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Ashley Barker. Credit: Carlos Jones/ORNL

At the National Center for Computational Sciences, Ashley Barker enjoys one of the least complicated–sounding job titles at ORNL: section head of operations. But within that seemingly ordinary designation lurks a multitude of demanding roles as she oversees the complete user experience for NCCS computer systems.

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.

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.

Quantum information scientists at ORNL hope to harness beams of light, or photons, as qubits for quantum networking. Credit: ORNL/Carlos Jones

ORNL’s next major computing achievement could open a new universe of scientific possibilities accelerated by the primal forces at the heart of matter and energy.

ORNL will use its land surface modeling tools to determine Baltimore’s climate risk and analyze green infrastructure improvements that can help mitigate impacts on underserved communities as part of a DOE Urban Integrated Field Laboratory project. Source: Google Earth, accessed Sept. 12, 2022

ORNL researchers are deploying their broad expertise in climate data and modeling to create science-based mitigation strategies for cities stressed by climate change as part of two U.S. Department of Energy Urban Integrated Field Laboratory projects.

Scattering-type scanning near-field optical microscopy, a nondestructive technique in which the tip of the probe of a microscope scatters pulses of light to generate a picture of a sample, allowed the team to obtain insights into the composition of plant cell walls. Credit: Ali Passian/ORNL, U.S. Dept. of Energy

To optimize biomaterials for reliable, cost-effective paper production, building construction, and biofuel development, researchers often study the structure of plant cells using techniques such as freezing plant samples or placing them in a vacuum.

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. 

QLAN submit - A team from the U.S. Department of Energy’s Oak Ridge National Laboratory, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL using entangled photons passing through optical fiber. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.

An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy

To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.