Lifeboat Foundation

In 2018, a discovery in materials science sent shock waves throughout the community. A team showed that stacking two layers of graphene at a precise magic angle turned it into a superconductor, says Ritesh Agarwal of the University of Pennsylvania. This sparked the field of twistronics, revealing that twisting layered materials could unlock extraordinary material properties.

Building on this concept, Agarwal, Penn theoretical physicist Eugene Mele, and collaborators have taken twistronics into new territory. In a study published in Nature (“Opto-twistronic Hall effect in a three-dimensional spiral lattice”), they investigated spirally stacked tungsten disulfide (WS 2) crystals and discovered that, by twisting these layers, light could be used to manipulate electrons. The result is analogous to the Coriolis force, which curves the paths of objects in a rotating frame, like how wind and ocean currents behave on Earth.

“What we discovered is that by simply twisting the material, we could control how electrons move,” says Agarwal, Srinivasa Ramanujan Distinguished Scholar in the School of Engineering and Applied Science. This phenomenon was particularly evident when the team shined circularly polarized light on WS 2 spirals, causing electrons to deflect in different directions based on the material’s internal twist.

Industrial electrochemical processes that use electrodes to produce fuels and chemical products are hampered by the formation of bubbles that block parts of the electrode surface, reducing the area available for the active reaction. Such blockage reduces the performance of the electrodes by anywhere from 10 to 25 percent.

But new research reveals a decades-long misunderstanding about the extent of that interference. The findings show exactly how the blocking effect works and could lead to new ways of designing electrode surfaces to minimize inefficiencies in these widely used electrochemical processes.

Continue reading “Bubble findings could unlock better electrode and electrolyzer designs” »

Quantum AI, the fusion of quantum computing and artificial intelligence, is poised to revolutionize industries from finance to healthcare.

Next-generation technologies, such as leading-edge memory storage solutions and brain-inspired neuromorphic computing systems, could touch nearly every aspect of our lives — from the gadgets we use daily to the solutions for major global challenges. These advances rely on specialized materials, including ferroelectrics — materials with switchable electric properties that enhance performance and energy efficiency.

A research team led by scientists at the Department of Energy’s Oak Ridge National Laboratory has developed a novel technique for creating precise atomic arrangements in ferroelectrics, establishing a robust framework for advancing powerful new technologies. The findings are published in Nature Nanotechnology (“On-demand nanoengineering of in-plane ferroelectric topologies”).

“Local modification of the atoms and electric dipoles that form these materials is crucial for new information storage, alternative computation methodologies or devices that convert signals at high frequencies,” said ORNL’s Marti Checa, the project’s lead researcher. “Our approach fosters innovations by facilitating the on-demand rearrangement of atomic orientations into specific configurations known as topological polarization structures that may not naturally occur.” In this context, polarization refers to the orientation of small, internal permanent electric fields in the material that are known as ferroelectric dipoles.

Neuromorphic engineering is a cutting-edge field that focuses on developing computer hardware and software systems inspired by the structure, function, and behavior of the human brain. The ultimate goal is to create computing systems that are significantly more energy-efficient, scalable, and adaptive than conventional computer systems, capable of solving complex problems in a manner reminiscent of the brain’s approach.

This interdisciplinary field draws upon expertise from various domains, including neuroscience, computer science, electronics, nanotechnology, and materials science. Neuromorphic engineers strive to develop computer chips and systems incorporating artificial neurons and synapses, designed to process information in a parallel and distributed manner, akin to the brain’s functionality.

Key challenges in neuromorphic engineering encompass developing algorithms and hardware capable of performing intricate computations with minimal energy consumption, creating systems that can learn and adapt over time, and devising methods to control the behavior of artificial neurons and synapses in real-time.

A Falcon 9 upper stage got some gorgeous, faraway looks at our planet.

Researchers have developed a method to recreate the formation of Lewy bodies in human neurons, shedding light on the essential roles of alpha-synuclein and immune responses in their development. This breakthrough offers new insights into Parkinson’s disease, showing that Lewy bodies form only under specific conditions and highlighting the potential…

Researchers at KIT’s Physikalisches Institut have developed a method to precisely control diamond tin-vacancy qubits.

A well came back to life Wednesday and hasn’t stopped since, with experts trying to get to the bottom of things.