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Fragile no more, nickelates get an upgrade that changes how superconductivity endures

Discovered in 2019, the material known as nickelates has intrigued researchers for its potential to become a superconductor at elevated temperatures—a property that could significantly advance such fields as quantum science and energy transmission. However, it’s a very unstable material and difficult to work with. But the lab of Professor Charles Ahn has developed a method that could enhance superconductivity in these materials. The results are published in Nature Communications.

With their ability to conduct electricity with no resistance, superconductors are a key component to quantum computing, medical imaging, and a number of other fields. A group of copper-oxide compounds known as cuprates have long been central to the study of high-temperature superconductivity (“high temperature” is a relative term—they still need to be kept in very cold environments). Nickelates are especially exciting because they share some of cuprates’ key electronic features while offering a new platform for materials design and tuning.

Enter nickelates, a material with many similarities to cuprates, but with the potential to eventually become even more useful to scientists. Dung Vu, a postdoctoral associate who led the study, noted that synthesizing nickelate thin films is “notoriously difficult.” The Ahn lab is one of the few in the world with the ability to do so.

Better volcano eruption predictions on Earth—and Venus—thanks to Mauna Loa study

When Mauna Loa erupted in 2022, the largest lava flow headed on a path headed directly toward Daniel K. Inouye State Highway 200, also known as Saddle Road, a critical route that carries many residents from their homes on one side to their jobs on the other.

No one could accurately predict whether the lava would continue to flow and eventually block the highway, or stop short, sparing the road.

However, when the volcano next erupts scientists will be better able to monitor the eruption in real time and make more accurate predictions about where the lava will flow and when the volcano might erupt. These advances are thanks to the availability of satellite data from public and private sources as well as machine learning algorithms developed at Pitt with help from a colleague in Italy, as highlighted in a recent publication in the Journal of Volcanology and Geothermal Research.

Synchrotron safety monitoring sheds light on dark photons

A scientist from Tokyo Metropolitan University has proposed using safety monitoring at synchrotron facilities to study the properties of dark photons, hypothetical particles proposed to explain dark matter. Calculations show that the X-ray source at these sites and a Geiger-Muller counter behind safety shielding could be used to propose limits on how strongly dark photons interact with normal photons. The experiment would not involve a dedicated facility and could run alongside other experiments.

Experimental particle physics is often a world of enormous collaborations, multinational funding, and dedicated sites and facilities, yielding groundbreaking triumphs such as the discovery of the Higgs boson.

The community has now turned its attention to the hunt for dark matter, some of which might account for the “missing” portion of mass in the known universe eluding detection by conventional means.

Neural network speeds tuning of attosecond light pulses for physics experiments

Researchers from Skoltech and the Shanghai Institute of Optics and Fine Mechanics have developed an approach that helps optimize the parameters of a laser-plasma source of attosecond pulses—ultrashort flashes of light used in physics experiments. Instead of relying on a large number of time-consuming calculations, the team trained a neural network to quickly identify promising settings and thereby speed up the optimization of the sophisticated laboratory equipment.

The results were published in Communications in Nonlinear Science and Numerical Simulation.

Attosecond pulse sources are used as research tools. They are applied in ultrafast spectroscopy, studies of magnetic materials, chiral molecules, and electron dynamics in matter. The goal of this work is to make it faster to tune a light source with the required properties for such experiments.

Why dolphins swim so fast: The secrets of hidden whirlpools

Dolphins are famous for their speed and agility in the water, but what exactly allows them to swim so effectively? Scientists have been asking this question for years, hoping to learn how to optimize propulsion in fluids from these elegant creatures.

When a dolphin swims, it flaps its tail up and down in a kicking motion. This motion pushes water backward, generating a turbulent flow filled with swirling currents of many different sizes. Until now, it has been difficult to determine how these complex motions conspire to propel the dolphin forward.

Self-organizing ‘pencil beam’ laser could help scientists design brain-targeted therapies

MIT researchers discovered a paradoxical phenomenon in optical physics that could enable a new bioimaging method that’s faster and higher-resolution than existing technology. They discovered that, under the right conditions, a chaotic mess of laser light can spontaneously self-organize into a highly focused “pencil beam.”

Using this self-organized pencil beam, the researchers captured 3D images of the human blood-brain barrier 25 times faster than the gold-standard method, while maintaining comparable resolution. By showing individual cells absorbing drugs in real-time, this technology could help scientists test whether new drugs for neurodegenerative diseases like Alzheimer’s or ALS reach their targets in the brain, with greater speed and resolution.

“The common belief in the field is that if you crank up the power in this type of laser, the light will inevitably become chaotic. But we proved that this is not the case. We followed the evidence, embraced the uncertainty, and found a way to let the light organize itself into a novel solution for bioimaging,” says Sixian You, assistant professor in the MIT Department of Electrical Engineering and Computer Science (EECS), a member of the Research Laboratory for Electronics, and senior author of a paper on this imaging technique.

DuctGPT demonstrates how AI can accelerate discovery of next-generation fusion materials

Scientists at Ames National Laboratory developed a new artificial intelligence (AI) tool that accelerates discovery of materials needed for next-generation fusion energy systems. The tool, DuctGPT, combines advanced AI with physics-based modeling to help researchers predict materials with the appropriate properties to function in the extreme conditions inside of fusion reactors.

This research is discussed in “DuctGPT: A Generative Transformer for Forward Screening of Ductile Refractory Multi-Principal Element Alloys,” published in Acta Materialia.

The challenge is to rapidly explore a wide range of potential alloy compositions that can maintain high-temperature strength, while retaining the ductility necessary for manufacturing the materials.

Breakthrough Crystal Lets Scientists “Write” Nanoscale Patterns With Light

A team of scientists has uncovered a crystal that can be reshaped and programmed using ordinary light, opening a new path for building optical technology.

Researchers at the XPANCEO Emerging Technologies Research Center, working alongside Nobel Laureate Prof. Konstantin Novoselov (University of Manchester and the National University of Singapore), have identified unusual optical behavior in arsenic trisulfide (As2S3), a crystalline van der Waals semiconductor. Their work shows that this material can be permanently altered by light and even shaped at the nanoscale using simple continuous-wave (CW) light. This approach eliminates the need for expensive cleanroom lithography or advanced femtosecond laser systems.

Understanding Refractive Index and Photorefractivity.

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