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February 23, 2021
New material is next step toward stable high-voltage long-life solid-state sodium-ion batteries
A team of researchers designed and manufactured a new sodium-ion conductor for solid-state sodium-ion batteries that is stable when incorporated into higher-voltage oxide cathodes. This new solid electrolyte could dramatically improve the efficiency and lifespan of this class of batteries. A proof of concept battery built with the new material lasted over 1000 cycles while retaining 89.3% of its capacity--a performance unmatched by other solid-state sodium batteries to date. Full Story
February 23, 2021
Tracking melting points above 4000 degrees Celsius
A materials engineer at the University of California San Diego is leading the development of a new research platform for studying high-performance materials, in particular new materials that melt above 4000 degrees Celsius (C). Full Story
February 15, 2021
New skin patch brings us closer to wearable, all-in-one health monitor
UC San Diego engineers have developed a soft, stretchy skin patch that can be worn on the neck to continuously track blood pressure and heart rate while measuring the wearer’s levels of glucose as well as lactate, alcohol or caffeine. It performs as well as commercial monitoring devices such as a blood pressure cuff, blood lactate meter, glucometer and breathalyzer. Full Story
January 29, 2021
Islands without structure inside metal alloys could lead to tougher materials for transportation, energy and defense
An international team of researchers produced islands of amorphous, non-crystalline material inside a class of new metal alloys known as high-entropy alloys. This discovery opens the door to applications in everything from landing gears, to pipelines, to automobiles. The new materials could make these lighter, safer, and more energy efficient. Full Story
January 14, 2021
New Method Makes Better Predictions of Material Properties Using Low Quality Data
By combining large amounts of low-fidelity data with smaller quantities of high-fidelity data, nanoengineers at UC San Diego have developed a machine learning method to more accurately predict the properties of new materials including, for the first time, disordered materials. Full Story