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When an electron beam drills holes in heated graphene, single-atom vacancies, shown in purple, diffuse until they join with other vacancies to form stationary structures and chains, shown in blue. Credit: Ondrej Dyck/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers serendipitously discovered when they automated the beam of an electron microscope to precisely drill holes in the atomically thin lattice of graphene, the drilled holes closed up.

Jack Cahill of ORNL’s Biosciences Division is developing new techniques to view and measure the previously unseen to better understand important chemical processes at play in plant-microbe interactions and in human health. In this photo, Cahill is positioning a rhizosphere-on-a-chip platform for imaging by mass spectrometry. Credit: Carlos Jones/ORNL, U.S. Dept of Energy

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.

ORNL researchers led by Michael Garvin, left, and David Kainer discovered genetic mutations called structural variants and linked them to autism spectrum disorders, demonstrating an approach that could be used to develop better diagnostics and drug therapies. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

ORNL researchers discovered genetic mutations that underlie autism using a new approach that could lead to better diagnostics and drug therapies.

Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy

A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.

Sophie Voisin, an ORNL software engineer, was part of a team that won a 2014 R&D 100 Award for work on Intelligent Software for a Personalized Modeling of Expert Opinions, Decisions and Errors in Visual Examination Tasks. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

Cameras see the world differently than humans. Resolution, equipment, lighting, distance and atmospheric conditions can impact how a person interprets objects on a photo.

Samarthya Bhagia examines a sample of a thermoplastic composite material additively manufactured using poplar wood and polylactic acid. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

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.

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions. Credit: Getty Images

Oak Ridge National Laboratory researchers developed an invertible neural network, a type of artificial intelligence that mimics the human brain, to improve accuracy in climate-change models and predictions.

Jennifer Morrell-Falvey leads the Molecular and Cellular Imaging group at ORNL, advancing new insights in several scientific areas, including the interactions between plants and microbes that influence ecosystem health and carbon cycling. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

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. 

Researchers at Oak Ridge National Laboratory demonstrated center-of-mass scanning transmission electron microscopy to observe lithium along with heavier elements in battery materials at atomic resolution. Credit: Chad Malone/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers demonstrated an electron microscopy technique for imaging lithium in energy storage materials, such as lithium ion batteries, at the atomic scale.

ORNL researchers worked with partners at the Colorado School of Mines and Baylor University to develop a new process optimization and control method for a closed-circuit reverse osmosis desalination system. The work is intended to support fully automated, decentralized water treatment plants. Credit: Andrew Sproles/ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.