Real-time simultaneous refractive index and thickness mapping of sub-cellular biology at the diffraction limit.

Mapping 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. This technology leverages a suitably engineered nanostructured membrane that stretches a biological analyte over its surface and absorbs transmitted light, generating complex reflection spectra from each sample point. The technique does not need pre-existing sample knowledge. It achieves 10-4 RI sensitivity and sub-nanometer thickness resolution on diffraction-limited spatial areas. We illustrate practical application by performing sub-cellular segmentation of HCT-116 colorectal cancer cells, obtaining complete three-dimensional reconstruction of the cellular regions with a characteristic length of 30 µm. These results can facilitate the development of real-time label-free technologies for biomedical studies on microscopic multicellular dynamics.

Enhanced Selectivity in the Electroproduction of H2 O2 via F/S Dual-Doping in Metal-Free Nanofibers.

Electrocatalytic two-electron oxygen reduction (2e- ORR) to hydrogen peroxide (H2 O2 ) 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 H2 O2 electrocatalysts based on metal-free carbon fibers with a fluorine and sulfur dual-doping strategy is engineered. Optimized samples yield with a high onset potential of 0.814 V versus reversible hydrogen electrode (RHE), an almost ideal 2e- pathway selectivity of 99.1%, outperforming most of the recently reported carbon-based or metal-based electrocatalysts. First principle theoretical computations and experiments demonstrate that the intermolecular charge transfer coupled with electron spin redistribution from fluorine and sulfur dual-doping is the crucial factor contributing to the enhanced performances in 2e- ORR. This work opens the door to the design and implementation of scalable, earth-abundant, highly selective electrocatalysts for H2 O2 production and other catalytic fields of industrial interest.