a b s t r a c tWithin this article, we report the characterization and organic vapor sensing properties of Langmuir-Blodgett (LB) thin films of calix[8]arenes. Surface pressure-area isotherms show that very stable monolayers are formed at the air-water interface. The LB film could be deposited onto different substrates which allowed the films to be characterized by UV, quartz crystal microbalance (QCM), surface plasmon resonance (SPR) and atomic force microscopy (AFM). The results indicate that good quality, uniform LB films can be prepared with transfer ratios of over 0.95. QCM results showed that the deposited mass of calix[8]arene monolayer onto a quartz crystal decreased from 693 to 204 ng as the number of layers is increased. AFM studies showed a smooth, and void free surface morphology with a rms value of 1.202 nm. The sensing abilities of this LB film towards the development of room temperature organic vapor sensing devices are also studied. Responses of the LB films to various vapors are fast, large, and reversible. It was found that the obtained LB film is significantly more sensitive to chloroform than other vapors. It can be concluded that this molecule could have a potential application in the research area of room temperature vapor sensing devices.
PTH nanoparticles and thin films were synthesized via a plasma polymerization technique using a double‐discharge system. This system has a fast filamentary discharge formed from the superposition of an ordinary low‐pressure dc glow discharge and a high‐current pulsed one. The samples were characterized by SEM, TEM, XPS, UV‐vis and FT‐IR spectroscopy. We found that superposing two discharges allows to control the morphology of the films. In the high‐temperature region, smooth and uniform thin films were produced, whereas gas‐phase polymerization resulted in films with grains of irregular shape. However, the films produced in the gas‐phase region exhibited highly thiophenic structures and could be dispersed in DCM, giving nanoparticles of 30 to 50 nm diameter.magnified image
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