Skip to main content
Data scientists at Oak Ridge National Laboratory have completed a study of long-term trends in the relationship between the timing of tree leafing and rising temperatures in the United States. The information is being incorporated into DOE’s Energy Exascale Earth System Model. Photo Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy

A team of scientists led by Oak Ridge National Laboratory found that while all regions of the country can expect an earlier start to the growing season as temperatures rise, the trend is likely to become more variable year-over-year in hotter regions.

A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy

A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days. 

Researchers in ORNL’s Quantum Information Science group summarized their significant contributions to quantum networking and quantum computing in a special issue of Optics & Photonics News. Image credit: Christopher Tison and Michael Fanto/Air Force Research Laboratory.

A team from the ORNL has conducted a series of experiments to gain a better understanding of quantum mechanics and pursue advances in quantum networking and quantum computing, which could lead to practical applications in cybersecurity and other areas.

Dalton Lunga

A typhoon strikes an island in the Pacific Ocean, downing power lines and cell towers. An earthquake hits a remote mountainous region, destroying structures and leaving no communication infrastructure behind.

VERA, the Virtual Environment for Reactor Applications

Nuclear scientists at Oak Ridge National Laboratory have established a Nuclear Quality Assurance-1 program for a software product designed to simulate today’s commercial nuclear reactors – removing a significant barrier for industry adoption of the technology.

ADIOS logo

Researchers across the scientific spectrum crave data, as it is essential to understanding the natural world and, by extension, accelerating scientific progress.

As hurricanes formed in the Gulf Coast, ORNL activated a computing technique to quickly gather building structure data from Texas’ coastal counties. Credit: Mark Tuttle/Oak Ridge National Laboratory, U.S. Dept. of Energy

Geospatial scientists at Oak Ridge National Laboratory have developed a novel method to quickly gather building structure datasets that support emergency response teams assessing properties damaged by Hurricanes Harvey and Irma. By coupling deep learning with high-performance comp...

ORNL’s Frank Combs and Michael Starr of the U.S. Armed Forces (driver) work in ORNL’s Vehicle Security Laboratory to evaluate a prototype device that can detect network intrusions in all modern vehicles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

A new Oak Ridge National Laboratory-developed method promises to protect connected and autonomous vehicles from possible network intrusion. Researchers built a prototype plug-in device designed to alert drivers of vehicle cyberattacks. The prototype is coded to learn regular timing...

Arjun Shankar

The field of “Big Data” has exploded in the blink of an eye, growing exponentially into almost every branch of science in just a few decades. Sectors such as energy, manufacturing, healthcare and many others depend on scalable data processing and analysis for continued in...

Scientists will use ORNL’s computing resources such as the Titan supercomputer to develop deep learning solutions for data analysis. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy.

A team of researchers from Oak Ridge National Laboratory has been awarded nearly $2 million over three years from the Department of Energy to explore the potential of machine learning in revolutionizing scientific data analysis. The Advances in Machine Learning to Improve Scient...