NEWS RELEASES

Inspired by an artist’s stencils, researchers have developed atomic-level precision patterning on nanoparticle surfaces, allowing them to “paint” gold nanoparticles with polymers to give them an array of new shapes and functions. The “patchy nanoparticles” developed by University of Illinois Urbana-Champaign researchers and collaborators at the University of Michigan and Penn State University can be made in large batches, used for a variety of electronic, optical or biomedical applications, or used as building blocks for new complex materials and metamaterials. 

The Princeton Plasma Physics Laboratory will provide critical measurement technology for the world’s largest fusion machine, JT-60SA. It is among the first contributions to the fusion system from an institution outside of Japan and Europe.

Breakthrough from Princeton team reveals exotic quantum state that coherently blends many-body correlation and quantum topology—two key concepts of modern quantum physics in a single material. 

A team of researchers at the Ming Hsieh Department of Electrical and Computer Engineering at USC has created a new breakthrough in photonics: the design of the first optical device that follows the emerging framework of optical thermodynamics. The work, reported in Nature Photonics, introduces a fundamentally new way of routing light in nonlinear systems—meaning systems that do not require switches, external control, or digital addressing. Instead, light naturally finds its way through the device, guided by simple thermodynamic principles. The implications of the new approach extend far beyond the laboratory. As computing and data processing continue to push the limits of traditional electronics, various companies—including chip designers —are exploring optical interconnects as a way to move information faster and more efficiently. By providing a natural, self-organizing way to direct light signals, however, optical thermodynamics could accelerate the development of such technologies. Beyond chip-scale data routing, the framework may also influence telecommunications, high-performance computing, and even secure information processing, offering a path toward devices that are both simpler and more powerful.

To increase energy efficiency and reduce the carbon footprint of hydrogen fuel production, Fanglin Che, associate professor in the Department of Chemical Engineering at Worcester Polytechnic Institute, is leveraging the power and potential of machine learning and computational modeling. The multi-university team she leads has completed a research study that was just published in Nature Chemical Engineering.