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Experimental and computational study of the effect of temperature on the electro-polymerization process of Thiophene

Article

Authorship
Camarada, María Belén ; Romero, M. ; GIMENEZ, MARIA CECILIA ; Schmickler, Wolfgang ; del Valle, M. A.
Date
2013
Publishing House and Editing Place
Scientific Research Publishing
Magazine
Open Journal of Organic Polymer Materials, vol. 3 (pp. 59-67) - ISSN 2164-5736
Scientific Research Publishing
ISSN
2164-5736
Summary Information provided by the agent in SIGEVA
Temperature effect on the nucleation and growth mechanisms (NGM) of poly(thiophene) (PTh) was investigated through experimental and computational tools. The computational simulation method was based on a kinetic Monte Carlo algorithm. It reproduced key processes such as diffusion, oligomerization, and the precipitation of oligomers onto the electrode surface. Electrochemical synthesis conditions at temperatures between 263 and 303 K were optimized. The deconvolution of the i-t transients reflec... Temperature effect on the nucleation and growth mechanisms (NGM) of poly(thiophene) (PTh) was investigated through experimental and computational tools. The computational simulation method was based on a kinetic Monte Carlo algorithm. It reproduced key processes such as diffusion, oligomerization, and the precipitation of oligomers onto the electrode surface. Electrochemical synthesis conditions at temperatures between 263 and 303 K were optimized. The deconvolution of the i-t transients reflected two contributions: a progressive nucleation with three-dimensional growth controlled by diffusion and the other by charge transfer, PN3Ddif and PN3Dct, respectively. As temperature decreased, a diminution of the charge associated to each contribution was observed and the nucleation induction time increased. Experimental and computational evidence indicated that temperature does not change the nucleation and growth mechanism (NGM). This effect was ascribed to kinetic factors rather than to film conductivity. This work contrasts simulation and experimental evidence and demonstrates how computational simulations can help to understand the electrochemical process of conducting polymers formation.
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Key Words
Electro-PolymerizationThiopheneConducting PolymersKinetic Monte Carlo
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