DTN 133: AI Expands Search for New Battery Materials

Plus: Record-breaking magnetic field, muscle-bound micromirrors, 2025 IG Nobel Prize winners, quantum memories, sperm injecting robots, and more.

October 03, 2025

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“When Microsoft researchers in 2023 identified a new kind of material that could dramatically reduce the amount of lithium needed in rechargeable batteries, it felt like combing through a haystack in record time. That’s because their discovery began as 32 million possibilities and, with the help of artificial intelligence, produced a promising candidate within 80 hours…Around the world, researchers are busy trying to develop next-generation designs to replace or improve lithium-ion batteries, which use large quantities of rare, expensive, and difficult-to-acquire elements…The chemistries to do this are waiting out there to be discovered, and increasingly, researchers are harnessing AI and machine learning to do the work of sorting through the mountain of data.”

Artificial blood vessel with nanoparticles. Credit: CIC biomaGUNE.

Researchers are exploring ways to combine advanced 3D bioprinting techniques with nanomaterials to create tissue models that mimic real, living tissue and respond when external stimuli are applied. Bioprinting has emerged as a useful tool to enhance pathology; however, successful studies hinge on the realistic printing of organ and tissue models. Currently, one of the major challenges is identifying materials that are ideal for 3D printing and possess optimal properties to allow the cells to survive. Researchers in Europe had a breakthrough when they used a bioprinting technique that enabled them to produce a model of a blood vessel with concentric cylinders that mimic the various layers of an artery. Through specific printing techniques, researchers copied the image of a valve belonging to an actual patient and printed one that responds similarly to those found in the heart. It can open and close when an external stimulus is applied. While this is a major breakthrough, 3D bioprinting remains a very complex process that remains ripe for disruption. (via Phys.org)

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