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  • 2018-01-03 12:05:04
  • Article ID: 687411

Story Tips From the Department of Energy's Oak Ridge National Laboratory, January 2018

  • Credit: Jason Johnson/SIU School of Medicine

    Studying reproductive microbiomes could help identify women with endometriosis without an invasive surgical procedure, even before symptoms start.

  • Credit: Catherine Schuman and Margaret Drouhard/Oak Ridge National Laboratory, U.S. Dept. of Energy

    An example of a spiking neural network shows how data can be classified using the neuromorphic device.

  • Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy

    Victoria DiStefano, University of Tennessee Bredesen Center graduate student researcher, and her adviser, Lawrence Anovitz of ORNL, study rock samples from the Eagle Ford Shale Formation in Texas.

  • Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy

    An ORNL-led team used neutrons to understand how water flows through fractured rock.

  • Credit: Fie Xie/Oak Ridge National Laboratory, U.S. Dept. of Energy

    An analysis from Oak Ridge National Laboratory shows the optimal number of fast chargers needed at electric vehicle charging stations between California cities in a multi-stage deployment through 2029.

  • Credit: Jill Hemman/Oak Ridge National Laboratory, U.S. Dept. of Energy

    Long-range ordering of magnetic ions in a graphene-like material (on left) is disrupted by placing nonmagnetic ions on the honeycomb lattice, resulting in a quantum spin liquid state (on right). As neutrons (blue line) scatter off the magnetically disordered material, they produce unusual particles such as Majorana fermions (purple wave) that move through the lattice disrupting or breaking apart magnetic interactions between “spinning” electrons.

 

Credit: University of Texas at Austin

A computed tomography image details fractures in rock samples from the Eagle Ford Shale Formation in Texas.

 

 

Biology—Telltale microbes 

A new process to identify certain microbes in women could be used to diagnose endometriosis without invasive surgery, even before symptoms start. A collaborative research team analyzed bacteria from a small sample of premenopausal women undergoing laparoscopic surgery for suspected endometriosis. Endometriosis occurs when the uterus’ lining grows outside the uterus, resulting in painful lesions and possible infertility. Researchers from Southern Illinois University School of Medicine, Michigan State University and Oak Ridge National Laboratory studied microbes from women with and without endometriosis and compared bacteria from the uterus with vaginal microbes. “We determined that the uterine microbiome is not simply a subset of the vaginal microbiome and that microbial diversity increased with stage III endometriosis,” said ORNL’s Melissa Cregger, lead author of a pilot study published in Reproductive Immunology. The team plans to further analyze the microbiome to diagnosis ovarian and endometrial cancers and evaluate responses to treatment. [Contact: Sara Shoemaker, (865) 576-9219; shoemakerms@ornl.gov

Image: https://www.ornl.gov/sites/default/files/BraundmeierA_0011_0.jpg 

Caption: Studying reproductive microbiomes could help identify women with endometriosis without an invasive surgical procedure, even before symptoms start. Credit: Jason Johnson/SIU School of Medicine 

Data—Plug-in learning 

For smarter data management and analysis, researchers have developed a low-power neuromorphic device based on spiking neural networks that can quickly and more efficiently analyze and classify data. The versatile platform, which will be compatible with instruments that collect data during scientific experiments, becomes “smarter” as it classifies large amounts of information into smaller, more manageable datasets. “The device is designed to get better at the task it was trained to do,” said Oak Ridge National Laboratory’s Catherine Schuman, who developed the device’s training algorithms. She and University of Tennessee collaborator Garrett Rose advise UT students who demonstrated the technology’s data-crunching abilities on well-known biology and medical research datasets. The ORNL-UT team published their results in an IEEE journal. The researchers are testing the device’s capabilities on scientific data such as complex neutrino collision data. [Contact: Sara Shoemaker, (865) 576-9219; shoemakerms@ornl.gov

Image: https://www.ornl.gov/sites/default/files/news/images/Spiking_neural_network_ORNL.jpg 

Caption: An example of a spiking neural network shows how data can be classified using the neuromorphic device. Credit: Catherine Schuman and Margaret Drouhard/Oak Ridge National Laboratory, U.S. Dept. of Energy 

Fossil energy—Neutrons run deep 

To improve models for drilling, hydraulic fracturing and underground storage of carbon dioxide, Oak Ridge National Laboratory scientists used neutrons to understand how water flows through fractured rock. Researchers used neutrons bouncing off the hydrogen in water molecules to see inside the rock’s microstructure without destroying it and quantify water uptake in real time. “One of the biggest challenges with shale is that it’s such a complex system,” ORNL’s Victoria DiStefano said. “Neutrons help us grasp the complex rock and fracture properties, which determine how quickly water uptake occurs in the rock.” Results of the study, which used rock samples from the oil- and gas-rich Eagle Ford Shale Formation in Texas, are detailed in the Journal of Earth Science. Future research will explore how fracture characteristics, such as roughness and mineralogy, affect these interactions. [Contact: Stephanie Seay, (865) 576-9894; seaysg@ornl.gov

Image #1: https://www.ornl.gov/sites/default/files/Fossil_energy_ORNL1.jpg 

Caption #1: Victoria DiStefano, University of Tennessee Bredesen Center graduate student researcher, and her adviser, Lawrence Anovitz of ORNL, study rock samples from the Eagle Ford Shale Formation in Texas. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy 

Image #2: https://www.ornl.gov/sites/default/files/Fossil_energy_ORNL2.jpg 

Caption #2: An ORNL-led team used neutrons to understand how water flows through fractured rock. Credit: Jason Richards/Oak Ridge National Laboratory, U.S. Dept. of Energy 

Image #3: https://www.ornl.gov/sites/default/files/Fossil_energy_ORNL3.jpg 

Caption #3: A computed tomography image details fractures in rock samples from the Eagle Ford Shale Formation in Texas. Credit: University of Texas at Austin 

Video clip: https://www.ornl.gov/sites/default/files/giphy-13.gif 

Video caption: A computed tomography image details fractures in rock samples from the Eagle Ford Shale Formation in Texas. Credit: University of Texas at Austin

Transportation—Better charging access 

Officials responsible for anticipating the demand for electric vehicle charging stations could get help through a sophisticated new method developed at Oak Ridge National Laboratory. The method considers electric vehicle volume and the random timing of vehicles arriving at charging stations to determine an optimal number of chargers needed in the near and long term. “Our method can provide insights for planners to strategically balance the cost of new infrastructure with establishing a level of service that can enable and sustain increased use of electric vehicles,” said ORNL’s Zhenhong Lin. The study, published in Transportation Research Part E, mapped the number of direct current fast chargers needed at new stations between California cities if regional infrastructure were added in stages through 2029. The method can also be applied to other states, regions and the nation. [Contact: Kim Askey, (865) 576-2841; askeyka@ornl.gov

Image: https://www.ornl.gov/sites/default/files/news/images/Untitled-1%20%281%29.jpg

Caption: An analysis from Oak Ridge National Laboratory shows the optimal number of fast chargers needed at electric vehicle charging stations between California cities in a multi-stage deployment through 2029. Credit: Fie Xie/Oak Ridge National Laboratory, U.S. Dept. of Energy 

Materials—Shape-memory conductors 

A novel approach that creates a renewable, leathery material—programmed to remember its shape—may offer a low-cost alternative to conventional conductors for applications in sensors and robotics. To make the bio-based, shape-memory material, Oak Ridge National Laboratory scientists streamlined a solvent-free process that mixes rubber with lignin—the by-product of woody plants used to make biofuels. They fashioned the leathery material into small strips and brushed on a thin layer of silver nanoparticles to activate electrical conductivity. The strips were stretched or curled and then frozen as part of the process to program the material to return to its intended shape, which occurs after the application of low heat. “The performance of this polymer can be tuned further,” said ORNL’s Amit Naskar. “Variant lignins can be used at different ratios, which determines the material’s pliability.” ORNL detailed their method in Macromolecules. [Contact: Sara Shoemaker, (865) 576-9219; shoemakerms@ornl.gov

Image: https://www.ornl.gov/sites/default/files/Screen%20Shot%202017-12-22%20at%202.01.38%20PM.jpg 

Caption: An Oak Ridge National Laboratory team developed a novel approach that creates a renewable, leathery material—programmed to remember its shape—which may offer a low-cost alternative to conventional conductors for applications in sensors and robotics.

Credit: Jenny Woodbery/Oak Ridge National Laboratory, U.S. Dept. of Energy 

Video: https://www.youtube.com/watch?time_continue=1&v=CGGkJo6WJJc 

Video caption: An Oak Ridge National Laboratory team developed a novel approach that creates a renewable, leathery material—programmed to remember its shape—which may offer a low-cost alternative to conventional conductors for applications in sensors and robotics. Credit: Jenny Woodbery/Oak Ridge National Laboratory, U.S. Dept. of Energy 

Neutrons—Exotic particles 

A novel approach for studying magnetic behavior in a material called alpha-ruthenium trichloride may have implications for quantum computing. By suppressing the material’s magnetic order, scientists from Oak Ridge National Laboratory and the University of Tennessee observed behavior consistent with exotic particles that are predicted to emerge when energy is added to a quantum spin liquid, or QSL. QSLs exist in certain materials where magnetic moments fluctuate in a liquid-like state rather than forming an ordered pattern. The team disrupted the material’s magnetic order by substituting iridium ions for ruthenium, then used neutron scattering to characterize the resulting magnetic behavior. “Through this process, we saw hints of highly sought-after particles, which were robust and perhaps even more intense in the QSL state,” said UT’s Paige Kelley, coauthor of a study published in Physical Review Letters. “This discovery could be the future basis for a topologically protected qubit in a quantum computer.” [Contact: Paul Boisvert, 865-576-9047; boisvertpl@ornl.gov

Image: https://www.ornl.gov/sites/default/files/Neutrons-Exotic_particles.jpg 

Caption: Long-range ordering of magnetic ions in a graphene-like material (on left) is disrupted by placing nonmagnetic ions on the honeycomb lattice, resulting in a quantum spin liquid state (on right). As neutrons (blue line) scatter off the magnetically disordered material, they produce unusual particles such as Majorana fermions (purple wave) that move through the lattice disrupting or breaking apart magnetic interactions between “spinning” electrons. Credit: Jill Hemman/Oak Ridge National Laboratory, U.S. Dept. of Energy

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X-Rays Reveal 'Handedness' in Swirling Electric Vortices

Scientists used spiraling X-rays at Berkeley Lab to observe, for the first time, a property that gives left- or right-handedness to swirling electric patterns - dubbed polar vortices - in a layered material called a superlattice.

Breaking Bad Metals with Neutrons

By combining the latest developments in neutron scattering and theory, researchers are close to predicting phenomena like superconductivity and magnetism in strongly correlated electron systems. It is likely that the next advances in superconductivity and magnetism will come from such systems, but they might also be used in completely new ways such as quantum computing.

ORNL Researchers Use Titan to Accelerate Design, Training of Deep Learning Networks

For deep learning to be effective, existing neural networks to be modified, or novel networks designed and then "trained" so that they know precisely what to look for and can produce valid results. This is a time-consuming and difficult task, but one that a team of ORNL researchers recently demonstrated can be dramatically expedited with a capable computing system.

Dark Energy Survey Publicly Releases First Three Years of Data

At a special session held during the American Astronomical Society meeting in Washington, D.C., scientists on the Dark Energy Survey (DES) announced today the public release of their first three years of data. This first major release of data from the Survey includes information on about 400 million astronomical objects, including distant galaxies billions of light-years away as well as stars in our own galaxy.

Ingredients for Life Revealed in Meteorites That Fell to Earth

A detailed study of blue salt crystals found in two meteorites that crashed to Earth - which included X-ray experiments at Berkeley Lab - found that they contain both liquid water and a mix of complex organic compounds including hydrocarbons and amino acids.

Rewritable Wires Could Mean No More Obsolete Circuitry

An electric field switches the conductivity on and off in atomic-scale channels, which could allow for upgrades at will.

Research Outlines the Interconnected Benefits of Urban Agriculture

a team of researchers led by Arizona State University and Google has assessed the value of urban agriculture and quantified its benefits at global scale. They report their findings in "A Global Geospatial Ecosystems Services Estimate of Urban Agriculture," in the current issue of Earth's Future.

Filtering Water Better than Nature

Water passes through human-made straws faster than the "gold standard" protein, allowing us to filter seawater.

Machine Learning Provides a Bridge to the Texture of the Quantum World

Machine learning and neural networks are the foundation of artificial intelligence and image recognition, but now they offer a bridge to see and recognize exotic insulating phases in quantum materials.

A Rare Quantum State Realized in a New Material

A revolutionary material harbors magnetism and massless electrons that travel near the speed of light--for future ultrasensitive, high-efficiency electronics and sensors.


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DOE Announces Funding for New HPC4Manufacturing Industry Projects

The Department of Energy's Advanced Manufacturing Office (AMO) today announced the funding of $1.87 million for seven new industry projects under an ongoing initiative designed to utilize DOE's high-performance computing (HPC) resources and expertise to advance U.S. manufacturing and clean energy technologies.

DOE Announces First Awardees for New HPC4Materials for Severe Environments Program

The Department of Energy's Office of Fossil Energy (FE) today announced the funding of $450,000 for the first two private-public partnerships under a brand-new initiative aimed at discovering, designing and scaling up production of novel materials for severe environments.

Two Argonne Scientists Recognized for a Decade of Breakthroughs

Two scientists with the U.S. Department of Energy's (DOE) Argonne National Laboratory have been named to the Web of Science's Highly Cited List of 2017, ranking in the top 1 percent of their peers by citations and subject area. Materials Scientist Khalil Amine and Energy and Environmental Policy Scientist David Streets say they are thrilled to see their work -- and the laboratory -- recognized in such a way.

Argonne Welcomes Department of Energy Secretary Perry

U.S. Department of Energy Secretary Rick Perry visited Argonne National Laboratory yesterday, getting a first-hand view of the multifaceted and interdisciplinary research program laboratory of the Department.

Argonne names John Quintana Deputy Laboratory Director for Operations and COO

John Quintana has been named Deputy Laboratory Director for Operations and Chief Operations Officer (COO) of the U.S. Department of Energy's (DOE) Argonne National Laboratory.

Developing Next-Generation Sensing Technologies

Recently, the Advanced Research Projects Agency-Energy (ARPA-E) announced $20 million in funding for 15 projects that will develop a new class of sensor systems to enable significant energy savings via reduced demand for heating and cooling in residential and commercial buildings.

Supporting the Development of Offshore Wind Power Plants

Offshore wind is becoming a reality in the United States, especially in the northeast states. To support this development, the Center for Future Energy System (CFES) at Rensselaer Polytechnic Institute will present a webinar titled "Turbine and Transmission System Technologies for Offshore Wind (OSW) Power Plants." The program will be held on Wednesday, Dec. 20, from 2 to 4 p.m. Advance registration is required.

LLNL Releases Newly Declassified Nuclear Test Videos

Researchers at Lawrence Livermore National Laboratory (LLNL) released 62 newly declassified videos today of atmospheric nuclear tests films that have never before been seen by the public.

NAU Researchers Join DOE Project to Study the Soil Microbiome and Its Effect on Carbon Persistence

NAU Regents' Professor Bruce Hungate, director of the Center for Ecosystem Science and Society (Ecoss), recently joined a new initiative lead by LLNL to study how the soil microbiome controls the mechanisms that regulate the stabilization of the organic matter in soil.

Four Scientists Win the Los Alamos Medal

Los Alamos National Laboratory will award four former researchers with the Los Alamos Medal for their scientific contributions.


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What's the Noise Eating Quantum Bits?

The magnetic noise caused by adsorbed oxygen molecules is "eating at" the phase stability of quantum bits, mitigating the noise is vital for future quantum computers.

Rewritable Wires Could Mean No More Obsolete Circuitry

An electric field switches the conductivity on and off in atomic-scale channels, which could allow for upgrades at will.

Filtering Water Better than Nature

Water passes through human-made straws faster than the "gold standard" protein, allowing us to filter seawater.

Machine Learning Provides a Bridge to the Texture of the Quantum World

Machine learning and neural networks are the foundation of artificial intelligence and image recognition, but now they offer a bridge to see and recognize exotic insulating phases in quantum materials.

A Rare Quantum State Realized in a New Material

A revolutionary material harbors magnetism and massless electrons that travel near the speed of light--for future ultrasensitive, high-efficiency electronics and sensors.

Discovering Secrets of Superfluids

Observed atomic dynamics helps explain bizarre flow without friction that has been puzzling scientists for decades.

An Exotic State of Matter Discovered in 2-D Material

Electrons are forced to the edge of the road on a thin sheet of tungsten ditelluride.

Studying Crowd Behavior at MINERvA

Detector measures the energy a neutrino imparts to protons and neutrons to help explain the nature of matter and the universe.

Tweaking Quantum Dots Powers-Up Double-Pane Solar Windows

Using two types of "designer" quantum dots, researchers are creating double-pane solar windows that generate electricity with greater efficiency and create shading and insulation for good measure. It's all made possible by a new window architecture which utilizes two different layers of low-cost quantum dots tuned to absorb different parts of the solar spectrum.

See What Lies Beneath

Real-time imaging shows how hydrogen causes oxygen to leave a buried surface, transforming an oxide into a metal.


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