Argonne National Laboratory

Feature Stories

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Argonne researchers have created skyrmions – ordered regions of magnetic spins – by using a spiraling focused ion beam. (Illustration by Robert Horn / Argonne National Laboratory.)
Skyrmions created with a special spiral

Researchers at Argonne have found a way to control the creation of special textured surfaces, called skyrmions, in magnetically ordered materials.

April 5, 2017
Click to view infographic larger.
Four fantastic materials found at Argonne

New materials are the seeds for new technologies. Here are four discoveries with never-before-seen properties that could lead to new devices, innovations, or breakthroughs.

April 3, 2017
"To take the next step in nanoscience, we need to master reproduction and adaptation. How can we think about making it easier to repair individual units in artificial systems?"
Crowdsource: What will your field of science look like in 50 years?

CROWDSOURCE asks Argonne scientists from different disciplines to each provide a perspective on a complex question. Today we’re asking: What might your field of science look like in 50 years?

April 3, 2017
Scientists have used a new X-ray diffraction technique called Bragg single-angle ptychography to get a clear picture of how planes of atoms shift and squeeze under stress. (Image by Robert Horn/Argonne National Laboratory.)
Single-angle ptychography allows 3D imaging of stressed materials

Scientists have used a new X-ray diffraction technique called Bragg single-angle ptychography to get a clear picture of how planes of atoms shift and squeeze under stress.

March 21, 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
Building project managers and scientific leads confer at the site of a new clean room under construction at Argonne National Laboratory. When completed, the lab will enable scientists and engineers to build extremely sensitive detectors — such as those capable of detecting light from the early days of the universe. (Image by Mark Lopez/Argonne National Laboratory.)
Building a room clean enough to make sensors to find light from the birth of the universe

Work is underway at Argonne on an expansion of its “clean room.” The new lab will be specially suited for building parts for ultra-sensitive detectors — such as those to carry out improved X-ray research, or for the South Pole Telescope to search for light from the early days of the universe.

October 17, 2016
No one has yet imaged an entire brain down to the level of individual cells; but Bobby Kasthuri has a plan to do just that using intensive computing and imaging resources at Argonne. Above is a simulation showing an unusual configuration of a neuron: one axon (blue) connected to multiple points on a dendrite (green). The total image is smaller than the diameter of a single human hair. (Click to view larger.)
Adventures of the first neuroscientist at Argonne

Bobby Kasthuri wants to map the human brain. Unlike most brain researchers, he wants a literal map: a 3D picture of every single neuron inside a brain. All 100 billion of them — or maybe 80 billion. Or maybe 120 billion?

March 16, 2016
"We’re spending a lot of power to reduce the frequency of error. What if you built a system that makes mistakes much more frequently but uses much less energy?" - Marc Snir, director of Argonne's mathematics & computer science division
Crowdsource: How do we make computers faster?

Five Argonne scientists with very different specialties answer the same question: "How do we make computers faster?"

March 7, 2016
Argonne engineer Aaron Greco works to improve the reliability of wind turbines using tribology. (Click to view larger.)
7 things you might not know about tribology

Objects rubbing together cause friction which eventually wears down one or the other surface. Finding ways to reduce this friction—in your knees, in an engine, or in factory machinery—can help scientists develop stronger materials that last longer and slide easier, which increases efficiency.

March 7, 2016