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In this artist’s conception of the process, an automated deposition system places a new material onto a base material (purple beam, right) as the last sample that was made is analyzed and sent to the AI (green beams, brain, left). The AI tells the pulsed laser deposition machine what to do next (data cable, bottom).
Researchers harness AI for autonomous discovery and optimization of materials
Students gather at a poster session
Students acquire skills at Quantum Science Center
Rectangular box being lifted by a red pully system up the left side of the building
Researchers make ‘green’ floor to replace steel

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Scientists with the Center for Bioenergy Innovation at ORNL highlighted a hybrid approach that uses microbes and catalysis to convert cellulosic biomass into fuels suitable for aviation and other difficult-to-electrify sectors. Credit: ORNL, U.S. Dept. of Energy

New perspective highlights promise of hybrid approach for cellulosic biofuel production

The rapid pace of global climate change has added urgency to developing technologies that reduce the carbon footprint of transportation technologies, especially in sectors that are difficult to electrify.

This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL

ORNL multimodal study sheds new light on promising photovoltaic material

A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.

ORNL biogeochemist Teri O’Meara is focused on improving how coastal systems are represented in global climate models, enabling better predictions about the future of these critical ecosystems. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Teri O’Meara: Making a splash with coastal ecology

Surrounded by the mountains of landlocked Tennessee, Oak Ridge National Laboratory’s Teri O’Meara is focused on understanding the future of the vitally important ecosystems lining the nation’s coasts.

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.

The Energy Exascale Earth System Model project reliably simulates aspects of earth system variability and projects decadal changes that will critically impact the U.S. energy sector in the future. A new version of the model delivers twice the performance of its predecessor. Credit: E3SM, Dept. of Energy

Updated exascale system for Earth simulations delivers twice the speed

A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.

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.