Polydopamine (PDA) is fast becoming a popular surface modification technique. Detailed understanding of the ion permeability properties of PDA films will improve their applications. Herein, we report for the first time the thickness-independent ion permeability of PDA films using a Prussian blue (PB)-based electrochemical method. In this method, PDA films are deposited via ammonium persulfate-induced dopamine polymerization onto a PB electrode. The ion permeability of the PDA films can thus be detected by observing the changes in electrochemical behaviors of the PB coated by PDA films. On the basis of this method, it was unexpectedly found that the PDA films with thickness greater than 45 nm (e.g., ~60 and ~113 nm) can exhibit pH-switchable but thickness-insensitive permeability to monovalent cations such as potassium and sodium ions. These observations clearly indicate the presence of a continuous network of interconnected intermolecular voids within PDA films, regardless of film thickness.

In this study we report the improved stability of Prussian blue (PB) films in neutral and alkaline solutions via an electrochemical post-treatment procedure. In this procedure, PB films synthesized via the electroless deposition method at glassy carbon electrodes were continuously cycled for 300 cycles (∼12 h) between the potential limits of +0.6 and -0.1 V (vs. Ag/AgCl) at a scan rate of 10 mV s(-1) in 2.0 M KCl solution of pH 3. It was found that after such electrochemical post-treatment the PB films exhibit dramatically improved stability in neutral and alkaline solutions. Control experiments confirmed that the longer potential cycling time and the higher KCl concentration are indispensable. In addition, interestingly, it was found that after the successive potential cycling treatments the shape of PB nanoparticles evolves from a sphere into a cube as well as a small amount of a rectangle, indicating the electrochemically induced shape evolution of nanocrystals. The electrochemical post-treatment procedure proposed here could be useful for the development of PB-based devices with improved stability, for instance, biosensors, biofuel cells, etc.

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Shadow detection and removal in real scene images are a significant problem for target detection. This work proposes an improved shadow detection and removal algorithm for urban video surveillance. First, the foreground is detected by background subtraction and the shadow is detected by HSV color space. Using local variance and OTSU method, we obtain the moving targets with texture features. According to the characteristics of shadow in HSV space and texture feature, the shadow is detected and removed to eliminate the shadow interference for the subsequent processing of moving targets. Finally, we embed our algorithm into C/S framework based on the HTML5 web socket protocol. Both the experimental and actual operation results show that the proposed algorithm is efficient and robust in target detection and shadow detection and removal under different scenes.