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Fabrication, structural characterization, and applications of langmuir and langmuir-blodgett films of a poly(azo)urethane
Authors:Alessio Priscila  Ferreira Daniele M  Job Aldo E  Aroca Ricardo F  Riul Antonio  Constantino Carlos J L  Gonzalez Eduardo R Pérez
Institution:Departamento de Física, Química e Biologia, Faculdade de Ciências e Tecnologia, UNESP, Presidente Prudente/SP, 19060-080, Brazil.
Abstract:The synthesis of a poly(azo)urethane by fixing CO(2) in bis-epoxide followed by a polymerization reaction with an azodiamine is presented. Since isocyanate is not used in the process, it is termed "clean method" and the polymers obtained are named "NIPUs" (non-isocyanate polyurethanes). Langmuir films were formed at the air-water interface and were characterized by surface pressure vs mean molecular area per mer unit (Pi-A) isotherms. The Langmuir monolayers were further studied by running stability tests and cycles of compression/expansion (possible hysteresis) and by varying the compression speed of the monolayer formation, the subphase temperature, and the solvents used to prepare the spreading polymer solutions. The Langmuir-Blodgett (LB) technique was used to fabricate ultrathin films of a particular polymer (PAzoU). It is possible to grow homogeneous LB films of up to 15 layers as monitored using UV-vis absorption spectroscopy. Higher number of layers can be deposited when PAzoU is mixed with stearic acid, producing mixed LB films. Fourier transform infrared (FTIR) absorption spectroscopy and Raman scattering showed that the materials do not interact chemically in the mixed LB films. The atomic force microscopy (AFM) and micro-Raman technique (optical microscopy coupled to Raman spectrograph) revealed that mixed LB films present a phase separation distinguishable at micrometer or nanometer scale. Finally, mixed and neat LB films were successfully characterized using impedance spectroscopy at different temperatures, a property that may lead to future application as temperature sensors. Principal component analysis (PCA) was used to correlate the data.
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