Scanning ion conductance microscopy (SICM) is a new noncontact, high-resolution scanning probe microscopy technique, which has become increasingly popular in recent years. The hopping modecurrently the most widely used scanning modecan be used for imaging samples with complicated surface topographies. However, its slow scanning rate seriously restricts its broader application. This paper proposes a fast imaging control mode using a doublebarreled theta pipette as the probe, which effectively increases the imaging rate. In this mode, sample surface height information is obtained when the doublebarreled theta pipette approaches the sample in a two-step downward process. The ion current sum of two barrels and ion current of one barrel are used as feedback signals to approach the sample until the feedback signals decrease to the set threshold, respectively, thereby obtaining the height of the imaging point. First, this work used COMSOL to establish an SICM model and perform simulation analysis. The simulation results verified the proposed method's feasibility. Second, a scanning time mathematical model was established. The results revealed that the new method is superior to the traditional method in terms of imaging rate. Finally, experiments were performed on poly(dimethylsiloxane) (PDMS) samples using the two imaging modes described above. The results demonstrated that the new scanning mode could significantly improve the imaging rate of SICM without a loss in imaging quality and stability.

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This paper presents a new intelligent communication strategy for multi robots’ cooperation and competition, which combines the explicit with implicit communications via using the prediction of robotic behavior and a fuzzy communication approach. The multi robotic system employs a host computer and a team of mobile robots that understand the semantics and grammar as well as observe the codes of conduct. Based on the intelligent communication strategy, two robots playing a zero-sum game of hide-and-seek and two cooperative robots competing against a third robot have been explored. The results of simulation show that the new intelligent communication strategy and the algorithms for cooperation and competition used in the multi-robot system work successfully

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