A flexible screen-printed rechargeable battery with up to 10 times more power than state of the art

A team of researchers has developed a flexible, rechargeable silver oxide-zinc battery with a five to 10 times greater areal energy density than state of the art. The battery also is easier to manufacture; while most flexible batteries need to be manufactured in sterile conditions, under vacuum, this one can be screen printed in normal lab conditions. The device can be used in flexible, stretchable electronics for wearables as well as soft robotics.

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Virus-like probes could help make rapid COVID-19 testing more accurate, reliable

Nanoengineers at the University of California San Diego have developed new and improved probes, known as positive controls, that could make it easier to validate rapid, point-of-care diagnostic tests for COVID-19 across the globe. The advance could help expand testing to low-resource, underserved areas.

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Environmentally friendly method could lower costs to recycle lithium-ion batteries

A new process for restoring spent cathodes to mint condition could make it more economical to recycle lithium-ion batteries. The process, developed by nanoengineers at the University of California San Diego, is more environmentally friendly than today’s methods; it uses greener ingredients, consumes 80 to 90% less energy, and emits about 75% less greenhouse gases.

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A Nanomaterial Path Forward for COVID-19 Vaccine Development

From mRNA vaccines entering clinical trials, to peptide-based vaccines and using molecular farming to scale vaccine production, the COVID-19 pandemic is pushing new and emerging nanotechnologies into the frontlines and the headlines.
Nanoengineers at UC San Diego detail the current approaches to COVID-19 vaccine development, and highlight how nanotechnology has enabled these advances, in a review article in Nature Nanotechnology published July 15.

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Machine learning technique speeds up crystal structure determination

A computer-based method could make it less labor-intensive to determine the crystal structures of various materials and molecules, including alloys, proteins and pharmaceuticals. The method uses a machine learning algorithm, similar to the type used in facial recognition and self-driving cars, to independently analyze electron diffraction patterns, and do so with at least 95% accuracy.

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