Oak Ridge National Laboratory

Story Tips: Pandemic impact, root studies, neutrons confirm, lab on a crystal and modeling fusion

Transportation – Gauging pandemic impact 

Newswise — Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States. 

Called the Pandemic Oil Demand Analysis, or PODA, this model compared mobility patterns before and during the COVID-19 pandemic, analyzing historical weekly motor travel trends and projecting future usage. 

“We developed this machine learning-based model by studying trip activities and corresponding fuel usage,” ORNL’s Shiqi (Shawn) Ou said. “The PODA analysis can serve as a useful tool to understand the impact of travel quarantine on fuel demand.”

In a Nature Energy study sponsored by Aramco Research Center, researchers focusing on mid-May until August determined that average fuel demand is not likely to reach pre-pandemic levels before October 2020. However, while a continued quarantine would have a negative impact on fuel demand temporarily, demand would likely recover to normal levels quicker. 

PODA data could help inform economic and energy planning. 

Image: https://www.ornl.gov/sites/default/files/2020-08/Transportation-Gauging_pandemic_impact_ORNL.jpg 

Caption: ORNL researchers developed a machine learning model to know the impact a pandemic can have on U.S. fuel demand prior to a travel quarantine. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy 

Ecosystem – At the root

Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming. 

The team working at DOE’s whole-ecosystem warming experiment in northern Minnesota found that shrub fine-root growth increased linearly by 130% for every degree increase in soil temperature – a response 20 times greater than other ecosystems. This was driven by soil drying in the usually sodden peatlands, which store one-third of the world’s soil carbon. 

According to published results, this response could explain why shrub coverage is increasing in these landscapes, which could shade out Sphagnum moss – a key species for carbon fixation in peatlands – and have downstream effects on peatland carbon storage. 

“This work helps us understand a previously unknown aspect of these ecosystems, the world belowground,” said Avni Malhotra of Stanford University, formerly of ORNL.  

Link: https://www.ornl.gov/sites/default/files/2020-08/FineRootGrowth.jpg 

Caption: A belowground snapshot reveals the complex maze of tree and shrub roots and their fungal partners in carbon-rich peatland soils. Credit: Colleen Iversen/ORNL, U.S. Dept. of Energy 

Link: https://www.ornl.gov/sites/default/files/2020-08/SPRUCE.png 

Caption: Scientists use the Spruce and Peatland Responses Under Changing Environments experiment in Minnesota to assess the response of northern peatlands to increases in temperature and atmospheric carbon dioxide. Credit: ORNL, U.S. Dept. of Energy 

Neutrons Ferromagnetic topological material 

A UCLA-led team that discovered the first intrinsic ferromagnetic topological insulator – a quantum material that could revolutionize next-generation electronics – used neutrons at Oak Ridge National Laboratory to help verify their finding. 

Topological insulators act as insulators on the inside while allowing electrons to flow across their surfaces. Their less-studied ferromagnetic counterparts are thought to hold useful properties for quantum technology. The researchers discovered the first intrinsic ferromagnetic topological insulator – consisting of manganese, bismuth and tellurium atoms – by stacking ferromagnetic molecular layers. 

To confirm the material’s intrinsic nature, the team used the High Flux Isotope Reactor at ORNL. 

“Neutron diffraction's high contrast can distinguish magnetic manganese atoms from others,” said ORNL’s Huibo Cao, co-author on the study published in Science Advances. “It is well-suited for the new two-dimensional material and its magnetism.” 

“Using neutron diffraction, we concluded the atomic arrangement in each layer and confirmed the ferromagnetic order to support this discovery,” added ORNL co-author Lei Ding. 

Image: https://www.ornl.gov/sites/default/files/2020-08/2017-S00412.jpg 

Caption: Researchers performed single-crystal neutron diffraction using the HB-3A four circle diffractometer to confirm the first intrinsic ferromagnetic topological insulator. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy 

Technology – Lab on a crystal

An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.

The “Lab-on-a-crystal,” designed on a commercially available quartz crystal microbalance, or QCM, measures materials’ interrelated responses to the environment in real time – something that traditionally required different specialized instruments, multiple experiments and a lot of time.

Modified QCM hardware has been incorporated into a machine learning platform that optimizes data collection and identifies correlations among several simultaneous measurements, including mechanical, electrical and optical.

“Being able to characterize multiple functionalities simultaneously at macro-, micro- and nanoscales on the same sample is a breakthrough for materials sciences. In a day, we can accomplish a month’s worth of experiments,” said ORNL’s Ilia Ivanov.

A collaboration with researchers from the European Union on advancing rapid-detection methods for enzymes that degrade milk quality highlights the platform’s broad applications to CNMS users. Ashley Huff

Image: https://www.ornl.gov/sites/default/files/2020-08/lab_on_crystal2.png 

Caption: ORNL’s Lab-on-a-crystal uses machine learning to correlate materials’ mechanical, optical and electrical responses to dynamic environments. Credit: Ilia Ivanov/ORNL, U.S. Dept. of Energy 

Computing – Enhancing fusion models

Combining expertise in physics, applied math and computing, Oak Ridge National Laboratory scientists are expanding the possibilities for simulating electromagnetic fields that underpin phenomena in materials design and telecommunications.

An initial application for the work is in fusion energy, for which modeling small-scale, energetic particle movements in fusion plasmas requires complex numerical simulations, particularly at plasma boundaries where electromagnetic fluctuations can result in energy loss or damage to the fusion reactor.

To overcome computational limitations and advance models of whole fusion reactors, the ORNL team developed the Adaptive Sparse Grid Discretization, or ASGarD, mathematical framework for solving complex equations.

As reported in a recent Computer Physics Communications paper, the team applied its framework to the foundational equations of electromagnetism, known as Maxwell’s equations, and demonstrated a 100-times reduction in the computational resources required for solving the equations compared to traditional methods. Katie Jones

Image: https://www.ornl.gov/sites/default/files/2020-08/Max1_t5e-1_EB.png

Caption: Using the ASGarD mathematical framework, scientists can model and visualize the electric fields, shown as arrows, circling around magnetic fields that are colorized to represent field magnitude of a fusion plasma. Credit: David Green/ORNL, U.S. Dept. of Energy


Register for reporter access to contact details

Nature Energy/Jul-2020; PNAS/Jul-2020; Science Advances/Jul-2020; Advanced Functional Materials/Jan-2020; Computer Physics Communications/

Filters close

Showing results

110 of 3395
Newswise: Historical Racial & Ethnic Health Inequities Account for Disproportionate COVID-19 Impact
22-Sep-2020 4:00 PM EDT
Historical Racial & Ethnic Health Inequities Account for Disproportionate COVID-19 Impact
American Thoracic Society (ATS)

A new Viewpoint piece published online in the Annals of the American Thoracic Society examines the ways in which COVID-19 disproportionately impacts historically disadvantaged communities of color in the United States, and how baseline inequalities in our health system are amplified by the pandemic. The authors also discuss potential solutions.

Released: 24-Sep-2020 5:05 PM EDT
In-person college instruction leading to thousands of COVID-19 cases per day in US
University of Washington

Reopening university and college campuses with primarily in-person instruction is associated with a significant increase in cases of COVID-19 in the counties where the schools are located.

Newswise: Some Severe COVID-19 Cases Linked to Genetic Mutations or Antibodies that Attack the Body
Released: 24-Sep-2020 3:25 PM EDT
Some Severe COVID-19 Cases Linked to Genetic Mutations or Antibodies that Attack the Body
Howard Hughes Medical Institute (HHMI)

Two new studies offer an explanation for why COVID-19 cases can be so variable. A subset of patients has mutations in key immunity genes; other patients have auto-antibodies that target the same components of the immune system. Both circumstances could contribute to severe forms of the disease.

access_time Embargo lifts in 2 days
Embargo will expire: 25-Sep-2020 6:30 PM EDT Released to reporters: 24-Sep-2020 3:20 PM EDT

A reporter's PressPass is required to access this story until the embargo expires on 25-Sep-2020 6:30 PM EDT The Newswise PressPass gives verified journalists access to embargoed stories. Please log in to complete a presspass application. If you have not yet registered, please Register. When you fill out the registration form, please identify yourself as a reporter in order to advance to the presspass application form.

17-Sep-2020 1:15 PM EDT
Accuracy of commercial antibody kits for SARS-CoV-2 varies widely

There is wide variation in the performance of commercial kits for detecting antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), according to a study published September 24 in the open-access journal PLOS Pathogens by Jonathan Edgeworth and Blair Merrick of Guy’s and St Thomas’ NHS Foundation Trust, Suzanne Pickering and Katie Doores of King's College London, and colleagues. As noted by the authors, the rigorous comparison of antibody testing platforms will inform the deployment of point-of-care technologies in healthcare settings and their use in monitoring SARS-CoV-2 infections.

24-Sep-2020 9:25 AM EDT
Loneliness levels high during COVID-19 lockdown
Newswise Review

During the initial phase of COVID-19 lockdown, rates of loneliness among people in the UK were high and were associated with a number of social and health factors, according to a new study published this week in the open-access journal PLOS ONE by Jenny Groarke of Queen’s University Belfast, UK, and colleagues.

Newswise: Genetic, immunological abnormalities in Type I interferon pathway are risk factors for severe COVID-19
24-Sep-2020 12:35 PM EDT
Genetic, immunological abnormalities in Type I interferon pathway are risk factors for severe COVID-19
Uniformed Services University of the Health Sciences (USU)

Individuals with severe forms of COVID-19 disease can present with compromised type I interferon (IFN) responses based on their genetics, according to results published in two papers today in the journal Science. Type I IFN responses are critical for protecting cells and the body from more severe disease after acute viral infection.

Newswise: Talking Alone: Researchers Use Artificial Intelligence Tools to Predict Loneliness
Released: 24-Sep-2020 1:45 PM EDT
Talking Alone: Researchers Use Artificial Intelligence Tools to Predict Loneliness
University of California San Diego Health

A team led by researchers at University of California San Diego School of Medicine has used artificial intelligence technologies to analyze natural language patterns to discern degrees of loneliness in older adults.

Showing results

110 of 3395