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ORNL scientists developed a method that improves the accuracy of the CRISPR Cas9 gene editing tool used to modify microbes for renewable fuels and chemicals production. This research draws on the lab’s expertise in quantum biology, artificial intelligence and synthetic biology. Credit: Philip Gray/ORNL, U.S. Dept. of Energy

Scientists at ORNL used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.

Hilda Klasky

Hilda Klasky, an R&D staff member in the Scalable Biomedical Modeling group at ORNL, has been selected as a senior member of the Association of Computing Machinery, or ACM.

The OpeN-AM experimental platform, installed at the VULCAN instrument at ORNL’s Spallation Neutron Source, features a robotic arm that prints layers of molten metal to create complex shapes. This allows scientists to study 3D printed welds microscopically. Credit: Jill Hemman, ORNL/U.S. Dept. of Energy

Using neutrons to see the additive manufacturing process at the atomic level, scientists have shown that they can measure strain in a material as it evolves and track how atoms move in response to stress.

The image conceptualizes the processing, structure and mechanical behavior of glassy ion conductors for solid state lithium batteries. Credit: Adam Malin/ORNL, U.S. Dept. of Energy

As current courses through a battery, its materials erode over time. Mechanical influences such as stress and strain affect this trajectory, although their impacts on battery efficacy and longevity are not fully understood.

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of its Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making. Credit: Rachel Green/ORNL, U.S. Dept. of Energy

The Department of Energy’s Oak Ridge National Laboratory announced the establishment of the Center for AI Security Research, or CAISER, to address threats already present as governments and industries around the world adopt artificial intelligence and take advantage of the benefits it promises in data processing, operational efficiencies and decision-making.

An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL

Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.

The configurational ensemble (a collection of 3D structures) of an intrinsically disordered protein, the N-terminal of c-Src kinase, which is a major signaling protein in humans. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy.

Using the Titan supercomputer and the Spallation Neutron Source at the Department of Energy’s Oak Ridge National Laboratory, scientists have created the most accurate 3D model yet of an intrinsically disordered protein, revealing the ensemble of its atomic-level structures.

Pictured in this early conceptual drawing, the Translational Research Capability planned for Oak Ridge National Laboratory will follow the design of research facilities constructed during the laboratory’s modernization campaign.

OAK RIDGE, Tenn., May 7, 2019—Energy Secretary Rick Perry, Congressman Chuck Fleischmann and lab officials today broke ground on a multipurpose research facility that will provide state-of-the-art laboratory space 

Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.

Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.

(From left) ORNL Associate Laboratory Director for Computing and Computational Sciences Jeff Nichols; ORNL Health Data Sciences Institute Director Gina Tourassi; DOE Deputy Under Secretary for Science Thomas Cubbage; ORNL Task Lead for Biostatistics Blair Christian; and ORNL Research Scientist Ioana Danciu were invited to the White House to showcase an ORNL-developed digital tool aimed at better matching cancer patients with clinical trials.

OAK RIDGE, Tenn., March 4, 2019—A team of researchers from the Department of Energy’s Oak Ridge National Laboratory Health Data Sciences Institute have harnessed the power of artificial intelligence to better match cancer patients with clinical trials.