Argonne National Laboratory

Feature Stories

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Argonne nanoscientist Xiao-Min Lin works with the shear cell device that enabled the new discovery in shear-thickening fluids. The polycarbonate cell holds the nanoparticle suspension and the mechanical response of the fluid is measured by the transducer in the rheometer above. The X-ray beam is focused on the sample from the left. (Image by Argonne National Laboratory.)
Through thick and thin

Researchers solve a decades-old question: Is particle ordering responsible for the thickening of some industrial products when stirred rapidly? The answer brings us one step closer to solving complex industrial production problems.

April 13, 2018
Academic researchers look to Argonne’s Mira supercomputer to better understand boiling phenomena, bubble formation and two-phase bubbly flow inside nuclear reactors. (Image courtesy of Igor Bolotnov / North Carolina State University.)
Tiny bubbles

Bubbles are a linchpin of nuclear engineering, helping to explain the natural world, predict safety issues and improve the operation of the existing and next-generation nuclear fleet. High-performance supercomputers like Mira, located at Argonne, are helping researchers understand the phenomena of bubbling behavior more quickly.

April 4, 2018
A snapshot of silicene (shown in yellow), a 2-D material made up of silicon atoms, as it grows on iridium substrate (shown in red). The image was taken from a molecular dynamics simulation, which Argonne researchers used to predict the growth and evolution of silicene. (Image courtesy of Joseph Insley / Argonne National Laboratory.)
The flat and the curious

Argonne researchers have simulated the growth of the 2-D material silicene. Their work, published in Nanoscale, delivers new and useful insights on the material’s properties and behavior and offers a predictive model for other researchers studying 2-D materials.

November 6, 2017
Schematic of the experimental setup. Six YIG/Pt nanowires (in red) integrated in the signal arm (S) are measured in parallel. A bias-T is utilized for simultaneous RF transmission and DC voltage detection by lock-in techniques. (Image adapted from Jungfleisch et al., Nano Lett., 17, 8 (2017).)
Report sheds new insights on the spin dynamics of a material candidate for low-power devices

In a report published in Nano LettersArgonne researchers reveal new insights into the properties of a magnetic insulator that is a candidate for low-power device applications; their insights form early stepping-stones towards developing high-speed, low-power electronics that use electron spin rather than charge to carry information.

May 22, 2017
Lisa Goodenough, astrophysicist
Science in the 1000 most common words: nuclear engineering & Dark Matter

Webcomic author Randall Munroe is famous for his series that explains science using only the 1000 most commonly used words in the English language. So we asked two of our postdoctoral researchers to try a hand at explaining their research the same way.

April 3, 2017
Anaerobic bacteria play a central role in cycling carbon and other key elements throughout Earth. A new study shows that the behavior of these microbes is significantly affected by the types of carbon “food” sources available to them. (Image by Argonne National Laboratory.)
Study of microbes reveals new insight about Earth’s geology and carbon cycles

Tiny microbes play a big role in cycling carbon and other key elements through our air, water, soil and sediment. Researchers who study these processes at Argonne National Laboratory have discovered that these microbial communities are significantly affected by the types of carbon “food” sources available. Their findings reveal that the type of carbon source affects not only the composition and activity of natural microbial communities, but also in turn the types of mineral products that form in their environment.

January 30, 2017
In a new study, Argonne scientists have discovered a way to confine the behavior of electrons by using extremely high magnetic fields. (Image by Argonne National Laboratory.)
Electrons "puddle" under high magnetic fields, study reveals

In a new study, researchers used extremely high magnetic fields — equivalent to those found in the center of neutron stars — to alter electronic behavior. By observing the change in the behavior of these electrons, scientists may be able to gain an enriched understanding of material behavior.

January 3, 2017
The Argonne research team that has pioneered the use of machine learning tools in 2-D material modeling. (Image by Wes Agresta/Argonne National Laboratory.)
Machine learning enables predictive modeling of 2-D materials

In a study published in The Journal of Physical Chemistry Letters, a team of researchers led by Argonne computational scientist Subramanian Sankaranarayanan described their use of machine learning tools to create the first atomic-level model that accurately predicts the thermal properties of stanene, a 2-D material made up of a one-atom-thick sheet of tin.

December 7, 2016
"I was interested in mathematics and problem solving from a very early age," said Katrin Heitmann, a computational physicist and computational scientist in Argonne's high energy physics department.
Women in STEM careers: Breaking down barriers

Three Argonne researchers share their experiences, why they pursued STEM careers, and how they’re continuing to help the next generation of scientists and engineers to flourish.

March 7, 2016
What might precipitation over the United States look like in 2094? Two Argonne researchers ran the highest-resolution climate forecast ever done for North America — dividing the continent into squares 12 km at a side. These two sample maps show different scenarios to project how much more (green) or less (brown) it would rain in a ten-year period at the end of the century versus how much it rained in 1995-2004. (Crosshatching indicates statistically significant changes).
(Rain)cloud computing: Researchers work to improve how we predict climate change

Two Argonne scientists work on simulations that project what the climate will look like 100 years from now. Last year, they completed the highest resolution climate forecast ever done for North America, dividing the continent into squares just over seven miles on a side — far more detailed than the standard 30 to 60 miles.

March 3, 2016