.

The Energy Exascale Earth System Model project reliably simulates aspects of earth system variability and projects decadal changes that will critically impact the U.S. energy sector in the future. A new version of the model delivers twice the performance of its predecessor. Credit: E3SM, Dept. of Energy

A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.