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Promethium’s secrets exposed
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Jim Szybist, Propulsion Science section head at ORNL, is applying his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy.

Jim Szybist: Toward a greener transportation future

What’s getting Jim Szybist fired up these days? It’s the opportunity to apply his years of alternative fuel combustion and thermodynamics research to the challenge of cleaning up the hard-to-decarbonize, heavy-duty mobility sector — from airplanes to locomotives to ships and massive farm combines.

TEDB

Tracking data: DOE’s 40th edition Transportation Energy Data Book monitors U.S. mobility trends, charges up on electric outlook

It’s been referenced in Popular Science and Newsweek, cited in the Economic Report of the President, and used by agencies to create countless federal regulations.

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

VA, ORNL and Harvard develop novel method to identify complex medical relationships

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.

Andrew Sutton joined ORNL in 2020 to guide a newly formed team that focuses on chemical process scale-up in advanced manufacturing. Credit: ORNL, U.S. Dept. of Energy

Andrew Sutton: Exploring carbon sources through fundamental chemistry

When Andrew Sutton arrived at ORNL in late 2020, he knew the move would be significant in more ways than just a change in location.

ORNL research scientist Christa Brelsford explained a mathematical framework she developed in 2018, which showed increased availability of infrastructure didn’t necessarily reduce inequality in its access. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Study measuring infrastructure inequity addresses disparities in growing cities

Unequal access to modern infrastructure is a feature of growing cities, according to a study published this week in the Proceedings of the National Academy of Sciences

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

Retro technique advances modern bacterial engineering for bioenergy

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

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

QIS investments position ORNL to lead the quantum revolution

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.

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

Scientists use Summit supercomputer, deep learning to predict protein functions at genome scale

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.

From left, Amit Naskar, Ngoc Nguyen and Christopher Bowland in ORNL’s Carbon and Composites Group bring a new capability—structural health monitoring—to strong, lightweight materials promising for transportation applications.

Self-sensing materials are here

Carbon fiber composites—lightweight and strong—are great structural materials for automobiles, aircraft and other transportation vehicles. They consist of a polymer matrix, such as epoxy, into which reinforcing carbon fibers have been embedded. Because of differences in the mecha...

L-R, Researchers Nils Stenvig, Isabelle Snyder and Travis Smith are developing tools and deploying sensors to aid decision-making as Puerto Rico rebuilds and modernizes its power grid.

Modeling, monitoring and microgrids: ORNL provides help as Puerto Rico rebuilds

As Puerto Rico works to restore and modernize its power grid after last year’s devastating hurricane season, researchers at Oak Ridge National Laboratory have stepped up to provide unique analysis, sensing and modeling tools to better inform decisions.