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We reported the selective electrochemical reduction of oxygen (O 2 )t oh ydroxylr adicals (COH) via 3-electron pathway with FeCo alloye ncapsulated by carbon aerogel (FeCoC). The graphite shell with exposed -COOH is conducive to the 2-electron reduction pathway for H 2 O 2 generation stepped by 1-electron reduction towardst oCOH. The electrocatalytic activity can be regulated by tuning the local electronic environment of carbon shell with the electrons coming from the inner FeCo alloy. The new strategy of COH generation from electrocatalytic reduction O 2 overcomes the rate-limiting step over electron transfer initiated by reduction-/oxidation-state cycle in Fenton process.F ast and complete removal of ciprofloxacin was achieved within 5min in this proposed system, the apparent rate constant (k obs )w as up to 1.44 AE 0.04 min À1 ,w hich is comparable with the state-of-the-art advanced oxidation processes.T he degradation rate almost remains the same after 50 successive runs,s uggesting the satisfactory stability for practical applications.

A fundamental challenge in fluorescence microscopy is the photon shot noise arising from the inevitable stochasticity of photon detection. Noise increases measurement uncertainty and limits imaging resolution, speed and sensitivity. To achieve high-sensitivity fluorescence imaging beyond the shot-noise limit, we present DeepCAD-RT, a self-supervised deep learning method for real-time noise suppression. Based on our previous framework DeepCAD, we reduced the number of network parameters by 94%, memory consumption by 27-fold and processing time by a factor of 20, allowing real-time processing on a two-photon microscope. A high imaging signal-to-noise ratio can be acquired with tenfold fewer photons than in standard imaging approaches. We demonstrate the utility of DeepCAD-RT in a series of photon-limited experiments, including in vivo calcium imaging of mice, zebrafish larva and fruit flies, recording of three-dimensional (3D) migration of neutrophils after acute brain injury and imaging of 3D dynamics of cortical ATP release. DeepCAD-RT will facilitate the morphological and functional interrogation of biological dynamics with a minimal photon budget.