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Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.

ORNL neural network study harnesses made-to-order design to pair properties to materials

April 21, 2022

A study led by researchers at ORNL could help make materials design as customizable as point-and-click.

Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy

Artificially altered material could accelerate neuromorphic device development

January 10, 2022

Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant

ORNL’s Sergei Kalinin and Rama Vasudevan (foreground) use scanning probe microscopy to study bulk ferroelectricity and surface electrochemistry -- and generate a lot of data. Credit: Jason Richards/ORNL, U.S. Dept. of Energy

ORNL’s superb materials expertise, data and AI tools propel progress

May 3, 2021

At the Department of Energy’s Oak Ridge National Laboratory, scientists use artificial intelligence, or AI, to accelerate the discovery and development of materials for energy and information technologies.

Selenium atoms, represented by orange, implant in a monolayer of blue tungsten and yellow sulfur to form a Janus layer. In the background, electron microscopy confirms atomic positions. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy

Process for ‘two-faced’ nanomaterials may aid energy, information tech

June 26, 2020

An ORNL team used a simple process to implant atoms precisely into the top layers of ultra-thin crystals, yielding two-sided structures with different chemical compositions.

ORNL is in the fight against COVID-19

April 15, 2020

In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s Oak Ridge National Laboratory are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron sc

To understand the electronic structures of solids and predict their properties, ORNL’s Valentino Cooper uses density functional theory (DFT), which models how many electrons are in a region rather than where those electrons are. “DFT essentially presents one electron existing in a ‘sea foam’ and tells how dense that foam is,” he said. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy

Valentino Cooper: Building foundations for solid science

February 24, 2020

Valentino (“Tino”) Cooper of the Department of Energy’s Oak Ridge National Laboratory uses theory, modeling and computation to improve fundamental understanding of advanced materials for next-generation energy and information technologies.

Closely spaced hydrogen atoms could facilitate superconductivity in ambient conditions

February 3, 2020

An international team of researchers has discovered the hydrogen atoms in a metal hydride material are much more tightly spaced than had been predicted for decades — a feature that could possibly facilitate superconductivity at or near room temperature

The lithium-aluminum-layered double hydroxide chloride (LDH) sorbent being developed by ORNL targets recovery of lithium from geothermal brines—paving the way for increased domestic production of the material for today’s rechargeable batteries. Credit: Oak Ridge National Laboratory

ORNL develops sorbent to recover lithium from geothermal brines

January 21, 2020

In the quest for domestic sources of lithium to meet growing demand for battery production, scientists at ORNL are advancing a sorbent that can be used to more efficiently recover the material from brine wastes at geothermal power plants.

Materials