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Media Contacts
John “Jack” Cahill is out to illuminate previously unseen processes with new technology, advancing our understanding of how chemicals interact to influence complex systems whether it’s in the human body or in the world beneath our feet.
In human security research, Thomaz Carvalhaes says, there are typically two perspectives: technocentric and human centric. Rather than pick just one for his work, Carvalhaes uses data from both perspectives to understand how technology impacts the lives of people.
Scientists at ORNL have created a miniaturized environment to study the ecosystem around poplar tree roots for insights into plant health and soil carbon sequestration.
Chemical and environmental engineer Samarthya Bhagia is focused on achieving carbon neutrality and a circular economy by designing new plant-based materials for a range of applications from energy storage devices and sensors to environmentally friendly bioplastics.
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.
Jennifer Morrell-Falvey’s interest in visualizing the science behind natural processes was what drew her to ORNL in what she expected to be a short stint some 18 years ago.
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
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.
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
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.