Recent advancements in artificial intelligence have significantly expanded capabilities in processing language and images. However, the challenge of comprehensively understanding video content still needs to be solved. The main problem is the requirement to process real-time multidimensional video information at data rates exceeding 1 Tb/s, a demand that current hardware technologies cannot meet.
View Article and Find Full Text PDFPhotoelectrochemical (PEC) water splitting is attracting significant research interest in addressing sustainable development goals in renewable energy. Current state-of-the-art, however, cannot provide photoanodes with simultaneously high efficiency and long-lasting lifetime. Here, large-scale NiFe oxyhydroxides-alloy hybridized co-catalyst layer that exhibits an applied bias photon-to-current efficiency (ABPE) of 4.
View Article and Find Full Text PDFMapping the cellular refractive index (RI) is a central task for research involving the composition of microorganisms and the development of models providing automated medical screenings with accuracy beyond 95%. These models require significantly enhancing the state-of-the-art RI mapping capabilities to provide large amounts of accurate RI data at high throughput. Here, we present a machine-learning-based technique that obtains a biological specimen's real-time RI and thickness maps from a single image acquired with a conventional color camera.
View Article and Find Full Text PDFElectrocatalytic two-electron oxygen reduction (2e ORR) to hydrogen peroxide (H O ) is attracting broad interest in diversified areas including paper manufacturing, wastewater treatment, production of liquid fuels, and public sanitation. Current efforts focus on researching low-cost, large-scale, and sustainable electrocatalysts with high activity and selectivity. Here a large-scale H O electrocatalysts based on metal-free carbon fibers with a fluorine and sulfur dual-doping strategy is engineered.
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