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The instability of supported poly(methyl methacrylate) (PMMA) thin films in water has been investigated. It is found that PMMA films partially detach from the solid substrate, resulting in the formation of bubbles under water. The process is reversible. Surface morphology analysis shows that the radius of curvature of the bubbles is dependent on the thickness of the PMMA films and is independent of the treatment of the films, such as the annealing temperature and the annealing time. Theoretical analysis based on a two-layer model (the swollen layer and the interior layer) shows that the partial swelling of PMMA in water is the physical origin of bubble formation.

The thickness dependence of the chemical and physical properties is one fundamental characteristic shared by many twodimensional layered transition-metal dichalcogenides, including molybdenum disulfide (MoS 2 ). Recently, in order to expand the scope of applications of MoS 2 , surface functionalization has been employed to engineer its chemical and electrical properties for the purposes of drug delivery, photothermal therapy, gas sensing, and biosensing. Here, we report a facile method for controlled functionalization of MoS 2 fieldeffect transistors of a wide range of thicknesses with α-lipoic acid (LA). Atomic force microscopy (AFM), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS) show evidence of chemical bonding. After functionalization, a significant increase of on current is observed in the MoS 2 transistors, caused by the enhancement of electronic mobility. The maximum increase of mobility can reach ∼100% for monolayer devices. The thickness dependence of the mobility enhancement is analyzed, and a theoretical model based on vacancy filling and charge impurity scattering is proposed to reveal the microscopic origin. These results provide new opportunities of controlling the electronic properties of MoS 2 by surface functionalization.

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Intending to mimic the operating mechanism of biological neural systems, a self organizing map-based approach to task assignment of a swarm of robots in 3-D dynamic environments is proposed in this paper. This approach integrates the advantages and characteristics of biological neural systems. It is capable of dynamically planning the paths of a swarm of robots in 3-D environments under uncertain situations, such as when some robots are presented in or broken down or when more than one robot is needed for some special task locations. A Bezier path optimizing algorithm and a parameter adjusting algorithm are integrated in this paper. It is capable of reducing the complexity of the robot navigation control and limiting the number of convergence iterations. The simulation results with different environments demonstrate the effectiveness of the proposed approach.

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