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Scientists have found new, unexpected behaviors when SARS-CoV-2 – the virus that causes COVID-19 – encounters drugs known as inhibitors, which bind to certain components of the virus and block its ability to reproduce.

Stan Wullschleger has been selected as the associate laboratory director for the Biological and Environmental Systems Science Directorate, or BESSD, at ORNL.

Thirty-two Oak Ridge National Laboratory employees were named among teams recognized by former DOE Secretary Dan Brouillette with Secretary’s Honor Awards as he completed his term. Four teams received new awards that reflect DOE responses to the coronavirus pandemic.

In the quest for advanced vehicles with higher energy efficiency and ultra-low emissions, ORNL researchers are accelerating a research engine that gives scientists and engineers an unprecedented view inside the atomic-level workings of combustion engines in real time.

Six scientists at the Department of Energy’s Oak Ridge National Laboratory were named Battelle Distinguished Inventors, in recognition of obtaining 14 or more patents during their careers at the lab.

Seven ORNL scientists have been named among the 2020 Highly Cited Researchers list, according to Clarivate, a data analytics firm that specializes in scientific and academic research.

ORNL has added 10 virtual tours to its campus map, each with multiple views to show floor plans, rotating dollhouse views and 360-degree navigation. As a user travels through a map, pop-out informational windows deliver facts, videos, graphics and links to other related content.

To better understand how the novel coronavirus behaves and how it can be stopped, scientists have completed a three-dimensional map that reveals the location of every atom in an enzyme molecule critical to SARS-CoV-2 reproduction.

Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.

Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.