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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.

It has long been assumed that the entire area of the electrode shadowed by each bubble would be effectively inactivated. But it turns out that a much smaller area — roughly the area where the bubble actually contacts the surface — is blocked from its electrochemical activity. The new insights could lead directly to new ways of patterning the surfaces to minimize the contact area and improve overall efficiency.

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.

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