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Intricate Nanotextures in Thin-Film Materials Shown by Scientists

With the use of integration of high-powered X-Rays, machine learning, and phase-retrieval algorithms, Cornell scientists showed the intricate nanotextures in thin-film materials, providing researchers with a novel, streamlined method to examining likely candidates for microelectronics and quantum computing, among other applications.

Machine learning enhances X-ray imaging of na

Using a combination of high-powered X-rays, phase-retrieval algorithms and machine learning, Cornell researchers revealed the intricate nanotextures in thin-film materials, offering scientists a new, streamlined approach to analyzing potential candidates for quantum computing and microelectronics, among other applications.

Machine learning enhances X-ray imaging of nanotextures

Cornell energy center receives $12 6M in renewed funding for alkaline fuel cell work

Cornell’s Center for Alkaline-Based Energy Solutions (CABES) has received renewal funding of $12.6 million for a four-year period to continue its work developing advanced fuel cell technologies in alkaline media. The center, part of the Energy Frontier Research Center (EFRC) program supported by the US Department of Energy, was created.

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