Computational Chemistry and Nanomaterials News

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Distinguished staff fellow Gang Seob “GS” Jung knew from an early age he wanted to be a scientist. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Gang Seob “GS” Jung: Solving scientific puzzles using computational models

September 26, 2022

Gang Seob “GS” Jung has known from the time he was in middle school that he was interested in science.

Shown here is the structure of the NEMO protein. A team from ORNL conducted extensive molecular dynamics work on Summit by using both quantum mechanics and machine-learning methods to look at the binding affinity of NEMO and 3CLpro in humans and other species and to consider the structural models derived from the sequences of other coronaviruses. Image courtesy Nature Communications, Dan Jacobson/ORNL.

Lab experiments support COVID-19 bradykinin storm theory

September 15, 2022

A new paper published in Nature Communications adds further evidence to the bradykinin storm theory of COVID-19’s viral pathogenesis — a theory that was posited two years ago by a team of researchers at the Department of Energy’s Oak Ridge Nati

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

Improving materials for energy storage, generation

September 6, 2022

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.

Oak Ridge National Laboratory scientists are enhancing the performance of polymer materials for next-generation lithium batteries. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Materials — Tailor-made molecules

June 2, 2022

Researchers at Oak Ridge National Laboratory are using state-of-the-art methods to shed light on chemical separations needed to recover rare-earth elements and secure critical materials for clean energy technologies.

A smart approach to microscopy and imaging developed at Oak Ridge National Laboratory could drive discoveries in materials for future technologies. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

Self-driving microscopes discover shortcuts to new materials

May 9, 2022

Researchers at ORNL are teaching microscopes to drive discoveries with an intuitive algorithm, developed at the lab’s Center for Nanophase Materials Sciences, that could guide breakthroughs in new materials for energy technologies, sensing and computing

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

A material’s spins, depicted as red spheres, are probed by scattered neutrons. Applying an entanglement witness, such as the QFI calculation pictured, causes the neutrons to form a kind of quantum gauge. This gauge allows the researchers to distinguish between classical and quantum spin fluctuations. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

Key witness helps scientists detect ‘spooky’ quantum entanglement in solid materials

November 8, 2021

A team led by the U.S. Department of Energy’s Oak Ridge National Laboratory demonstrated the viability of a “quantum entanglement witness” capable of proving the presence of entanglement between magnetic particles, or spins, in a quantum material.

Researchers at ORNL and the University of Tennessee developed an automated workflow that combines chemical robotics and machine learning to speed the search for stable perovskites. Credit: Jaimee Janiga/ORNL, U.S. Dept of Energy

Automated chemistry sets new pace for materials discovery

March 9, 2021

Researchers at the Department of Energy’s Oak Ridge National Laboratory and the University of Tennessee are automating the search for new materials to advance solar energy technologies.

ORNL has modeled the spike protein that binds the novel coronavirus to a human cell for better understanding of the dynamics of COVID-19. Credit: Stephan Irle/ORNL, U.S. Dept. of Energy

Computing – Modeling COVID dynamics

February 15, 2021

To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human ce

ORNL’s Ziatdinov named Foresight Fellow

January 14, 2021

Maxim Ziatdinov, a research scientist in the Computational Sciences and Engineering Division at the Department of Energy’s Oak Ridge National Laboratory, has been selected as a 2021 Foresight Fellow in Physics-Guided Artificial Intelligence for

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Computational Chemistry and Nanomaterials Sciences Group